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Climate change resilient agricultural practices: A learning experience from indigenous communities over India

Affiliation South Asian Forum for Environment, India

* E-mail: [email protected] , [email protected]

Affiliation Ecole Polytechnique Fédérale de Lausanne (Swiss Federal Institute of Technology), Lausanne, Switzerland

• Amitava Aich, 
• Dipayan Dey, 
• Arindam Roy

Published: July 28, 2022

• https://doi.org/10.1371/journal.pstr.0000022
• Reader Comments

The impact of climate change on agricultural practices is raising question marks on future food security of billions of people in tropical and subtropical regions. Recently introduced, climate-smart agriculture (CSA) techniques encourage the practices of sustainable agriculture, increasing adaptive capacity and resilience to shocks at multiple levels. However, it is extremely difficult to develop a single framework for climate change resilient agricultural practices for different agrarian production landscape. Agriculture accounts for nearly 30% of Indian gross domestic product (GDP) and provide livelihood of nearly two-thirds of the population of the country. Due to the major dependency on rain-fed irrigation, Indian agriculture is vulnerable to rainfall anomaly, pest invasion, and extreme climate events. Due to their close relationship with environment and resources, indigenous people are considered as one of the most vulnerable community affected by the changing climate. In the milieu of the climate emergency, multiple indigenous tribes from different agroecological zones over India have been selected in the present study to explore the adaptive potential of indigenous traditional knowledge (ITK)-based agricultural practices against climate change. The selected tribes are inhabitants of Eastern Himalaya (Apatani), Western Himalaya (Lahaulas), Eastern Ghat (Dongria-Gondh), and Western Ghat (Irular) representing rainforest, cold desert, moist upland, and rain shadow landscape, respectively. The effect of climate change over the respective regions was identified using different Intergovernmental Panel on Climate Change (IPCC) scenario, and agricultural practices resilient to climate change were quantified. Primary results indicated moderate to extreme susceptibility and preparedness of the tribes against climate change due to the exceptionally adaptive ITK-based agricultural practices. A brief policy has been prepared where knowledge exchange and technology transfer among the indigenous tribes have been suggested to achieve complete climate change resiliency.

Citation: Aich A, Dey D, Roy A (2022) Climate change resilient agricultural practices: A learning experience from indigenous communities over India. PLOS Sustain Transform 1(7): e0000022. https://doi.org/10.1371/journal.pstr.0000022

Editor: Ashwani Kumar, Dr. H.S. Gour Central University, INDIA

Copyright: © 2022 Aich et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

Traditional agricultural systems provide sustenance and livelihood to more than 1 billion people [ 1 – 3 ]. They often integrate soil, water, plant, and animal management at a landscape scale, creating mosaics of different land uses. These landscape mosaics, some of which have existed for hundreds of years, are maintained by local communities through practices based on traditional knowledge accumulated over generations [ 4 ]. Climate change threatens the livelihood of rural communities [ 5 ], often in combination with pressures coming from demographic change, insecure land tenure and resource rights, environmental degradation, market failures, inappropriate policies, and the erosion of local institutions [ 6 – 8 ]. Empowering local communities and combining farmers’ and external knowledge have been identified as some of the tools for meeting these challenges [ 9 ]. However, their experiences have received little attention in research and among policy makers [ 10 ].

Traditional agricultural landscapes as linked social–ecological systems (SESs), whose resilience is defined as consisting of 3 characteristics: the capacity to (i) absorb shocks and maintain function; (ii) self-organize; (iii) learn and adapt [ 11 ]. Resilience is not about an equilibrium of transformation and persistence. Instead, it explains how transformation and persistence work together, allowing living systems to assimilate disturbance, innovation, and change, while at the same time maintaining characteristic structures and processes [ 12 ]. Agriculture is one of the most sensitive systems influenced by changes in weather and climate patterns. In recent years, climate change impacts have been become the greatest threats to global food security [ 13 , 14 ]. Climate change results a decline in food production and consequently rising food prices [ 15 , 16 ]. Indigenous people are good observers of changes in weather and climate and acclimatize through several adaptive and mitigation strategies [ 17 , 18 ].

Traditional agroecosystems are receiving rising attention as sustainable alternatives to industrial farming [ 19 ]. They are getting increased considerations for biodiversity conservation and sustainable food production in changing climate [ 20 ]. Indigenous agriculture systems are diverse, adaptable, nature friendly, and productive [ 21 ]. Higher vegetation diversity in the form of crops and trees escalates the conversion of CO 2 to organic form and consequently reducing global warming [ 22 ]. Mixed cropping not only decreases the risk of crop failure, pest, and disease but also diversifies the food supply [ 23 ]. It is estimated that traditional multiple cropping systems provide 15% to 20% of the world’s food supply [ 1 ]. Agro-forestry, intercropping, crop rotation, cover cropping, traditional organic composting, and integrated crop-animal farming are prominent traditional agricultural practices [ 24 , 25 ].

Traditional agricultural landscapes refer to the landscapes with preserved traditional sustainable agricultural practices and conserved biodiversity [ 26 , 27 ]. They are appreciated for their aesthetic, natural, cultural, historical, and socioeconomic values [ 28 ]. Since the beginning of agriculture, peasants have been continually adjusting their agriculture practices with change in climatic conditions [ 29 ]. Indigenous farmers have a long history of climate change adaptation through making changes in agriculture practices [ 30 ]. Indigenous farmers use several techniques to reduce climate-driven crop failure such as use of drought-tolerant local varieties, polyculture, agro-forestry, water harvesting, and conserving soil [ 31 – 33 ]. Indigenous peasants use various natural indicators to forecast the weather patterns such as changes in the behavior of local flora and fauna [ 34 , 35 ].

The climate-smart agriculture (CSA) approach [ 36 ] has 3 objectives: (i) sustainably enhancing agricultural productivity to support equitable increase in income, food security, and development; (ii) increasing adaptive capacity and resilience to shocks at multiple levels, from farm to national; and (iii) reducing Green House Gases (GHG) emissions and increasing carbon sequestration where possible. Indigenous peoples, whose livelihood activities are most respectful of nature and the environment, suffer immediately, directly, and disproportionately from climate change and its consequences. Indigenous livelihood systems, which are closely linked to access to land and natural resources, are often vulnerable to environmental degradation and climate change, especially as many inhabit economically and politically marginal areas in fragile ecosystems in the countries likely to be worst affected by climate change [ 25 ]. The livelihood of many indigenous and local communities, in particular, will be adversely affected if climate and associated land-use change lead to losses in biodiversity. Indigenous peoples in Asia are particularly vulnerable to changing weather conditions resulting from climate change, including unprecedented strength of typhoons and cyclones and long droughts and prolonged floods [ 15 ]. Communities report worsening food and water insecurity, increases in water- and vector-borne diseases, pest invasion, destruction of traditional livelihoods of indigenous peoples, and cultural ethnocide or destruction of indigenous cultures that are linked with nature and agricultural cycles [ 37 ].

The Indian region is one of the world’s 8 centres of crop plant origin and diversity with 166 food/crop species and 320 wild relatives of crops have originated here (Dr R.S. Rana, personal communication). India has 700 recorded tribal groups with population of 104 million as per 2011 census [ 38 ] and many of them practicing diverse indigenous farming techniques to suit the needs of various respective ecoclimatic zones. The present study has been designed as a literature-based analytical review of such practices among 4 different ethnic groups in 4 different agroclimatic and geographical zones of India, viz, the Apatanis of Arunachal Pradesh, the Dongria Kondh of Niamgiri hills of Odisha, the Irular in the Nilgiris, and the Lahaulas of Himachal Pradesh to evaluating the following objectives: (i) exploring comparatively the various indigenous traditional knowledge (ITK)-based farming practices in the different agroclimatic regions; (ii) climate resiliency of those practices; and (iii) recommending policy guidelines.

2 Methodology

2.1 systematic review of literature.

An inventory of various publications in the last 30 years on the agro biodiversity, ethno botany, traditional knowledge, indigenous farming practices, and land use techniques of 4 different tribes of India in 4 different agroclimatic and geographical zones viz, the Apatanis of Arunachal Pradesh, the Dongria Kondh of Niamgiri hills of Odisha, the Irular in the Nilgiris, and the Lahaulas of Himachal Pradesh has been done based on key word topic searches in journal repositories like Google Scholar. A small but significant pool of led and pioneering works has been identified, category, or subtopics are developed most striking observations noted.

2.2 Understanding traditional practices and climate resiliency

The most striking traditional agricultural practices of the 4 major tribes were noted. A comparative analysis of different climate resilient traditional practices of the 4 types were made based on existing information available via literature survey. Effects of imminent dangers of possible extreme events and impact of climate change on these 4 tribes were estimated based on existing facts and figures. A heat map representing climate change resiliency of these indigenous tribes has been developed using R-programming language, and finally, a reshaping policy framework for technology transfers and knowledge sharing among the tribes for successfully helping them to achieve climate resiliency has been suggested.

2.3 Study area

Four different agroclimatic zones and 4 different indigenous groups were chosen for this particular study. The Apatanis live in the small plateau called Zero valley ( Fig 1 ) surrounded by forested mountains of Eastern Himalaya in the Lower Subansiri district of Arunachal Pradesh. It is located at 27.63° N, 93.83° E at an altitude ranging between 1,688 m to 2,438 m. Rainfall is heavy and can be up to 400 mm in monsoon months. Temperature varies from moderate in summer to very cold in the winter months. Their approximate population is around 12,806 (as per 2011 census), and Tibetan and Ahom sources indicate that they have been inhabiting the area from at least the 15th century and probably much earlier ( https://whc.unesco.org/en/tentativelists/5893/ ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

The base map is prepared using QGIS software.

https://doi.org/10.1371/journal.pstr.0000022.g001

The Lahaulas are the inhabitants of Lahaul valley ( Fig 1 ) that is located in the western Himalayan region of Lahaul and Spiti and lies between the Pir Panjal in the south and Zanskar in the north. It is located between 76° 46′ and 78° 41′ east longitudes and between 31° 44′ and 32° 59′ north altitudes. The Lahaul valley receives scanty rainfalls, almost nil in summer, and its only source of moisture is snow during the winter. Temperature is generally cold. The combined population of Lahaul and Spiti is 31,564 (as per 2011 census).

The Dongria Kondh is one of the officially designated primitive tribal group (PTG) in the Eastern Ghat region of the state Orissa. They are the original inhabitants of Niyamgiri hilly region ( Fig 1 ) that extends to Rayagada, Koraput, and Kalahandi districts of south Orissa. Dongria Kondhs have an estimated population of about 10,000 and are distributed in around 120 settlements, all at an altitude up to 1,500 above the sea level [ 39 ]. It is located between 190 26′ to 190 43′ N latitude and 830 18′ to 830 28′ E longitudes with a maximum elevation of 1,516 meters. The Niyamgiri hill range abounds with streams. More than 100 streams flows from the Niyamgiri hills and 36 streams originate from Niyamgiri plateau (just below the Niyam Raja), and most of the streams are perennial. Niyamgiri hills have been receiving high rainfall since centuries and drought is unheard of in this area.

The Irular tribes inhabit the Palamalai hills and Nilgiris of Western Ghats ( Fig 1 ). Their total population may be 200,000 (as per 2011 census). The Palamali Hills is situated in the Salem district of Tamil Nadu, lies between 11° 14.46′ and 12° 53.30′ north latitude and between 77° 32.52′ to 78° 35.05′ east longitude. It is located 1,839 m from the mean sea level (MSL) and more over the climate of the district is whole dry except north east monsoon seasons [ 40 , 41 ]. Nilgiri district is hilly, lying at an elevation of 1,000 to 2,600 m above MSL and divided between the Nilgiri plateau and the lower, smaller Wayanad plateau. The district lies at the juncture of the Western Ghats and the Eastern Ghats. Its latitudinal and longitudinal location is 130 km (latitude: 11° 12 N to 11° 37 N) by 185 km (longitude 76° 30 E to 76° 55 E). It has cooler and wetter climate with high average rainfall.

3 Results and discussion

3.1 indigenous agricultural practices in 4 different agro-biodiversity hotspots.

Previous literatures on the agricultural practices of indigenous people in 4 distinct agro-biodiversity hotspots did not necessarily focus on climate resilient agriculture. The authors of these studies had elaborately discussed about the agro-biodiversity, farming techniques, current scenario, and economical sustainability in past and present context of socioecological paradigm. However, no studies have been found to address direct climate change resiliency of traditional indigenous agricultural practices over Indian subcontinent to the best of our knowledge. The following section will primarily focus on the agricultural practices of indigenous tribes and how they can be applied on current eco-agricultural scenario in the milieu of climate change over different agricultural macroenvironments in the world.

3.1.1 Apatani tribes (Eastern Himalaya).

The Apatanis practice both wet and terrace cultivation and paddy cum fish culture with finger millet on the bund (small dam). Due to these special attributes of sustainable farming systems and people’s traditional ecological knowledge in sustaining ecosystems, the plateau is in the process of declaring as World Heritage centre [ 42 – 44 ]. The Apatanis have developed age-old valley rice cultivation has often been counted to be one of the advanced tribal communities in the northeastern region of India [ 45 ]. It has been known for its rich economy for decades and has good knowledge of land, forest, and water management [ 46 ]. The wet rice fields are irrigated through well-managed canal systems [ 47 ]. It is managed by diverting numerous streams originated in the forest into single canal and through canal each agriculture field is connected with bamboo or pinewood pipe.

The entire cultivation procedure by the Apatani tribes are organic and devoid of artificial soil supplements. The paddy-cum-fish agroecosystem are positioned strategically to receive all the run off nutrients from the hills and in addition to that, regular appliance of livestock manure, agricultural waste, kitchen waste, and rice chaff help to maintain soil fertility [ 48 ]. Irrigation, cultivation, and harvesting of paddy-cum-fish agricultural system require cooperation, experience, contingency plans, and discipline work schedule. Apatani tribes have organized tasks like construction and maintenance of irrigation, fencing, footpath along the field, weeding, field preparation, transplantation, harvesting, and storing. They are done by the different groups of farmers and supervised by community leaders (Gaon Burha/Panchayat body). Scientific and place-based irrigation solution using locally produced materials, innovative paddy-cum-fish aquaculture, community participation in collective farming, and maintaining agro-biodiversity through regular usage of indigenous landraces have potentially distinguished the Apatani tribes in the context of agro-biodiversity regime on mountainous landscape.

3.1.2 Lahaula (Western Himalaya).

The Lahaul tribe has maintained a considerable agro-biodiversity and livestock altogether characterizing high level of germ plasm conservation [ 49 ]. Lahaulas living in the cold desert region of Lahaul valley are facultative farmers as they able to cultivate only for 6 months (June to November) as the region remained ice covered during the other 6 months of the year. Despite of the extreme weather conditions, Lahaulas are able to maintain high level of agro-biodiversity through ice-water harvesting, combinatorial cultivation of traditional and cash crops, and mixed agriculture–livestock practices. Indigenous practices for efficient use of water resources in such cold arid environment with steep slopes are distinctive. Earthen channels (Nullah or Kuhi) for tapping melting snow water are used for irrigation. Channel length run anywhere from a few meters to more than 5 km. Ridges and furrows transverse to the slope retard water flow and soil loss [ 50 ]. Leaching of soil nutrients due to the heavy snow cover gradually turns the fertile soil into unproductive one [ 51 ]. The requirement of high quantity organic manure is met through composting livestock manure, night soil, kitchen waste, and forest leaf litter in a specially designed community composting room. On the advent of summer, compost materials are taken into the field for improving the soil quality.

Domesticated Yaks ( Bos grunniens ) is crossed with local cows to produce cold tolerant offspring of several intermediate species like Gari, Laru, Bree, and Gee for drought power and sources of protein. Nitrogen fixing trees like Seabuckthrone ( Hippophae rhamnoides ) are also cultivated along with the crops to meet the fuels and fodder requires for the long winter period. Crop rotation is a common practice among the Lahaulas. Domesticated wild crop, local variety, and cash crops are rotated to ensure the soil fertility and maintaining the agro-biodiversity. Herbs and indigenous medicinal plants are cultivated simultaneously with food crops and cash crop to maximize the farm output. A combinatorial agro-forestry and agro-livestock approach of the Lahaulas have successfully able to generate sufficient revenue and food to sustain 6 months of snow-covered winter in the lap of western Himalayan high-altitude landscape. This also helps to maintain the local agro-biodiversity of the immensely important ecoregion.

3.1.3 Dongria Kondh (Eastern Ghat).

Dongria Kondh tribes, living at the semiarid hilly range of Eastern Ghats, have been applying sustainable agro-forestry techniques and a unique mixed crop system for several centuries since their establishment in the tropical dry deciduous hilly forest ecoregion. The forest is a source for 18 different non-timber forest products like mushroom, bamboo, fruits, vegetables, seeds, leaf, grass, and medicinal products. The Kondh people sustainably uses the forest natural capital such a way that maintain the natural stock and simultaneously ensure the constant flow of products. Around 70% of the resources have been consumed by the tribes, whereas 30% of the resources are being sold to generate revenue for further economic and agro-forest sustainability [ 52 ]. The tribe faces moderate to acute food grain crisis during the post-sowing monsoon period and they completely rely upon different alternative food products from the forest. The system has been running flawlessly until recent time due to the aggressive mining activity, natural resources depleted significantly, and the food security have been compromised [ 53 ].

However, the Kondh farmer have developed a very interesting agrarian technique where they simultaneously grow 80 varieties of different crops ranging from paddy, millet, leaves, pulses, tubers, vegetables, sorghum, legumes, maize, oil-seeds, etc. [ 54 ]. In order to grow so many crops in 1 dongor (the traditional farm lands of Dongria Kondhs on lower hill slopes), the sowing period and harvesting period extends up to 5 months from April till the end of August and from October to February basing upon climatic suitability, respectively.

Genomic profiling of millets like finger millet, pearl millet, and sorghum suggest that they are climate-smart grain crops ideal for environments prone to drought and extreme heat [ 55 ]. Even the traditional upland paddy varieties they use are less water consuming, so are resilient to drought-like conditions, and are harvested between 60 and 90 days of sowing. As a result, the possibility of complete failure of a staple food crop like millets and upland paddy grown in a dongor is very low even in drought-like conditions [ 56 ].

The entire agricultural method is extremely organic in nature and devoid of any chemical pesticide, which reduces the cost of farming and at the same time help to maintain environmental sustainability [ 57 ].

3.1.4 Irular tribes (Western Ghat).

Irulas or Irular tribes, inhabiting at the Palamalai mountainous region of Western Ghats and also Nilgiri hills are practicing 3 crucial age-old traditional agricultural techniques, i.e., indigenous pest management, traditional seed and food storage methods, and age-old experiences and thumb rules on weather prediction. Similar to the Kondh tribes, Irular tribes also practice mixed agriculture. Due to the high humidity in the region, the tribes have developed and rigorously practices storage distinct methods for crops, vegetables, and seeds. Eleven different techniques for preserving seeds and crops by the Irular tribes are recorded till now. They store pepper seeds by sun drying for 2 to 3 days and then store in the gunny bags over the platform made of bamboo sticks to avoid termite attack. Paddy grains are stored with locally grown aromatic herbs ( Vitex negundo and Pongamia pinnata ) leaves in a small mud-house. Millets are buried under the soil (painted with cow dung slurry) and can be stored up to 1 year. Their storage structure specially designed to allow aeration protect insect and rodent infestation [ 58 ]. Traditional knowledge of cross-breeding and selection helps the Irular enhancing the genetic potential of the crops and maintaining indigenous lines of drought resistant, pest tolerant, disease resistant sorghum, millet, and ragi [ 59 , 60 ].

Irular tribes are also good observer of nature and pass the traditional knowledge of weather phenomenon linked with biological activity or atmospheric condition. Irular use the behavioral fluctuation of dragonfly, termites, ants, and sheep to predict the possibility of rainfall. Atmospheric phenomenon like ring around the moon, rainbow in the evening, and morning cloudiness are considered as positive indicator of rainfall, whereas dense fog is considered as negative indicator. The Irular tribes also possess and practice traditional knowledge on climate, weather, forecasting, and rainfall prediction [ 58 ]. The Irular tribes also gained extensive knowledge in pest management as 16 different plant-based pesticides have been documented that are all completely biological in nature. The mode of actions of these indigenous pesticides includes anti-repellent, anti-feedent, stomach poison, growth inhibitor, and contact poisoning. All of these pesticides are prepared from common Indian plants extract like neem, chili, tobacco, babul, etc.

The weather prediction thumb rules are not being validated with real measurement till now but understanding of the effect of forecasting in regional weather and climate pattern in agricultural practices along with biological pest control practices and seed conservation have made Irular tribe unique in the context of global agro-biodiversity conservation.

3.2 Climate change risk in indigenous agricultural landscape

The effect of climate change over the argo-ecological landscape of Lahaul valley indicates high temperature stress as increment of number of warm days, 0.16°C average temperature and 1.1 to 2.5°C maximum temperature are observed in last decades [ 61 , 62 ]. Decreasing trend of rainfall during monsoon and increasing trend of consecutive dry days in last several decades strongly suggest future water stress in the abovementioned region over western Himalaya. Studies on the western Himalayan region suggest presence of climate anomaly like retraction of glaciers, decreasing number of snowfall days, increasing incident of pest attack, and extreme events on western Himalayan region [ 63 – 65 ].

Apatani tribes in eastern Himalayan landscape are also experiencing warmer weather with 0.2°C increment in maximum and minimum temperature [ 66 ]. Although no significant trend in rainfall amount has been observed, however 11% decrease in rainy day and 5% to 15% decrease in rainfall amount by 2030 was speculated using regional climate model [ 67 ]. Increasing frequency of extreme weather events like flashfloods, cloudburst, landslide, etc. and pathogen attack in agricultural field will affect the sustainable agro-forest landscape of Apatani tribes. Similar to the Apatani and Lahaulas tribes, Irular and Dongria Kondh tribes are also facing climate change effect via increase in maximum and minimum temperature and decrease in rainfall and increasing possibility of extreme weather event [ 68 , 69 ]. In addition, the increasing number of forest fire events in the region is also an emerging problem due to the dryer climate [ 70 ].

Higher atmospheric and soil temperature in the crop growing season have direct impact on plant physiological processes and therefore has a declining effect on crop productivity, seedling mortality, and pollen viability [ 71 ]. Anomaly in precipitation amount and pattern also affect crop development by reducing plant growth [ 72 ]. Extreme events like drought and flood could alter soil fertility, reduce water holding capacity, increase nutrient run off, and negatively impact seed and crop production [ 73 ]. Agricultural pest attack increases at higher temperature as it elevates their food consumption capability and reproduction rate [ 74 ].

3.3 Climate resiliency through indigenous agro-forestry

Three major climate-resilient and environmentally friendly approaches in all 4 tribes can broadly classified as (i) organic farming; (ii) soil and water conservation and community farming; and (iii) maintain local agro-biodiversity. The practices under these 3 regimes have been listed in Table 1 .

https://doi.org/10.1371/journal.pstr.0000022.t001

Human and animal excreta, plant residue, ashes, decomposed straw, husk, and other by-products are used to make organic fertilizer and compost material that helps to maintain soil fertility in the extreme orographic landscape with high run-off. Community farming begins with division of labour and have produced different highly specialized skilled individual expert in different farming techniques. It needs to be remembered that studied tribes live in an area with complex topological feature and far from advance technological/logistical support. Farming in such region is extremely labour intensive, and therefore, community farming has become essential for surviving. All 4 tribes have maintained their indigenous land races of different crops, cereal, vegetables, millets, oil-seeds, etc. that give rises to very high agro-biodiversity in all 4 regions. For example, Apatanis cultivate 106 species of plants with 16 landraces of indigenous rice and 4 landraces of indigenous millet [ 75 ]. Similarly, 24 different crops, vegetables, and medicinal plants are cultivated by the Lahaulas, and 50 different indigenous landraces are cultivated by Irular and Dongria Kondh tribes.

The combination of organic firming and high indigenous agro-biodiversity create a perfect opportunity for biological control of pests. Therefore, other than Irular tribe, all 3 tribes depend upon natural predator like birds and spiders, feeding on the indigenous crop, for predation of pests. Irular tribes developed multiple organic pest management methods from extract of different common Indian plants. Apatani and Lahaulas incorporate fish and livestock into their agricultural practices, respectively, to create a circular approach to maximize the utilization of waste material produced. At a complex topographic high-altitude landscape where nutrient run-off is very high, the practices of growing plants with animals also help to maintain soil fertility. Four major stresses due to the advancement of climate change have been identified in previous section, and climate change resiliency against these stresses has been graphically presented in Fig 2 .

https://doi.org/10.1371/journal.pstr.0000022.g002

Retraction of the glaciers and direct physiological impact on the livestock due to the temperature stress have made the agricultural practices of the Lahaula’s vulnerable to climate change. However, Irular and Dongria Kondh tribes are resilient to the temperature stress due to their heat-resistant local agricultural landraces, and Apatanis will remain unaffected due to their temperate climate and vast forest cover. Dongria Kondh tribe will successfully tackle the water stress due to their low-water farming techniques and simultaneous cultivation of multiple crops that help to retain the soil moisture by reducing evaporation. Hundreds of perennial streams of Nyamgiri hills are also sustainably maintained and utilised by the Dongria Kondhs along with the forests, which gives them enough subsistence in form of non-timber forest products (NTFPs). However, although Apatani and Lahuala tribe extensively reuse and recirculate water in their field but due to the higher water requirement of paddy-cum-fish and paddy-cum-livestock agriculture, resiliency would be little less compared to Dongria Kondh.

Presence of vast forest cover, very well-structured irrigation system, contour agriculture and layered agricultural field have provided resiliency to the Apatani’s from extreme events like flash flood, landslides, and cloud burst. Due to their seed protection practices and weather prediction abilities, Irular tribe also show resiliency to the extreme events. However, forest fire and flash flood risk in both Eastern Ghat and Western Ghat have been increased and vegetation has significantly decreased in recent past. High risk of flash flood, land slide, avalanches, and very low vegetation coverage have made the Lahaulas extremely vulnerable to extreme events. Robust pest control methods of Irular tribe and age-old practices of intercropping, mixed cropping, and sequence cropping of the Dongria Kondh tribe will resist pest attack in near future.

3.4 Reshaping policy

Temperature stress, water stress, alien pest attack, and increasing risk of extreme events are pointed out as the major risks in the above described 4 indigenous tribes. However, every tribe has shown their own climate resiliency in their traditional agrarian practices, and therefore, a technology transfers and knowledge sharing among the tribes would successfully help to achieve the climate resilient closure. The policy outcome may be summarizing as follows:

• Designing, structuring and monitoring of infrastructural network of Apatani and Lahaul tribes (made by bamboo in case of Apatanis and Pine wood and stones in case of Lahaulas) for waster harvesting should be more rugged and durable to resilient against increasing risk of flash flood and cloud burst events.
• Water recycling techniques like bunds, ridges, and furrow used by Apatani and Lahaul tribes could be adopted by Irular and Dongria Kondh tribes as Nilgiri and Koraput region will face extreme water stress in coming decades.
• Simultaneous cultivation of multiple crops by the Dongria Kondh tribe could be acclimated by the other 3 tribes as this practice is not only drought resistance but also able to maximize the food security of the population.
• Germplasm storage and organic pest management knowledge by the Irular tribes could be transferred to the other 3 tribes to tackle the post-extreme event situations and alien pest attack, respectively.
• Overall, it is strongly recommended that the indigenous knowledge of agricultural practices needs to be conserved. Government and educational institutions need to focus on harvesting the traditional knowledge by the indigenous community.

3.5 Limitation

One of the major limitations of the study is lack of significant number of quantifiable literature/research articles about indigenous agricultural practices over Indian subcontinent. No direct study assessing risk of climate change among the targeted agroecological landscapes has been found to the best of our knowledge. Therefore, the current study integrates socioeconomic status of indigenous agrarian sustainability and probable climate change risk in the present milieu of climate emergency of 21st century. Uncertainty in the current climate models and the spatiotemporal resolution of its output is also a minor limitation as the study theoretically correlate and proposed reshaped policy by using the current and future modeled agro-meteorological parameters.

4. Conclusions

In the present study, an in-depth analysis of CSA practices among the 4 indigenous tribes spanning across different agro-biodiversity hotspots over India was done, and it was observed that every indigenous community is more or less resilient to the adverse effect of climate change on agriculture. Thousands years of traditional knowledge has helped to develop a unique resistance against climate change among the tribes. However, the practices are not well explored through the eyes of modern scientific perspective, and therefore, might goes extinct through the course of time. A country-wide study on the existing indigenous CSA practices is extremely important to produce a database and implementation framework that will successfully help to resist the climate change effect on agrarian economy of tropical countries. Perhaps the most relevant aspect of the study is the realization that economically and socially backward farmers cope with and even prepare for climate change by minimizing crop failure through increased use of drought tolerant local varieties, water harvesting, mixed cropping, agro-forestry, soil conservation practices, and a series of other traditional techniques.

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• Published: 16 February 2022

A global dataset for the projected impacts of climate change on four major crops

• Toshihiro Hasegawa   ORCID: orcid.org/0000-0001-8501-5612 1 ,
• Hitomi Wakatsuki   ORCID: orcid.org/0000-0002-9861-5921 1 ,
• Shalika Vyas   ORCID: orcid.org/0000-0002-9933-1269 3 ,
• Gerald C. Nelson   ORCID: orcid.org/0000-0003-3626-1221 4 ,
• Aidan Farrell 5 ,
• Delphine Deryng   ORCID: orcid.org/0000-0001-6214-7241 6 ,
• Francisco Meza 7 &
• David Makowski   ORCID: orcid.org/0000-0001-6385-3703 8  

Scientific Data volume  9 , Article number:  58 ( 2022 ) Cite this article

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• Environmental impact

Reliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate change impact assessments. However, the wealth of data produced by these studies has not been made publicly available. Here, we develop a global dataset by consolidating previously published meta-analyses and data collected through a new literature search covering recent crop simulations. The new global dataset builds on 8703 simulations from 202 studies published between 1984 and 2020. It contains projected yields of four major crops (maize, rice, soybean, and wheat) in 91 countries under major emission scenarios for the 21st century, with and without adaptation measures, along with geographical coordinates, current temperature and precipitation levels, projected temperature and precipitation changes. This dataset provides a solid basis for a quantitative assessment of the impacts of climate change on crop production and will facilitate the rapidly developing data-driven machine learning applications.

Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.17427674

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Background & summary.

Climate change affects many processes of food systems directly and indirectly 1 , but the primary effects often appear in crop production. Projections of crop production under future climate change have been studied since the early 1980s. From the 1990s onward, researchers have used future climate data and crop simulation models to project the impacts of climate change on crop yields under various scenarios 2 . Since then, crop simulation models have been used in hundreds of studies to simulate yields for different crops under a range of climate scenarios and growing conditions 3 . The results have been periodically reviewed and assessed by national and international organisations, in particular by the Intergovernmental Panel on Climate Change (IPCC) Working Group II, which provides policy-relevant scientific evidence for the impacts of and adaptation to climate change 3 . Review studies covering the last five IPCC assessment cycles confirm that the overall effects are negative but vary significantly among regions 4 , 5 .

Before 2010, simulation studies were conducted mainly by individual research groups using different climate models, target years, spatial resolution with local management and cultivar conditions. Since 2010, however, significant efforts have been made to coordinate modelling studies through Agricultural Model Intercomparison and Improvement Project (AgMIP) 6 , which compares results from multiple crop models using standardised inputs. Early AgMIP activities have disentangled sources of uncertainties in crop yield projections and revealed that yield projections are variable among crop models and that model ensemble mean or median often works better than a single model 7 , 8 , 9 , 10 , underpinning the importance of datasets based on multiple crop models.

Data sets including crop model simulations produced by AgMIP were subjected to statistical analysis and the results were used to quantify the impacts of climate change on major crops 11 , 12 . A versatile tool to aggregate simulated results is already available for global gridded studies 13 to facilitate access to the data. Besides these coordinated efforts, however, many simulation results are scattered and not readily available for meta-analysis. To deliver policy-relevant quantitative information, we need to develop a shared and well-documented database that can be used to assess the impacts of different climate and adaptation scenarios on crop yields.

Here, we have developed a global database for potential use for the IPCC Working Group II assessment, obtained through two methods. The first method draws on the dataset used in the meta-analysis of Aggarwal, et al . 5 , which includes studies considered in the previous five cycles of IPCC assessments 4 , 14 . The second method is based on a new literature search of studies published during the sixth IPCC assessment cycle (covering the period 2014–2020) reporting crop simulations produced for several contrasting climate change scenarios. The combined dataset covers all six cycles of the IPCC assessment and can serve as a solid basis for analyses from the sixth IPCC assessment onward.

The dataset contains the most relevant variables for evaluating climate change impacts on yields of maize, rice, soybean, and rice for the 21st century. They include geographical coordinates, crop species, CO 2 emission scenarios, CO 2 concentrations, current temperature and precipitation levels, local and global warming degrees, projected changes in precipitation, the relative changes in yield as a percentage of the baseline period obtained with or without CO 2 effects, and with or without implementation of different types of adaptation options.

Data collection

As shown in a PRISMA diagram (Fig.  1 ), we obtained data through two methods to develop this dataset. The first method is based on the previous meta-analysis by Aggarwal et al . 5 , which includes studies published before 2016 (Aggarwal-DS, hereafter). This meta-analysis builds on the dataset used for the 5 th IPCC assessment report 4 , 14 and an additional search through three types of databases: Scientific database (Scopus, Web of Science, CAB Direct, JSTOR, Agricola etc), journals and open access repositories, and institutional Websites (FAO database, AgMIP Database, World Bank, etc.) and Google Scholar. See Aggarwal et al . 5 for details. Briefly, the search terms used by Aggarwal et al . 5 include “agriculture” or “crop “or “farm” or “crop yield” or “crop yields” or “farm yields” or “crop productivity” or “agricultural productivity” or “maize” or “rice” or “wheat” and “climate change assessment” or “climate impacts” or “impact assessments” or “climate change impact” or “climate impact” or “effect of climate” or “impact of climate change”. The number of selected papers covering the four major crops is 166. We further screened them according to the availability of local temperature rise and geographical information, and traceability, resulting in 99 studies published between 1984 and 2016.

A diagram depicting paper collection and selection using the two search strategies. N is the number of studies.

The second method relies on a new recent literature review conducted using Scopus in March 2020 for four major crops (maize, rice, soybean, and wheat) for peer-review papers published from 2014 onward in line with the sixth assessment cycle of IPCC. In this method, we used several combinations of terms to retrieve relevant studies reporting simulations of the impacts of climate change on crop yields using recent climate change scenarios.

For maize, the following search equation was used: PUBYEAR > 2013 AND TITLE-ABS-KEY((maize OR corn) AND ((“greenhouse gas” OR “global warming” OR “climate change” OR “climate variability” OR “climate warming”)) AND NOT (emissions OR mitigation OR REDD OR MRV)).

Similar search equations were used for the other crops. Collectively, this search returned a total of 4703 references between 2014 and 2020: 1899 for maize, 1790 for wheat, 757 for rice, and 257 for soybean with some duplications because some papers studied multiple crops. Removing the duplicates, the number is down to 3816 studies.

To collect climate-scenario-based simulations, we then selected a subset of studies including the following terms related to climate scenarios in titles, abstracts, or authors’ keywords; “RCP”, “RCP2.6”, “RCP6.0”, “RCP4.5”, “RCP8.5”, “CMIP5”, and “CMIP6”. RCP stands for the Representative Concentration Pathways 15 , and each RCP corresponds to a greenhouse gas concentration trajectory describing different future greenhouse gas emission levels. The number followed by RCP is the level of radiative forcing (Wm −2 ) reached at the end of the 21 st century, which increases with the volume of greenhouse gas emitted to the atmosphere 16 . CMIP5 17 and CMIP6 18 are the Coupled Model Intercomparison Project Phase 5 and Phase 6, respectively, where groups of different earth system models (ESMs) provide global-scale climate projections based on different RCPs. Additionally, “process-based model” was used to search in the authors’ keywords to select for studies that use crop simulation models under CMIP5 or CMIP6 climate scenarios. As of March 2020, no results were found for CMIP6 in any search results.

This screening process resulted in a total of 207 references all together for four major crops. These studies were further evaluated for their variables and data availability; studies not reporting yield data were excluded. Projected yields with and without adaptations and yields of the baseline period were extracted, along with geographical coordinates, crop species, greenhouse gas emission scenarios, and adaptation options. We also tried to obtain local and global temperature changes and CO 2 concentrations as much as possible. In addition to extracting data from the literature, we contacted several authors of grid simulation studies to provide aggregated results for countries or regions. The authors of the three grid simulation studies responded and provided baseline and projected yields, annual temperature and precipitation data aggregated over for countries or regions 19 , 20 , 21 . The results from different ESMs were then averaged.

We removed duplicates between the datasets produced by the two methods and ultimatelly obtained a total of 202 unique studies. Both datasets include studies with different spatial scales: site-based, regional, and global. Among these, the results from the global gridded crop models were aggregated to country levels, and we focused on top-producing countries, which account for 95% of the world’s production of each commodity as of 2010 (FAOSTAT, http://www.fao.org/faostat/en/ , accessed on September 4, 2020). As a result, the dataset contains 8,703 sets of yield projections during the 21 st century from studies published between 1984 and 2020 (Online-only Table  1 ).

Relative yield impacts

Simulated grain mass per unit land area is used to derive the impact of climate change on yield (YI), which is defined as:

Where Y f is the future yield, and Y b is the baseline yield. One study 20 simulated yields separately under both climate change and counterfactual non-climate change scenarios from the pre-industrial era toward the end of the 21 st century, also accounting for yield increases due to non-climatic technological factors over time. In this case, YI obtained with the above equation under the climate change scenario was not fully relevant because it combines effects of both climate change and technological factors. Thus, for this study, YI was derived from the average yield in the 2001–2010 period under climate change and the average yield in the same period assuming no climate change, as follows:

Where Y f_cc and Y b_cc are the future and baseline average yields with climate change, Y f_ncc and Y b_ncc are the future and baseline average yields under counterfactual no climate change scenario.

Projected absolute grain yield (t/ha) is also included in the dataset, when available. These values should be used with caution because absolute grains yields are not always comparable due to the use of different yield definitions or assumptions. Different definitions include graded or non-graded yields, husked or unhusked, milled or non-milled yield. Moisture content correction factors can also be different, but these are not often explicitly indicated in the literature. Contrary to absolute yields, relative yields are unitless and rule out differences of yield defintions between studies.

Adaptation to climate changes

Various management or cultivar options are tested in the simulations. If the authors of the article consider these options as ways to adapt crops to climate change, we treat them as adaptation options, which are categorised into fertiliser, irrigation, cultivar, soil organic matter management, planting time, tillage, and others. Specifically, in the fertiliser option, if the amount and timing of fertiliser application are changed from the current conventional method, we treat them as adaptation. In the irrigation option, if the simulation program determines the irrigation scheduling based on the crop growth, climatic and soil moisture conditions, we treat this as adaptation because the management is adjusted to future climatic conditions. If rainfed and irrigated conditions are simulated separately, we do not consider irrigation as an adaptation. We define cultivar option as the use of cultivars of different maturity groups and/or higher heat tolerance than conventional cultivars. The planting time option corresponds to a shift of planting time from conventional timing. If multiple planting times are tested, we select the one that gives the best yield. The soil organic matter management option corresponds to application of compost and/or crop residue. The tillage option corresponds to reduced- or no-till cultivation compared to no conventional tillage. When studies consider adaptation options, we compute YI from the ratio of yield with adaptation under climate change to baseline yield without adaptation. To measure our capacity to adapt to climate change, we calculated adaptation potential - defined as the difference between yield impacts with and without adaptation - when a pair of yield values were available in the same study.

Temperature and precipitation changes

Both local temperature rise (ΔT l ) and global mean temperature rise (ΔT g ) from the baseline period have important implications. The former directly affects crop growth and yield, and the latter represents a global target associated with mitigation activities. We extracted both ΔT l and ΔT g from the literature as much as possible, but ΔT g is not available in many studies. In such cases, we estimated ΔT g using the Warming Attribution Calculator ( http://wlcalc.climateanalytics.org/choices ). In the dataset, we provide two estimates for ΔT g : one from the current baseline period (2001–2010) and the other from the preindustrial era (1850–1900). We also extracted precipitation changes (ΔPr) and baseline precipitation data reported in the selected studies. When only relative changes were available for precipitation data, we estimated ΔPr using the reported relative change and current precipitation levels described in the next section.

Current temperature and precipitation levels

Current annual mean temperatures and precipitation were obtained from the W5E5 dataset 22 , which was compiled to support the bias adjustment of climate input data for the impact assessments performed in Phase 3b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b, https://www.isimip.org/protocol/3/ ). The W5E5 dataset includes half-degree grid resolution daily mean temperature and precipitation data from 1979 to 2016, which we averaged for the period from 2001 and 2010. They were then extracted for each simulation site or region using the geographic information. For global simulations, which were aggregated to the country level, central coordinates were used to link gridded temperature and precipitation data with each country. As centroids may not represent the centre of the growing regions, particularly in large countries, growing-area weighted averages of annual temperature and precipitation were also provided using MIRCA 2000 23 , which contains half-degree grid harvested areas (a total of irrigated and rainfed) around the year 2000.

CO 2 concentrations

Several studies report two series of yield simulations obtained using two CO 2 levels to infer the CO 2 fertilization effects: one obtained with CO 2 concentrations fixed at the current levels and the other obtained with increased future CO 2 concentrations provided by the emission scenario considered. In the dataset, we make this explicit in the following two variables:

CO 2 : Binary variable equal to “Yes” if future CO 2 concentrations from the emission scenarios were used and “No” if the current CO 2 concentration was used for the yield simulations.

CO 2 ppm: if available, CO 2 concentration was extracted from the original paper. If not, we calculated it from projected changes in CO 2 concentrations based on the scenarios and periods studied. CO 2 concentration data were obtained from https://www.ipcc-data.org/observ/ddc_co2.html for CMIP3 and Meinshausen, et al . 16 ( http://www.pik-potsdam.de/~mmalte/rcps/ ) for CMIP5.

Baseline correction

Because baseline periods differed between studies, we corrected YI, ΔT l , ΔT g, ΔPr to the 2001–2010 baseline period by a linear interpolation method following Aggarwal et al . 5 . Namely, the impacts YI were first divided by the year gap between the future period midpoint year and the baseline period midpoint year of the original study. The impact per year was then multiplied by the year gap from our reference baseline period midpoint year (2005). The same method was applied to express ΔT l and ΔPr relatively to 2001–2010.

We made all data publicly available to increase accessibility (see Data Records section for access).

Data Records

All the data and R scripsts associated with the dataset are stored in the figshare repository 24 , where the following files are uploaded:

“Projected_impacts_datasheet_11.24.2021.xlsx” includes three worksheets. “Projected_impacts” worksheet contains the final dataset after screening, and “Adaptation_potential” is the extracted subset of the paired data comparing yield impacts with and without adaptation. “Excluded” has untraceable simulation results in the Aggarwal-DS.

“Meta-data_11.25.2021.xlsx” contains the summary of the dataset, such as the definition and unit of the variables used in “Projected_impacts_datatasheet.xlsx”.

“Online_only_summary_tables_11.18.2021.xlsx” contains data distribution, median, and mean impacts of climate change, presented in the online-only tables.

“Supplementary_materials_11.29.2021.pdf” contains methods for estimating local temperature rise and summary distribution of climate change impacts on four crop yields.

“Reference_11.24.2021.docx” provides a list of references that provided data.

“R_script_for_Hasegawa_et.al.11.26.2021.zip” contains R scripts used to estimate missing values of ΔT l ,ΔT l and ΔPr and draw Figs.  2 – 6 .

Data availability of crop yield simulations and its breakdown. (a) By global temperature rise from the preindustrial era and climate scenarios, (b) By projected time periods (midpoint years) and climate scenarios, (c) IPCC regions 29 and crop species, and (d) adaptation options and crop species. Note that n = 9812 in adaptation options (d) exceeds the total number of simulations (8703) because we collectively add all the options used in the simulations, including those that use multiple options. n is the number of simulation results.

Distribution of relative yield change due to climate change from the baseline period (2001–2010) with and without adaptation.

Climate change impacts (% of yield change from the baseline period) on four crops without adaptation under RCP8.5. ( a ) Mid-century; ( b ) End-Century. Maps with bluish symbols show positive effects (yield gain); Maps with reddish symbols show negative effects (yield loss). Projections under RCP2.6 and RCP4.5 are given in Supplementary Fig.  S3 .

Projected yield changes relative to the baseline period (2001–2010). (a) Mid-century (MC) projections without adaptation under RCP8.5 scenario, upper panels showing positive impacts and lower panels negative impacts, (b) End-century (EC) projections under three RCP scenarios by current annual temperature (T ave ), and (c) Yield change as a function of global temperature rise from the pre-industrial period by three T ave levels. The box is the interquartile range (IQR) and the middle line in the box represents the median. The upper- and lower-end of whiskers are median 1.5 × IQR ± median. Open circles are values outside the 1.5 × IQR.

Adaptation potential, defined as the difference between yield impacts with and without adaptation in projected yield impacts, for three RCPs by mid- and end-century (MC, EC). The box is the interquartile range (IQR) and the middle line in the box represents the median. The upper- and lower-end of whiskers are median 1.5 × IQR ± median. Open circles are values outside the 1.5 × IQR. (a) By adaptation options and (b) by IPCC regions.

Coverage of the data

A total of 8703 yield simulations are registered in the consolidated dataset. The number of simulations grows exponentially with publication year: 20 in the 1980s, 304 in 1990s, 830 in 2000s and 7549 in 2010s (Online-only Table  1 ). About 80% of the simulations use CMIP5 climate scenarios, and 11% use CMIP3. From CMIP5, RCP2.6, RCP4.5 and RCP8.5 are the most used concentration pathways (Online-only Table  2 , Fig.  2a ). ΔT g from the baseline period (2001–2010) ranges from 0 to 4.8 °C (0.8 to 5.6 °C from the preindustrial period). Almost all simulations with ΔT g  > 3 °C use RCP8.5, resulting in a greater ΔTg range under CMIP5 (RCPs) than under previous scenarios (SRES and others).

Projected time periods span widely in the 21 st century, but the midpoint years peak at 2020 for the near future, 2050 for mid-century, and 2080 for end-century (Fig.  2b ). Major emission scenarios such as RCP2.6, 4.5 and 8.5 are almost equally distributed across time periods. About 5% of the simulations assume no CO 2 fertilisation effects.

Relative frequency of the regions studied generally reflects harvested areas of the four crops in each region (Fig.  2c ). About 41% of the simulations were performed in Asia, which accounts for about 47% of the harvested area of the four major crops (mean of 2017–2019, FAOSTAT, http://www.fao.org/faostat/en/ , accessed on April 28, 2021). Europe is slightly overstudied (22%) for its world share of the harvested areas (12%). Central and South Americas is slightly under-researched (9%) for the regional share of harvested areas (15%), whereas Africa’s share (15%) is comparable to the area harvested (10%). Altogether global harvested areas for these four major crops is 7 × 10 8 ha: wheat represents 31% of this area, followed by maize (28%), rice (23%) and soybean (18%). Maize studies are over represented, accounting for about half of the simulations (52%), followed by wheat (26%) and rice (17%); soybean accounts only for 3% of the simulations (Fig.  2c ). Regionally, maize and wheat are harvested across almost all regions, and simulations follow the actual distribution of these crops. Rice is predominantly studied in Asia, reflecting actual distribution (85% of the harvested area is in Asia). Soybean remains understudied compared to the other three crops despite its large cultivated area (about 75% of the rice harvested area). Regionally, simulation sites or regions for soybean are mostly in the Americas, which account for 76% of the total soybean harvested area.

About 39% of the simulations (3376) use current management practices, and the rest (5327) consider different management or cultivars as adaptation options (Fig.  1d ). More than half of the simulations are run with multiple options. Among these options, fertiliser accounts for 32% followed by irrigation (29%), cultivar and planting date (17% each). There are 2005 pairs of yield simulations available for comparing results obtained with and without adaptation. These pairs of yield data can be used to compute the adaptation potentials of the different options considered.

Technical Validation

Data quality check.

We repeatedly checked the data with multiple authors for the new dataset. For the Aggarwal-DS, we reviewed the sources of references. In case of missing information such as climate scenarios, CO 2 concentration, or temperature increase, we came back to the original reference. Inconsistencies between the dataset and original papers were corrected when possible. Overall, corrections were made on 333 simulations from 10 studies, which we flag with “*” in the remark column of the dataset. We removed all data of the Aggarwal-DS that were untraceable in the original paper. This quality control excluded 47 simulations from 9 articles listed in the “Excluded” sheet.

We first examined the distribution of the climate change impacts on crop yields, which span from −100 to 136% (Fig.  3 ). This distribution is skewed to the left, as indicated by the negative skewness. The large kurtosis shows that distribution tails are longer than than those of the normal distribution. We tested the effects of potential outliers outside the 1.5-fold interquartile range (IQR) on the summary statistics of the climate change impacts on crop yields 25 . Removing values outside the 1.5-fold IQR decreases the number of simulations by 907(10.4%) and the negative effects of climate change on crop yields by 3.0% for the mean and 0.6% for the median, suggesting that the deletion affected the original distribution. We, therefore, keep all the simulation results in the dataset.

Methods to estimate local temperature and precipitation changes

Out of 8703 simulations, local temperature change (ΔT l ) and global temperature range (ΔT g ) were available in 4316 and 8109 simulations, respectively. To estimate ΔT l for 3793 simulations with missing ΔT l , we examined the relationship between ΔT l and the following six input variables in 4316 simulations where ΔT l was available: ΔT g , average temperature (area weighted), latitudes, longitudes, time periods, and emission scenarios. Values of ΔT l were estimated using random forest algorithms trained to establish a function relating local temperature rise to the six inputs considered. We tested and compared four models based on different combinations of the input variables. Among the four models, a reduced model with three variables (ΔT g , latitude, and longitude) showed the highest percentage of explained variance (97.1%), and led to a cross-validated RMSE as low as 0.18 °C (Supplementary Table  S1 and Fig.  S1 ). We, therefore, used the reduced model to impute ΔT l for the 4430 missing data. We also estimated ΔT g for 504 simulations with missing ΔT l from ΔT g , average temperature (area weighted), latitude, longitude, climate scenarios, future-midpoint year (Supplementary Table  S2 and Fig.  S2 ).

Likewise, we applied a random forest model to estimate ΔPr from current annual precipitation and average temperature (area weighted), latitude, longitude, local temperature change from 2005), climate scenario, future mid-point year, and climate change impact on yield relatively to 2005. Among eight models tested, a one with ΔT g , ΔT l , latitude, longitude, RCP, future-mid-point year and current annual precipitation perfomed best, which accounted for 96.9% of the out-of-bag variation of the data (n = 3560) and led to a cross-validated RMSE was 18 mm (Supplementary Table  S3 ). We then applied this model to estimate all missing ΔPr.

Comparison with previous studies

The overall effects of climate change on crop yields are negative, with the mean and median of −11% and −6.2% without adaptation and −4.6% and −1.6% with adaptation, respectively (Online-only Tables  3 and 4 ). The median per-decade yield impact without adaptation is −2.1% for maize, −1.2% for soybean, −0.7% for rice, and −1.2% for wheat (Table  1 ), which are consistent with previous IPCC assessments 14 . The median per-warming-degree impact is −7.1% for maize, −4.0% for soybean, −2.3% for rice, and −3.7% for wheat (Table  1 ). Per-degree yield impacts for each crop are generally within the range reported in the previous meta-analysis 11 . Among the four crops, soybean has the least number of simulations, resulting in a greater variation in both per-decade and per-degree impacts. Maize consistently shows the largest negative impacts, while rice shows the least.

The climate change impacts by IPCC regional groups reveals that Europe and North America are expected to be less affected by climate change in the mid-century (MC) and the end-century (EC) than Africa, Central and South America, particularly for maize and soybean. Both positive and negative effects are mixed in all regions (Fig.  4 , Supplementary Figs.  S3 , S4 ).

Regional differences in the impacts in MC and EC are associated with the current temperature level. In MC, positive or neutral effects are projected when current annual average temperatures (T ave ) are below 10–15 °C, but the effects become negative as T ave increases beyond these levels regardless of RCPs (Fig.  5a ). This accounts for the regional differences as a function of latitude reported in previous meta-analyses 4 , 5 . In EC, the threshold T ave shifts lower, and the negative effects become more severe, particularly under a high emission scenario (RCP8.5) (Fig.  5b ). The effect of ΔT g from the baseline period onYI differs depending on the T ave (Fig.  5c ); At T ave  < 10 °C, YI is generally neutral even where ΔT g  > 2 °C in most crops, but at T ave  > 20 °C, YI is negative even with small ΔT g, notably in maize. The difference in the YI dependence on ΔT g between regions is also consistent with the previous study 4 .

Adaptation potential averaged 7.3% in MC and 11.6% in EC (Fig.  6 , Supplementary Fig.  S5 ), which is not sufficient to offset the negative impacts, particularly in currently warmer regions. Residual damages will thus likely remain even with adaptation, which is also supported by other lines of evidence 26 , 27 .

Usage Notes

Crop yield simulation studies can provide a narrative of when, where, and what will happen to crop production under different GHG emissions and climate scenarios. They are also expected to provide quantitative information on the potential and limits to adaptation. However, robust estimates covering different temporal and spatial scales need to draw on multiple results obtained from various simulation studies. Nearly four decades have passed since the model projections based on future climate scenarios started. This dataset covers the entire period of simulation studies using climate scenarios, which can help update the quantitative review of climate change impacts on crops. The full list of references is provided in the reference file ( https://doi.org/10.6084/m9.figshare.14691579.v4 ).

Currently, studies are heavily biased towards major cereals such as maize, rice, and wheat, but this can be expanded to include other crops. As of 2020, our literature search failed to find published reports using CMIP6 climate scenarios, but this dataset can be easily updated when new simulations using new climate scenarios or other crop species become available. The next IPCC assessment cycle can fully utilise this dataset by adding the latest simulation results.

One of the caveats to the current dataset is that it only includes crop yield data, notwithstanding crop simulation studies are expected to produce other results than yield. Because of the recent progress in crop modelling, grain quality projections are emerging 28 . We have extensively included the temperature and precipitation levels to account for the impacts concerning the warming and current temperature, but there is a need to include other key climatic variables such as soil moisture. It will be useful to expand our dataset in the future to include this type of data.

Code availability

Script files were created using the R statistical programming to estimate missing values of ΔT l , ΔT l and ΔPr and draw Figs.  2 – 6 which are available in the figshare repository 24 .

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Acknowledgements

This study was performed by the Environment Research and Technology Development Fund (JPMEERF20S11820) of the Environmental Restoration and Conservation Agency of Japan. TH and DM would like to thank Joint-Linkage-Call between INRAE and NARO for supporting this collaborative study and the CLAND Institute of convergence (ANR 16-CONV-0003). We also thank Dr. T. Iizumi and Y. Ishigooka for providing the aggregated simulation results.

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Toshihiro Hasegawa and Hitomi Wakatsuki designed the dataset. Hitomi Wakatsuki and Hui Ju collected simulation results from the SCOPUS search. Shalika Vyas designed and collected the Aggarwal dataset. Gerald C. Nelson conducted literature search and provided global temperature dataset. David Makowski and Hitomi Wakatsuki developed a statistical imputation for missing data on the local temperature rise and precipitation change. All authors worked on data analysis and drafting the final version of the manuscript.

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Hasegawa, T., Wakatsuki, H., Ju, H. et al. A global dataset for the projected impacts of climate change on four major crops. Sci Data 9 , 58 (2022). https://doi.org/10.1038/s41597-022-01150-7

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Impact of Climate Change on Agriculture: Evidence and Predictions

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The impacts of climate change on agriculture are both positive and negative. The effects of climate change on agriculture and food security are also direct and indirect in nature. It impacted soil carbon losses, freshwater availability, crop yield, livestock production, fish migration, spawning, etc. directly. And, at the same time, it causes frequent floods, drought, salinity, heat stress, and an unprecedented tropical cyclone that threatens food security and biodiversity. Evidence of positive and negative effects of climate change on agriculture are clear cut. Moreover, the predicted climate change consequences are also going to adversely affect agriculture and food security in the near future. Specifically, the productivity of major field crops like rice, wheat, maize, soybean as well as millet and sorghum would be affected. The impacts on fruits and vegetables are widely varied and primarily depend on latitude and region of cultivation. The CO 2 fertilization effect is positive for most of the C3 crops but up to a certain temperature rise. In the livestock sector, pastoral system productivity is going to be reduced along with lower animal growth rates and productivity, higher pests and disease incidence, and loss of biodiversity. This sector is also likely to be adversely affected differently in different regions by rising temperatures, water scarcity, and low-quality feed supply, and the spreading of unexpected diseases. The vulnerability of rangeland (both productivity and composition) and pastoral systems to climate change is reasonably high. Moreover, the pests and diseases outbreak with altered vectors for both crop and livestock are going to take different dimensions in future climate change scenarios.

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Bhattacharyya, P., Pathak, H., Pal, S. (2020). Impact of Climate Change on Agriculture: Evidence and Predictions. In: Climate Smart Agriculture. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-9132-7_2

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Climate change is a long-lasting change in the weather arrays across tropics to polls. It is a global threat that has embarked on to put stress on various sectors. This study is aimed to conceptually engineer how climate variability is deteriorating the sustainability of diverse sectors worldwide. Specifically, the agricultural sector’s vulnerability is a globally concerning scenario, as sufficient production and food supplies are threatened due to irreversible weather fluctuations. In turn, it is challenging the global feeding patterns, particularly in countries with agriculture as an integral part of their economy and total productivity. Climate change has also put the integrity and survival of many species at stake due to shifts in optimum temperature ranges, thereby accelerating biodiversity loss by progressively changing the ecosystem structures. Climate variations increase the likelihood of particular food and waterborne and vector-borne diseases, and a recent example is a coronavirus pandemic. Climate change also accelerates the enigma of antimicrobial resistance, another threat to human health due to the increasing incidence of resistant pathogenic infections. Besides, the global tourism industry is devastated as climate change impacts unfavorable tourism spots. The methodology investigates hypothetical scenarios of climate variability and attempts to describe the quality of evidence to facilitate readers’ careful, critical engagement. Secondary data is used to identify sustainability issues such as environmental, social, and economic viability. To better understand the problem, gathered the information in this report from various media outlets, research agencies, policy papers, newspapers, and other sources. This review is a sectorial assessment of climate change mitigation and adaptation approaches worldwide in the aforementioned sectors and the associated economic costs. According to the findings, government involvement is necessary for the country’s long-term development through strict accountability of resources and regulations implemented in the past to generate cutting-edge climate policy. Therefore, mitigating the impacts of climate change must be of the utmost importance, and hence, this global threat requires global commitment to address its dreadful implications to ensure global sustenance.

Introduction

Worldwide observed and anticipated climatic changes for the twenty-first century and global warming are significant global changes that have been encountered during the past 65 years. Climate change (CC) is an inter-governmental complex challenge globally with its influence over various components of the ecological, environmental, socio-political, and socio-economic disciplines (Adger et al.  2005 ; Leal Filho et al.  2021 ; Feliciano et al.  2022 ). Climate change involves heightened temperatures across numerous worlds (Battisti and Naylor  2009 ; Schuurmans  2021 ; Weisheimer and Palmer  2005 ; Yadav et al.  2015 ). With the onset of the industrial revolution, the problem of earth climate was amplified manifold (Leppänen et al.  2014 ). It is reported that the immediate attention and due steps might increase the probability of overcoming its devastating impacts. It is not plausible to interpret the exact consequences of climate change (CC) on a sectoral basis (Izaguirre et al.  2021 ; Jurgilevich et al.  2017 ), which is evident by the emerging level of recognition plus the inclusion of climatic uncertainties at both local and national level of policymaking (Ayers et al.  2014 ).

Climate change is characterized based on the comprehensive long-haul temperature and precipitation trends and other components such as pressure and humidity level in the surrounding environment. Besides, the irregular weather patterns, retreating of global ice sheets, and the corresponding elevated sea level rise are among the most renowned international and domestic effects of climate change (Lipczynska-Kochany  2018 ; Michel et al.  2021 ; Murshed and Dao 2020 ). Before the industrial revolution, natural sources, including volcanoes, forest fires, and seismic activities, were regarded as the distinct sources of greenhouse gases (GHGs) such as CO 2 , CH 4 , N 2 O, and H 2 O into the atmosphere (Murshed et al. 2020 ; Hussain et al.  2020 ; Sovacool et al.  2021 ; Usman and Balsalobre-Lorente 2022 ; Murshed 2022 ). United Nations Framework Convention on Climate Change (UNFCCC) struck a major agreement to tackle climate change and accelerate and intensify the actions and investments required for a sustainable low-carbon future at Conference of the Parties (COP-21) in Paris on December 12, 2015. The Paris Agreement expands on the Convention by bringing all nations together for the first time in a single cause to undertake ambitious measures to prevent climate change and adapt to its impacts, with increased funding to assist developing countries in doing so. As so, it marks a turning point in the global climate fight. The core goal of the Paris Agreement is to improve the global response to the threat of climate change by keeping the global temperature rise this century well below 2 °C over pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5° C (Sharma et al. 2020 ; Sharif et al. 2020 ; Chien et al. 2021 .

Furthermore, the agreement aspires to strengthen nations’ ability to deal with the effects of climate change and align financing flows with low GHG emissions and climate-resilient paths (Shahbaz et al. 2019 ; Anwar et al. 2021 ; Usman et al. 2022a ). To achieve these lofty goals, adequate financial resources must be mobilized and provided, as well as a new technology framework and expanded capacity building, allowing developing countries and the most vulnerable countries to act under their respective national objectives. The agreement also establishes a more transparent action and support mechanism. All Parties are required by the Paris Agreement to do their best through “nationally determined contributions” (NDCs) and to strengthen these efforts in the coming years (Balsalobre-Lorente et al. 2020 ). It includes obligations that all Parties regularly report on their emissions and implementation activities. A global stock-take will be conducted every five years to review collective progress toward the agreement’s goal and inform the Parties’ future individual actions. The Paris Agreement became available for signature on April 22, 2016, Earth Day, at the United Nations Headquarters in New York. On November 4, 2016, it went into effect 30 days after the so-called double threshold was met (ratification by 55 nations accounting for at least 55% of world emissions). More countries have ratified and continue to ratify the agreement since then, bringing 125 Parties in early 2017. To fully operationalize the Paris Agreement, a work program was initiated in Paris to define mechanisms, processes, and recommendations on a wide range of concerns (Murshed et al. 2021 ). Since 2016, Parties have collaborated in subsidiary bodies (APA, SBSTA, and SBI) and numerous formed entities. The Conference of the Parties functioning as the meeting of the Parties to the Paris Agreement (CMA) convened for the first time in November 2016 in Marrakesh in conjunction with COP22 and made its first two resolutions. The work plan is scheduled to be finished by 2018. Some mitigation and adaptation strategies to reduce the emission in the prospective of Paris agreement are following firstly, a long-term goal of keeping the increase in global average temperature to well below 2 °C above pre-industrial levels, secondly, to aim to limit the rise to 1.5 °C, since this would significantly reduce risks and the impacts of climate change, thirdly, on the need for global emissions to peak as soon as possible, recognizing that this will take longer for developing countries, lastly, to undertake rapid reductions after that under the best available science, to achieve a balance between emissions and removals in the second half of the century. On the other side, some adaptation strategies are; strengthening societies’ ability to deal with the effects of climate change and to continue & expand international assistance for developing nations’ adaptation.

However, anthropogenic activities are currently regarded as most accountable for CC (Murshed et al. 2022 ). Apart from the industrial revolution, other anthropogenic activities include excessive agricultural operations, which further involve the high use of fuel-based mechanization, burning of agricultural residues, burning fossil fuels, deforestation, national and domestic transportation sectors, etc. (Huang et al.  2016 ). Consequently, these anthropogenic activities lead to climatic catastrophes, damaging local and global infrastructure, human health, and total productivity. Energy consumption has mounted GHGs levels concerning warming temperatures as most of the energy production in developing countries comes from fossil fuels (Balsalobre-Lorente et al. 2022 ; Usman et al. 2022b ; Abbass et al. 2021a ; Ishikawa-Ishiwata and Furuya  2022 ).

This review aims to highlight the effects of climate change in a socio-scientific aspect by analyzing the existing literature on various sectorial pieces of evidence globally that influence the environment. Although this review provides a thorough examination of climate change and its severe affected sectors that pose a grave danger for global agriculture, biodiversity, health, economy, forestry, and tourism, and to purpose some practical prophylactic measures and mitigation strategies to be adapted as sound substitutes to survive from climate change (CC) impacts. The societal implications of irregular weather patterns and other effects of climate changes are discussed in detail. Some numerous sustainable mitigation measures and adaptation practices and techniques at the global level are discussed in this review with an in-depth focus on its economic, social, and environmental aspects. Methods of data collection section are included in the supplementary information.

Review methodology

Related study and its objectives.

Today, we live an ordinary life in the beautiful digital, globalized world where climate change has a decisive role. What happens in one country has a massive influence on geographically far apart countries, which points to the current crisis known as COVID-19 (Sarkar et al.  2021 ). The most dangerous disease like COVID-19 has affected the world’s climate changes and economic conditions (Abbass et al. 2022 ; Pirasteh-Anosheh et al.  2021 ). The purpose of the present study is to review the status of research on the subject, which is based on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures” by systematically reviewing past published and unpublished research work. Furthermore, the current study seeks to comment on research on the same topic and suggest future research on the same topic. Specifically, the present study aims: The first one is, organize publications to make them easy and quick to find. Secondly, to explore issues in this area, propose an outline of research for future work. The third aim of the study is to synthesize the previous literature on climate change, various sectors, and their mitigation measurement. Lastly , classify the articles according to the different methods and procedures that have been adopted.

Review methodology for reviewers

This review-based article followed systematic literature review techniques that have proved the literature review as a rigorous framework (Benita  2021 ; Tranfield et al.  2003 ). Moreover, we illustrate in Fig.  1 the search method that we have started for this research. First, finalized the research theme to search literature (Cooper et al.  2018 ). Second, used numerous research databases to search related articles and download from the database (Web of Science, Google Scholar, Scopus Index Journals, Emerald, Elsevier Science Direct, Springer, and Sciverse). We focused on various articles, with research articles, feedback pieces, short notes, debates, and review articles published in scholarly journals. Reports used to search for multiple keywords such as “Climate Change,” “Mitigation and Adaptation,” “Department of Agriculture and Human Health,” “Department of Biodiversity and Forestry,” etc.; in summary, keyword list and full text have been made. Initially, the search for keywords yielded a large amount of literature.

Methodology search for finalized articles for investigations.

Source : constructed by authors

Since 2020, it has been impossible to review all the articles found; some restrictions have been set for the literature exhibition. The study searched 95 articles on a different database mentioned above based on the nature of the study. It excluded 40 irrelevant papers due to copied from a previous search after readings tiles, abstract and full pieces. The criteria for inclusion were: (i) articles focused on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures,” and (ii) the search key terms related to study requirements. The complete procedure yielded 55 articles for our study. We repeat our search on the “Web of Science and Google Scholars” database to enhance the search results and check the referenced articles.

In this study, 55 articles are reviewed systematically and analyzed for research topics and other aspects, such as the methods, contexts, and theories used in these studies. Furthermore, this study analyzes closely related areas to provide unique research opportunities in the future. The study also discussed future direction opportunities and research questions by understanding the research findings climate changes and other affected sectors. The reviewed paper framework analysis process is outlined in Fig.  2 .

Framework of the analysis Process.

Natural disasters and climate change’s socio-economic consequences

Natural and environmental disasters can be highly variable from year to year; some years pass with very few deaths before a significant disaster event claims many lives (Symanski et al.  2021 ). Approximately 60,000 people globally died from natural disasters each year on average over the past decade (Ritchie and Roser  2014 ; Wiranata and Simbolon  2021 ). So, according to the report, around 0.1% of global deaths. Annual variability in the number and share of deaths from natural disasters in recent decades are shown in Fig.  3 . The number of fatalities can be meager—sometimes less than 10,000, and as few as 0.01% of all deaths. But shock events have a devastating impact: the 1983–1985 famine and drought in Ethiopia; the 2004 Indian Ocean earthquake and tsunami; Cyclone Nargis, which struck Myanmar in 2008; and the 2010 Port-au-Prince earthquake in Haiti and now recent example is COVID-19 pandemic (Erman et al.  2021 ). These events pushed global disaster deaths to over 200,000—more than 0.4% of deaths in these years. Low-frequency, high-impact events such as earthquakes and tsunamis are not preventable, but such high losses of human life are. Historical evidence shows that earlier disaster detection, more robust infrastructure, emergency preparedness, and response programmers have substantially reduced disaster deaths worldwide. Low-income is also the most vulnerable to disasters; improving living conditions, facilities, and response services in these areas would be critical in reducing natural disaster deaths in the coming decades.

Global deaths from natural disasters, 1978 to 2020.

Source EMDAT ( 2020 )

The interior regions of the continent are likely to be impacted by rising temperatures (Dimri et al.  2018 ; Goes et al.  2020 ; Mannig et al.  2018 ; Schuurmans  2021 ). Weather patterns change due to the shortage of natural resources (water), increase in glacier melting, and rising mercury are likely to cause extinction to many planted species (Gampe et al.  2016 ; Mihiretu et al.  2021 ; Shaffril et al.  2018 ).On the other hand, the coastal ecosystem is on the verge of devastation (Perera et al.  2018 ; Phillips  2018 ). The temperature rises, insect disease outbreaks, health-related problems, and seasonal and lifestyle changes are persistent, with a strong probability of these patterns continuing in the future (Abbass et al. 2021c ; Hussain et al.  2018 ). At the global level, a shortage of good infrastructure and insufficient adaptive capacity are hammering the most (IPCC  2013 ). In addition to the above concerns, a lack of environmental education and knowledge, outdated consumer behavior, a scarcity of incentives, a lack of legislation, and the government’s lack of commitment to climate change contribute to the general public’s concerns. By 2050, a 2 to 3% rise in mercury and a drastic shift in rainfall patterns may have serious consequences (Huang et al. 2022 ; Gorst et al.  2018 ). Natural and environmental calamities caused huge losses globally, such as decreased agriculture outputs, rehabilitation of the system, and rebuilding necessary technologies (Ali and Erenstein  2017 ; Ramankutty et al.  2018 ; Yu et al.  2021 ) (Table ​ (Table1). 1 ). Furthermore, in the last 3 or 4 years, the world has been plagued by smog-related eye and skin diseases, as well as a rise in road accidents due to poor visibility.

Main natural danger statistics for 1985–2020 at the global level

Source: EM-DAT ( 2020 )

Climate change and agriculture

Global agriculture is the ultimate sector responsible for 30–40% of all greenhouse emissions, which makes it a leading industry predominantly contributing to climate warming and significantly impacted by it (Grieg; Mishra et al.  2021 ; Ortiz et al.  2021 ; Thornton and Lipper  2014 ). Numerous agro-environmental and climatic factors that have a dominant influence on agriculture productivity (Pautasso et al.  2012 ) are significantly impacted in response to precipitation extremes including floods, forest fires, and droughts (Huang  2004 ). Besides, the immense dependency on exhaustible resources also fuels the fire and leads global agriculture to become prone to devastation. Godfray et al. ( 2010 ) mentioned that decline in agriculture challenges the farmer’s quality of life and thus a significant factor to poverty as the food and water supplies are critically impacted by CC (Ortiz et al.  2021 ; Rosenzweig et al.  2014 ). As an essential part of the economic systems, especially in developing countries, agricultural systems affect the overall economy and potentially the well-being of households (Schlenker and Roberts  2009 ). According to the report published by the Intergovernmental Panel on Climate Change (IPCC), atmospheric concentrations of greenhouse gases, i.e., CH 4, CO 2 , and N 2 O, are increased in the air to extraordinary levels over the last few centuries (Usman and Makhdum 2021 ; Stocker et al.  2013 ). Climate change is the composite outcome of two different factors. The first is the natural causes, and the second is the anthropogenic actions (Karami 2012 ). It is also forecasted that the world may experience a typical rise in temperature stretching from 1 to 3.7 °C at the end of this century (Pachauri et al. 2014 ). The world’s crop production is also highly vulnerable to these global temperature-changing trends as raised temperatures will pose severe negative impacts on crop growth (Reidsma et al. 2009 ). Some of the recent modeling about the fate of global agriculture is briefly described below.

Decline in cereal productivity

Crop productivity will also be affected dramatically in the next few decades due to variations in integral abiotic factors such as temperature, solar radiation, precipitation, and CO 2 . These all factors are included in various regulatory instruments like progress and growth, weather-tempted changes, pest invasions (Cammell and Knight 1992 ), accompanying disease snags (Fand et al. 2012 ), water supplies (Panda et al. 2003 ), high prices of agro-products in world’s agriculture industry, and preeminent quantity of fertilizer consumption. Lobell and field ( 2007 ) claimed that from 1962 to 2002, wheat crop output had condensed significantly due to rising temperatures. Therefore, during 1980–2011, the common wheat productivity trends endorsed extreme temperature events confirmed by Gourdji et al. ( 2013 ) around South Asia, South America, and Central Asia. Various other studies (Asseng, Cao, Zhang, and Ludwig 2009 ; Asseng et al. 2013 ; García et al. 2015 ; Ortiz et al. 2021 ) also proved that wheat output is negatively affected by the rising temperatures and also caused adverse effects on biomass productivity (Calderini et al. 1999 ; Sadras and Slafer 2012 ). Hereafter, the rice crop is also influenced by the high temperatures at night. These difficulties will worsen because the temperature will be rising further in the future owing to CC (Tebaldi et al. 2006 ). Another research conducted in China revealed that a 4.6% of rice production per 1 °C has happened connected with the advancement in night temperatures (Tao et al. 2006 ). Moreover, the average night temperature growth also affected rice indicia cultivar’s output pragmatically during 25 years in the Philippines (Peng et al. 2004 ). It is anticipated that the increase in world average temperature will also cause a substantial reduction in yield (Hatfield et al. 2011 ; Lobell and Gourdji 2012 ). In the southern hemisphere, Parry et al. ( 2007 ) noted a rise of 1–4 °C in average daily temperatures at the end of spring season unti the middle of summers, and this raised temperature reduced crop output by cutting down the time length for phenophases eventually reduce the yield (Hatfield and Prueger 2015 ; R. Ortiz 2008 ). Also, world climate models have recommended that humid and subtropical regions expect to be plentiful prey to the upcoming heat strokes (Battisti and Naylor 2009 ). Grain production is the amalgamation of two constituents: the average weight and the grain output/m 2 , however, in crop production. Crop output is mainly accredited to the grain quantity (Araus et al. 2008 ; Gambín and Borrás 2010 ). In the times of grain set, yield resources are mainly strewn between hitherto defined components, i.e., grain usual weight and grain output, which presents a trade-off between them (Gambín and Borrás 2010 ) beside disparities in per grain integration (B. L. Gambín et al. 2006 ). In addition to this, the maize crop is also susceptible to raised temperatures, principally in the flowering stage (Edreira and Otegui 2013 ). In reality, the lower grain number is associated with insufficient acclimatization due to intense photosynthesis and higher respiration and the high-temperature effect on the reproduction phenomena (Edreira and Otegui 2013 ). During the flowering phase, maize visible to heat (30–36 °C) seemed less anthesis-silking intermissions (Edreira et al. 2011 ). Another research by Dupuis and Dumas ( 1990 ) proved that a drop in spikelet when directly visible to high temperatures above 35 °C in vitro pollination. Abnormalities in kernel number claimed by Vega et al. ( 2001 ) is related to conceded plant development during a flowering phase that is linked with the active ear growth phase and categorized as a critical phase for approximation of kernel number during silking (Otegui and Bonhomme 1998 ).

The retort of rice output to high temperature presents disparities in flowering patterns, and seed set lessens and lessens grain weight (Qasim et al. 2020 ; Qasim, Hammad, Maqsood, Tariq, & Chawla). During the daytime, heat directly impacts flowers which lessens the thesis period and quickens the earlier peak flowering (Tao et al. 2006 ). Antagonistic effect of higher daytime temperature d on pollen sprouting proposed seed set decay, whereas, seed set was lengthily reduced than could be explicated by pollen growing at high temperatures 40◦C (Matsui et al. 2001 ).

The decline in wheat output is linked with higher temperatures, confirmed in numerous studies (Semenov 2009 ; Stone and Nicolas 1994 ). High temperatures fast-track the arrangements of plant expansion (Blum et al. 2001 ), diminution photosynthetic process (Salvucci and Crafts‐Brandner 2004 ), and also considerably affect the reproductive operations (Farooq et al. 2011 ).

The destructive impacts of CC induced weather extremes to deteriorate the integrity of crops (Chaudhary et al. 2011 ), e.g., Spartan cold and extreme fog cause falling and discoloration of betel leaves (Rosenzweig et al. 2001 ), giving them a somehow reddish appearance, squeezing of lemon leaves (Pautasso et al. 2012 ), as well as root rot of pineapple, have reported (Vedwan and Rhoades 2001 ). Henceforth, in tackling the disruptive effects of CC, several short-term and long-term management approaches are the crucial need of time (Fig.  4 ). Moreover, various studies (Chaudhary et al. 2011 ; Patz et al. 2005 ; Pautasso et al. 2012 ) have demonstrated adapting trends such as ameliorating crop diversity can yield better adaptability towards CC.

Schematic description of potential impacts of climate change on the agriculture sector and the appropriate mitigation and adaptation measures to overcome its impact.

Climate change impacts on biodiversity

Global biodiversity is among the severe victims of CC because it is the fastest emerging cause of species loss. Studies demonstrated that the massive scale species dynamics are considerably associated with diverse climatic events (Abraham and Chain 1988 ; Manes et al. 2021 ; A. M. D. Ortiz et al. 2021 ). Both the pace and magnitude of CC are altering the compatible habitat ranges for living entities of marine, freshwater, and terrestrial regions. Alterations in general climate regimes influence the integrity of ecosystems in numerous ways, such as variation in the relative abundance of species, range shifts, changes in activity timing, and microhabitat use (Bates et al. 2014 ). The geographic distribution of any species often depends upon its ability to tolerate environmental stresses, biological interactions, and dispersal constraints. Hence, instead of the CC, the local species must only accept, adapt, move, or face extinction (Berg et al. 2010 ). So, the best performer species have a better survival capacity for adjusting to new ecosystems or a decreased perseverance to survive where they are already situated (Bates et al. 2014 ). An important aspect here is the inadequate habitat connectivity and access to microclimates, also crucial in raising the exposure to climate warming and extreme heatwave episodes. For example, the carbon sequestration rates are undergoing fluctuations due to climate-driven expansion in the range of global mangroves (Cavanaugh et al. 2014 ).

Similarly, the loss of kelp-forest ecosystems in various regions and its occupancy by the seaweed turfs has set the track for elevated herbivory by the high influx of tropical fish populations. Not only this, the increased water temperatures have exacerbated the conditions far away from the physiological tolerance level of the kelp communities (Vergés et al. 2016 ; Wernberg et al. 2016 ). Another pertinent danger is the devastation of keystone species, which even has more pervasive effects on the entire communities in that habitat (Zarnetske et al. 2012 ). It is particularly important as CC does not specify specific populations or communities. Eventually, this CC-induced redistribution of species may deteriorate carbon storage and the net ecosystem productivity (Weed et al. 2013 ). Among the typical disruptions, the prominent ones include impacts on marine and terrestrial productivity, marine community assembly, and the extended invasion of toxic cyanobacteria bloom (Fossheim et al. 2015 ).

The CC-impacted species extinction is widely reported in the literature (Beesley et al. 2019 ; Urban 2015 ), and the predictions of demise until the twenty-first century are dreadful (Abbass et al. 2019 ; Pereira et al. 2013 ). In a few cases, northward shifting of species may not be formidable as it allows mountain-dwelling species to find optimum climates. However, the migrant species may be trapped in isolated and incompatible habitats due to losing topography and range (Dullinger et al. 2012 ). For example, a study indicated that the American pika has been extirpated or intensely diminished in some regions, primarily attributed to the CC-impacted extinction or at least local extirpation (Stewart et al. 2015 ). Besides, the anticipation of persistent responses to the impacts of CC often requires data records of several decades to rigorously analyze the critical pre and post CC patterns at species and ecosystem levels (Manes et al. 2021 ; Testa et al. 2018 ).

Nonetheless, the availability of such long-term data records is rare; hence, attempts are needed to focus on these profound aspects. Biodiversity is also vulnerable to the other associated impacts of CC, such as rising temperatures, droughts, and certain invasive pest species. For instance, a study revealed the changes in the composition of plankton communities attributed to rising temperatures. Henceforth, alterations in such aquatic producer communities, i.e., diatoms and calcareous plants, can ultimately lead to variation in the recycling of biological carbon. Moreover, such changes are characterized as a potential contributor to CO 2 differences between the Pleistocene glacial and interglacial periods (Kohfeld et al. 2005 ).

Climate change implications on human health

It is an understood corporality that human health is a significant victim of CC (Costello et al. 2009 ). According to the WHO, CC might be responsible for 250,000 additional deaths per year during 2030–2050 (Watts et al. 2015 ). These deaths are attributed to extreme weather-induced mortality and morbidity and the global expansion of vector-borne diseases (Lemery et al. 2021; Yang and Usman 2021 ; Meierrieks 2021 ; UNEP 2017 ). Here, some of the emerging health issues pertinent to this global problem are briefly described.

Climate change and antimicrobial resistance with corresponding economic costs

Antimicrobial resistance (AMR) is an up-surging complex global health challenge (Garner et al. 2019 ; Lemery et al. 2021 ). Health professionals across the globe are extremely worried due to this phenomenon that has critical potential to reverse almost all the progress that has been achieved so far in the health discipline (Gosling and Arnell 2016 ). A massive amount of antibiotics is produced by many pharmaceutical industries worldwide, and the pathogenic microorganisms are gradually developing resistance to them, which can be comprehended how strongly this aspect can shake the foundations of national and global economies (UNEP 2017 ). This statement is supported by the fact that AMR is not developing in a particular region or country. Instead, it is flourishing in every continent of the world (WHO 2018 ). This plague is heavily pushing humanity to the post-antibiotic era, in which currently antibiotic-susceptible pathogens will once again lead to certain endemics and pandemics after being resistant(WHO 2018 ). Undesirably, if this statement would become a factuality, there might emerge certain risks in undertaking sophisticated interventions such as chemotherapy, joint replacement cases, and organ transplantation (Su et al. 2018 ). Presently, the amplification of drug resistance cases has made common illnesses like pneumonia, post-surgical infections, HIV/AIDS, tuberculosis, malaria, etc., too difficult and costly to be treated or cure well (WHO 2018 ). From a simple example, it can be assumed how easily antibiotic-resistant strains can be transmitted from one person to another and ultimately travel across the boundaries (Berendonk et al. 2015 ). Talking about the second- and third-generation classes of antibiotics, e.g., most renowned generations of cephalosporin antibiotics that are more expensive, broad-spectrum, more toxic, and usually require more extended periods whenever prescribed to patients (Lemery et al. 2021 ; Pärnänen et al. 2019 ). This scenario has also revealed that the abundance of resistant strains of pathogens was also higher in the Southern part (WHO 2018 ). As southern parts are generally warmer than their counterparts, it is evident from this example how CC-induced global warming can augment the spread of antibiotic-resistant strains within the biosphere, eventually putting additional economic burden in the face of developing new and costlier antibiotics. The ARG exchange to susceptible bacteria through one of the potential mechanisms, transformation, transduction, and conjugation; Selection pressure can be caused by certain antibiotics, metals or pesticides, etc., as shown in Fig.  5 .

A typical interaction between the susceptible and resistant strains.

Source: Elsayed et al. ( 2021 ); Karkman et al. ( 2018 )

Certain studies highlighted that conventional urban wastewater treatment plants are typical hotspots where most bacterial strains exchange genetic material through horizontal gene transfer (Fig.  5 ). Although at present, the extent of risks associated with the antibiotic resistance found in wastewater is complicated; environmental scientists and engineers have particular concerns about the potential impacts of these antibiotic resistance genes on human health (Ashbolt 2015 ). At most undesirable and worst case, these antibiotic-resistant genes containing bacteria can make their way to enter into the environment (Pruden et al. 2013 ), irrigation water used for crops and public water supplies and ultimately become a part of food chains and food webs (Ma et al. 2019 ; D. Wu et al. 2019 ). This problem has been reported manifold in several countries (Hendriksen et al. 2019 ), where wastewater as a means of irrigated water is quite common.

Climate change and vector borne-diseases

Temperature is a fundamental factor for the sustenance of living entities regardless of an ecosystem. So, a specific living being, especially a pathogen, requires a sophisticated temperature range to exist on earth. The second essential component of CC is precipitation, which also impacts numerous infectious agents’ transport and dissemination patterns. Global rising temperature is a significant cause of many species extinction. On the one hand, this changing environmental temperature may be causing species extinction, and on the other, this warming temperature might favor the thriving of some new organisms. Here, it was evident that some pathogens may also upraise once non-evident or reported (Patz et al. 2000 ). This concept can be exemplified through certain pathogenic strains of microorganisms that how the likelihood of various diseases increases in response to climate warming-induced environmental changes (Table ​ (Table2 2 ).

Examples of how various environmental changes affect various infectious diseases in humans

Source: Aron and Patz ( 2001 )

A recent example is an outburst of coronavirus (COVID-19) in the Republic of China, causing pneumonia and severe acute respiratory complications (Cui et al. 2021 ; Song et al. 2021 ). The large family of viruses is harbored in numerous animals, bats, and snakes in particular (livescience.com) with the subsequent transfer into human beings. Hence, it is worth noting that the thriving of numerous vectors involved in spreading various diseases is influenced by Climate change (Ogden 2018 ; Santos et al. 2021 ).

Psychological impacts of climate change

Climate change (CC) is responsible for the rapid dissemination and exaggeration of certain epidemics and pandemics. In addition to the vast apparent impacts of climate change on health, forestry, agriculture, etc., it may also have psychological implications on vulnerable societies. It can be exemplified through the recent outburst of (COVID-19) in various countries around the world (Pal 2021 ). Besides, the victims of this viral infection have made healthy beings scarier and terrified. In the wake of such epidemics, people with common colds or fever are also frightened and must pass specific regulatory protocols. Living in such situations continuously terrifies the public and makes the stress familiar, which eventually makes them psychologically weak (npr.org).

CC boosts the extent of anxiety, distress, and other issues in public, pushing them to develop various mental-related problems. Besides, frequent exposure to extreme climatic catastrophes such as geological disasters also imprints post-traumatic disorder, and their ubiquitous occurrence paves the way to developing chronic psychological dysfunction. Moreover, repetitive listening from media also causes an increase in the person’s stress level (Association 2020 ). Similarly, communities living in flood-prone areas constantly live in extreme fear of drowning and die by floods. In addition to human lives, the flood-induced destruction of physical infrastructure is a specific reason for putting pressure on these communities (Ogden 2018 ). For instance, Ogden ( 2018 ) comprehensively denoted that Katrina’s Hurricane augmented the mental health issues in the victim communities.

Climate change impacts on the forestry sector

Forests are the global regulators of the world’s climate (FAO 2018 ) and have an indispensable role in regulating global carbon and nitrogen cycles (Rehman et al. 2021 ; Reichstein and Carvalhais 2019 ). Hence, disturbances in forest ecology affect the micro and macro-climates (Ellison et al. 2017 ). Climate warming, in return, has profound impacts on the growth and productivity of transboundary forests by influencing the temperature and precipitation patterns, etc. As CC induces specific changes in the typical structure and functions of ecosystems (Zhang et al. 2017 ) as well impacts forest health, climate change also has several devastating consequences such as forest fires, droughts, pest outbreaks (EPA 2018 ), and last but not the least is the livelihoods of forest-dependent communities. The rising frequency and intensity of another CC product, i.e., droughts, pose plenty of challenges to the well-being of global forests (Diffenbaugh et al. 2017 ), which is further projected to increase soon (Hartmann et al. 2018 ; Lehner et al. 2017 ; Rehman et al. 2021 ). Hence, CC induces storms, with more significant impacts also put extra pressure on the survival of the global forests (Martínez-Alvarado et al. 2018 ), significantly since their influences are augmented during higher winter precipitations with corresponding wetter soils causing weak root anchorage of trees (Brázdil et al. 2018 ). Surging temperature regimes causes alterations in usual precipitation patterns, which is a significant hurdle for the survival of temperate forests (Allen et al. 2010 ; Flannigan et al. 2013 ), letting them encounter severe stress and disturbances which adversely affects the local tree species (Hubbart et al. 2016 ; Millar and Stephenson 2015 ; Rehman et al. 2021 ).

Climate change impacts on forest-dependent communities

Forests are the fundamental livelihood resource for about 1.6 billion people worldwide; out of them, 350 million are distinguished with relatively higher reliance (Bank 2008 ). Agro-forestry-dependent communities comprise 1.2 billion, and 60 million indigenous people solely rely on forests and their products to sustain their lives (Sunderlin et al. 2005 ). For example, in the entire African continent, more than 2/3rd of inhabitants depend on forest resources and woodlands for their alimonies, e.g., food, fuelwood and grazing (Wasiq and Ahmad 2004 ). The livings of these people are more intensely affected by the climatic disruptions making their lives harder (Brown et al. 2014 ). On the one hand, forest communities are incredibly vulnerable to CC due to their livelihoods, cultural and spiritual ties as well as socio-ecological connections, and on the other, they are not familiar with the term “climate change.” (Rahman and Alam 2016 ). Among the destructive impacts of temperature and rainfall, disruption of the agroforestry crops with resultant downscale growth and yield (Macchi et al. 2008 ). Cruz ( 2015 ) ascribed that forest-dependent smallholder farmers in the Philippines face the enigma of delayed fruiting, more severe damages by insect and pest incidences due to unfavorable temperature regimes, and changed rainfall patterns.

Among these series of challenges to forest communities, their well-being is also distinctly vulnerable to CC. Though the detailed climate change impacts on human health have been comprehensively mentioned in the previous section, some studies have listed a few more devastating effects on the prosperity of forest-dependent communities. For instance, the Himalayan people have been experiencing frequent skin-borne diseases such as malaria and other skin diseases due to increasing mosquitoes, wild boar as well, and new wasps species, particularly in higher altitudes that were almost non-existent before last 5–10 years (Xu et al. 2008 ). Similarly, people living at high altitudes in Bangladesh have experienced frequent mosquito-borne calamities (Fardous; Sharma 2012 ). In addition, the pace of other waterborne diseases such as infectious diarrhea, cholera, pathogenic induced abdominal complications and dengue has also been boosted in other distinguished regions of Bangladesh (Cell 2009 ; Gunter et al. 2008 ).

Pest outbreak

Upscaling hotter climate may positively affect the mobile organisms with shorter generation times because they can scurry from harsh conditions than the immobile species (Fettig et al. 2013 ; Schoene and Bernier 2012 ) and are also relatively more capable of adapting to new environments (Jactel et al. 2019 ). It reveals that insects adapt quickly to global warming due to their mobility advantages. Due to past outbreaks, the trees (forests) are relatively more susceptible victims (Kurz et al. 2008 ). Before CC, the influence of factors mentioned earlier, i.e., droughts and storms, was existent and made the forests susceptible to insect pest interventions; however, the global forests remain steadfast, assiduous, and green (Jactel et al. 2019 ). The typical reasons could be the insect herbivores were regulated by several tree defenses and pressures of predation (Wilkinson and Sherratt 2016 ). As climate greatly influences these phenomena, the global forests cannot be so sedulous against such challenges (Jactel et al. 2019 ). Table ​ Table3 3 demonstrates some of the particular considerations with practical examples that are essential while mitigating the impacts of CC in the forestry sector.

Essential considerations while mitigating the climate change impacts on the forestry sector

Source : Fischer ( 2019 )

Climate change impacts on tourism

Tourism is a commercial activity that has roots in multi-dimensions and an efficient tool with adequate job generation potential, revenue creation, earning of spectacular foreign exchange, enhancement in cross-cultural promulgation and cooperation, a business tool for entrepreneurs and eventually for the country’s national development (Arshad et al. 2018 ; Scott 2021 ). Among a plethora of other disciplines, the tourism industry is also a distinct victim of climate warming (Gössling et al. 2012 ; Hall et al. 2015 ) as the climate is among the essential resources that enable tourism in particular regions as most preferred locations. Different places at different times of the year attract tourists both within and across the countries depending upon the feasibility and compatibility of particular weather patterns. Hence, the massive variations in these weather patterns resulting from CC will eventually lead to monumental challenges to the local economy in that specific area’s particular and national economy (Bujosa et al. 2015 ). For instance, the Intergovernmental Panel on Climate Change (IPCC) report demonstrated that the global tourism industry had faced a considerable decline in the duration of ski season, including the loss of some ski areas and the dramatic shifts in tourist destinations’ climate warming.

Furthermore, different studies (Neuvonen et al. 2015 ; Scott et al. 2004 ) indicated that various currently perfect tourist spots, e.g., coastal areas, splendid islands, and ski resorts, will suffer consequences of CC. It is also worth noting that the quality and potential of administrative management potential to cope with the influence of CC on the tourism industry is of crucial significance, which renders specific strengths of resiliency to numerous destinations to withstand against it (Füssel and Hildén 2014 ). Similarly, in the partial or complete absence of adequate socio-economic and socio-political capital, the high-demanding tourist sites scurry towards the verge of vulnerability. The susceptibility of tourism is based on different components such as the extent of exposure, sensitivity, life-supporting sectors, and capacity assessment factors (Füssel and Hildén 2014 ). It is obvious corporality that sectors such as health, food, ecosystems, human habitat, infrastructure, water availability, and the accessibility of a particular region are prone to CC. Henceforth, the sensitivity of these critical sectors to CC and, in return, the adaptive measures are a hallmark in determining the composite vulnerability of climate warming (Ionescu et al. 2009 ).

Moreover, the dependence on imported food items, poor hygienic conditions, and inadequate health professionals are dominant aspects affecting the local terrestrial and aquatic biodiversity. Meanwhile, the greater dependency on ecosystem services and its products also makes a destination more fragile to become a prey of CC (Rizvi et al. 2015 ). Some significant non-climatic factors are important indicators of a particular ecosystem’s typical health and functioning, e.g., resource richness and abundance portray the picture of ecosystem stability. Similarly, the species abundance is also a productive tool that ensures that the ecosystem has a higher buffering capacity, which is terrific in terms of resiliency (Roscher et al. 2013 ).

Climate change impacts on the economic sector

Climate plays a significant role in overall productivity and economic growth. Due to its increasingly global existence and its effect on economic growth, CC has become one of the major concerns of both local and international environmental policymakers (Ferreira et al. 2020 ; Gleditsch 2021 ; Abbass et al. 2021b ; Lamperti et al. 2021 ). The adverse effects of CC on the overall productivity factor of the agricultural sector are therefore significant for understanding the creation of local adaptation policies and the composition of productive climate policy contracts. Previous studies on CC in the world have already forecasted its effects on the agricultural sector. Researchers have found that global CC will impact the agricultural sector in different world regions. The study of the impacts of CC on various agrarian activities in other demographic areas and the development of relative strategies to respond to effects has become a focal point for researchers (Chandioet al. 2020 ; Gleditsch 2021 ; Mosavi et al. 2020 ).

With the rapid growth of global warming since the 1980s, the temperature has started increasing globally, which resulted in the incredible transformation of rain and evaporation in the countries. The agricultural development of many countries has been reliant, delicate, and susceptible to CC for a long time, and it is on the development of agriculture total factor productivity (ATFP) influence different crops and yields of farmers (Alhassan 2021 ; Wu  2020 ).

Food security and natural disasters are increasing rapidly in the world. Several major climatic/natural disasters have impacted local crop production in the countries concerned. The effects of these natural disasters have been poorly controlled by the development of the economies and populations and may affect human life as well. One example is China, which is among the world’s most affected countries, vulnerable to natural disasters due to its large population, harsh environmental conditions, rapid CC, low environmental stability, and disaster power. According to the January 2016 statistical survey, China experienced an economic loss of 298.3 billion Yuan, and about 137 million Chinese people were severely affected by various natural disasters (Xie et al. 2018 ).

Mitigation and adaptation strategies of climate changes

Adaptation and mitigation are the crucial factors to address the response to CC (Jahanzad et al. 2020 ). Researchers define mitigation on climate changes, and on the other hand, adaptation directly impacts climate changes like floods. To some extent, mitigation reduces or moderates greenhouse gas emission, and it becomes a critical issue both economically and environmentally (Botzen et al. 2021 ; Jahanzad et al. 2020 ; Kongsager 2018 ; Smit et al. 2000 ; Vale et al. 2021 ; Usman et al. 2021 ; Verheyen 2005 ).

Researchers have deep concern about the adaptation and mitigation methodologies in sectoral and geographical contexts. Agriculture, industry, forestry, transport, and land use are the main sectors to adapt and mitigate policies(Kärkkäinen et al. 2020 ; Waheed et al. 2021 ). Adaptation and mitigation require particular concern both at the national and international levels. The world has faced a significant problem of climate change in the last decades, and adaptation to these effects is compulsory for economic and social development. To adapt and mitigate against CC, one should develop policies and strategies at the international level (Hussain et al. 2020 ). Figure  6 depicts the list of current studies on sectoral impacts of CC with adaptation and mitigation measures globally.

Sectoral impacts of climate change with adaptation and mitigation measures.

Conclusion and future perspectives

Specific socio-agricultural, socio-economic, and physical systems are the cornerstone of psychological well-being, and the alteration in these systems by CC will have disastrous impacts. Climate variability, alongside other anthropogenic and natural stressors, influences human and environmental health sustainability. Food security is another concerning scenario that may lead to compromised food quality, higher food prices, and inadequate food distribution systems. Global forests are challenged by different climatic factors such as storms, droughts, flash floods, and intense precipitation. On the other hand, their anthropogenic wiping is aggrandizing their existence. Undoubtedly, the vulnerability scale of the world’s regions differs; however, appropriate mitigation and adaptation measures can aid the decision-making bodies in developing effective policies to tackle its impacts. Presently, modern life on earth has tailored to consistent climatic patterns, and accordingly, adapting to such considerable variations is of paramount importance. Because the faster changes in climate will make it harder to survive and adjust, this globally-raising enigma calls for immediate attention at every scale ranging from elementary community level to international level. Still, much effort, research, and dedication are required, which is the most critical time. Some policy implications can help us to mitigate the consequences of climate change, especially the most affected sectors like the agriculture sector;

Warming might lengthen the season in frost-prone growing regions (temperate and arctic zones), allowing for longer-maturing seasonal cultivars with better yields (Pfadenhauer 2020 ; Bonacci 2019 ). Extending the planting season may allow additional crops each year; when warming leads to frequent warmer months highs over critical thresholds, a split season with a brief summer fallow may be conceivable for short-period crops such as wheat barley, cereals, and many other vegetable crops. The capacity to prolong the planting season in tropical and subtropical places where the harvest season is constrained by precipitation or agriculture farming occurs after the year may be more limited and dependent on how precipitation patterns vary (Wu et al. 2017 ).

The genetic component is comprehensive for many yields, but it is restricted like kiwi fruit for a few. Ali et al. ( 2017 ) investigated how new crops will react to climatic changes (also stated in Mall et al. 2017 ). Hot temperature, drought, insect resistance; salt tolerance; and overall crop production and product quality increases would all be advantageous (Akkari 2016 ). Genetic mapping and engineering can introduce a greater spectrum of features. The adoption of genetically altered cultivars has been slowed, particularly in the early forecasts owing to the complexity in ensuring features are expediently expressed throughout the entire plant, customer concerns, economic profitability, and regulatory impediments (Wirehn 2018 ; Davidson et al. 2016 ).

To get the full benefit of the CO 2 would certainly require additional nitrogen and other fertilizers. Nitrogen not consumed by the plants may be excreted into groundwater, discharged into water surface, or emitted from the land, soil nitrous oxide when large doses of fertilizer are sprayed. Increased nitrogen levels in groundwater sources have been related to human chronic illnesses and impact marine ecosystems. Cultivation, grain drying, and other field activities have all been examined in depth in the studies (Barua et al. 2018 ).

• The technological and socio-economic adaptation

The policy consequence of the causative conclusion is that as a source of alternative energy, biofuel production is one of the routes that explain oil price volatility separate from international macroeconomic factors. Even though biofuel production has just begun in a few sample nations, there is still a tremendous worldwide need for feedstock to satisfy industrial expansion in China and the USA, which explains the food price relationship to the global oil price. Essentially, oil-exporting countries may create incentives in their economies to increase food production. It may accomplish by giving farmers financing, seedlings, fertilizers, and farming equipment. Because of the declining global oil price and, as a result, their earnings from oil export, oil-producing nations may be unable to subsidize food imports even in the near term. As a result, these countries can boost the agricultural value chain for export. It may be accomplished through R&D and adding value to their food products to increase income by correcting exchange rate misalignment and adverse trade terms. These nations may also diversify their economies away from oil, as dependence on oil exports alone is no longer economically viable given the extreme volatility of global oil prices. Finally, resource-rich and oil-exporting countries can convert to non-food renewable energy sources such as solar, hydro, coal, wind, wave, and tidal energy. By doing so, both world food and oil supplies would be maintained rather than harmed.

IRENA’s modeling work shows that, if a comprehensive policy framework is in place, efforts toward decarbonizing the energy future will benefit economic activity, jobs (outweighing losses in the fossil fuel industry), and welfare. Countries with weak domestic supply chains and a large reliance on fossil fuel income, in particular, must undertake structural reforms to capitalize on the opportunities inherent in the energy transition. Governments continue to give major policy assistance to extract fossil fuels, including tax incentives, financing, direct infrastructure expenditures, exemptions from environmental regulations, and other measures. The majority of major oil and gas producing countries intend to increase output. Some countries intend to cut coal output, while others plan to maintain or expand it. While some nations are beginning to explore and execute policies aimed at a just and equitable transition away from fossil fuel production, these efforts have yet to impact major producing countries’ plans and goals. Verifiable and comparable data on fossil fuel output and assistance from governments and industries are critical to closing the production gap. Governments could increase openness by declaring their production intentions in their climate obligations under the Paris Agreement.

It is firmly believed that achieving the Paris Agreement commitments is doubtlful without undergoing renewable energy transition across the globe (Murshed 2020 ; Zhao et al. 2022 ). Policy instruments play the most important role in determining the degree of investment in renewable energy technology. This study examines the efficacy of various policy strategies in the renewable energy industry of multiple nations. Although its impact is more visible in established renewable energy markets, a renewable portfolio standard is also a useful policy instrument. The cost of producing renewable energy is still greater than other traditional energy sources. Furthermore, government incentives in the R&D sector can foster innovation in this field, resulting in cost reductions in the renewable energy industry. These nations may export their technologies and share their policy experiences by forming networks among their renewable energy-focused organizations. All policy measures aim to reduce production costs while increasing the proportion of renewables to a country’s energy system. Meanwhile, long-term contracts with renewable energy providers, government commitment and control, and the establishment of long-term goals can assist developing nations in deploying renewable energy technology in their energy sector.

Author contribution

KA: Writing the original manuscript, data collection, data analysis, Study design, Formal analysis, Visualization, Revised draft, Writing-review, and editing. MZQ: Writing the original manuscript, data collection, data analysis, Writing-review, and editing. HS: Contribution to the contextualization of the theme, Conceptualization, Validation, Supervision, literature review, Revised drapt, and writing review and editing. MM: Writing review and editing, compiling the literature review, language editing. HM: Writing review and editing, compiling the literature review, language editing. IY: Contribution to the contextualization of the theme, literature review, and writing review and editing.

Availability of data and material

Declarations.

Not applicable.

The authors declare no competing interests.

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Contributor Information

Kashif Abbass, Email: nc.ude.tsujn@ssabbafihsak .

Muhammad Zeeshan Qasim, Email: moc.kooltuo@888misaqnahseez .

Huaming Song, Email: nc.ude.tsujn@gnimauh .

Muntasir Murshed, Email: [email protected] .

Haider Mahmood, Email: moc.liamtoh@doomhamrediah .

Ijaz Younis, Email: nc.ude.tsujn@sinuoyzaji .

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From Panama to Suez and the Turkish Straits: The cost of climate change for International trade

The cost of climate change on three key chokepoints for international trade could reach up to 34 billion USD in 2030. A new study led by the CMCC also highlights the possible effects on production and prices of agricultural commodities.  

Global trade relies on maritime routes, which pass through key chokepoints, for smooth and timely shipments. Analyzing how climate change will impact these key areas for global trade, and hence both national and global economies, is an area of concern when assessing the adaptation measures, particularly in the context of the unequal distribution of climate change impacts on agriculture.

A new study, involving an international team coordinated by CMCC researcher Ramón Key , looks at the potential macro-economic effects of climate change affecting operations in three maritime chokepoints, namely the Panama Canal, the Suez Canal, and the Turkish Straits.

By looking specifically at agricultural commodities and using a combination of models, among which a “logistics” model of maritime trade flows, the study predicts the direction of changes in the main economic variables under scrutiny with similar results across models.

Most notably, climate change was shown to affect chokepoints’ operations with effects on production and prices of agricultural commodities that in turn brought a downturn in global GDP. In fact, the study found that although trade re-composition generates winners and losers, total losses tend to prevail and could reach 34 billion USD (2014 prices) in 2030.

“Given the importance of trade on agricultural commodities as an adaptation mechanism, the interest in the subject continues. Now we are looking at measuring the simultaneous effects of climate change events affecting the chokepoints, and the production of agricultural commodities around the world,” says Key.

Weather events in remote locations, such as the Panama Canal, could have cascading effects on the EU, with potential losses of 2 billion USD in GDP. And perhaps of even more concern is the impact on mid- and low- income countries, with the study showing that North Africa, the Middle East and Sub-Saharan Africa are even more vulnerable to these effects, once again highlighting the asymmetry and unequal distribution of impacts of climate change on agriculture .

As the frequency and intensity of extreme events continues to rise, the need for further adaptation measures by the authorities managing the chokepoints is therefore recommended, with the paper suggesting that these should include investments in monitoring and control systems as well as the infrastructure of the chokepoints.

For more information:

Key, R., Parrado, R., Delpiazzo, E. et al. Potential climate-induced impacts on trade: the case of agricultural commodities and maritime chokepoints. J. shipp. trd. 9, 11 (2024). https://doi.org/10.1186/s41072-024-00170-3

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Climate change: impact on agriculture

Climate crisis has deeper implications for agriculture which is already facing formidable challenge of lower productivity in this time of food insecurity. Arable land is shrinking due to its overuse for the non-agricultural purposes — like transport projects, infrastructure development, new settlement patterns and establishing industries closer to water resources — across the world. Further, cultivable land is diminishing due to overgrazing of livestock which tramples the soil squeezing out air, water and nutrients. Livestock grazing on large expanses of grassy land generates about 15% to greenhouse gases and uses major portion of cultivable land causing deforestation and biodiversity. A third of global food production is at risk from climate crisis but at the same time our food production through agriculture is also major a contributor to carbon emissions causing climate breakdown. Thus, agriculture needs to develop itself environment friendly and meet the food demand which is expected to rise by 35% in the year 2030. Hence, switching over to modern methods of climate farming has become imperative for survival of mankind.

Agriculture in Pakistan accounts for 25% of its GDP. The country is one of the world’s top producers of food crops and fruits. Nevertheless, its productivity remains insufficient for domestic as well as commercial needs. Farmers in Pakistan are facing huge problems including water shortage, soil erosion and nutrition-deficient land and they are unable to access major farm inputs including good quality seeds, suitable fertiliser, irrigation and mechanisation. They are not provided with easy loans for purchasing farm inputs and handling climate contingencies. The performance of farmers largely depends on climatic conditions and thus it injects an element of uncertainty causing demotivation among farmers who have no access to fair price for their produce due to underdeveloped nature of market mechanism and weak government control. The lack of good water governance, ineffective planning for mitigating climatic catastrophes through community resilience further discourage farmers to take huge climate risks associated with farming in the absence of climate assurance policy.

Agriculture is very sensitive to climate because the agricultural practices are impacted by the variation in temperature and precipitation. Warmer temperatures can disturb the process of pollination at the time plants bloom. Air pollution also affects the photosynthesis process in plants and increases crop sensitivity to various diseases. Recent heavy rains in Pakistan not only damaged crops by eroding soil and depleting its nutrients but also affected the quality of water in lakes, rivers and other wetlands which further disturbed eco-system and affected coastal communities already stressed by pollution, warming marine waters and ocean acidification. Floods of 2022 drastically impacted agricultural productivity, killed livestock, destroyed houses and devastated the life in rural areas where health of farmers was endangered by various diseases caused by humidity and water pollution.

However, the production of food through organic means has more potential to deal with wider climate events in Pakistan. Organic crops are not treated by chemicals and pesticides. Thus, farmers use manure and compost and choose natural methods of pest control including crop rotation. Further, bagasse and other waste of crops is used to make chipboard and paper to replace plastic for producing environment friendly products. Further, increasing forest cultivation provides us timber and other necessary raw material for medicines and papermaking. Thus, environmental sustainability can be ensured by protecting forests against all risks including wildfire and by growing more mangrove trees. Moreover, diverse range of crops should be encouraged to minimise environmental degradation by using holistic approach of Climate Smart Agriculture (CSA). New methods of intensified farming adaptable to local conditions should be encouraged to reduce the food insecurity affecting more than 30% of population. It needs to use modern agriculture techniques and significantly increases its present 47% of total land under cultivation.

Transforming farming on modern lines by globalising agricultural techniques for the benefit of agrarian community is important to learn from diverse experiences about how to avoid using conventional methods. New practices of monitoring health of livestock need to be applied, and hydroponic system should be encouraged to cut down on fertilisers and pesticides. In addition to mechanised farming, irrigation, temperature, lightening, water and level of carbon dioxide at farms should be monitored through digital means. Further, artificial intelligence should be used to supply farm inputs, protect crops from insects through aerial sprays and ensure crop surveillance through drone technology. Higher productivity-based farming should be encouraged to cater to the needs of a booming population. Pakistan needs to increase the production of staple as well as cash crops by using improved methods of irrigation in addition to use of good quality seeds and other inputs. The newly formed government has the economy as its foremost challenge ahead, but economic stability cannot come without increasing agricultural productivity on a sustained basis. Further, organic farming needs to be incentivised for the export purpose to earn foreign exchange. The government should facilitate farming community for cultivating those crops which are demanded in international market. Pakistan also needs to increase reining of coastline, inland, river, lake and aquaculture sources of fishing and remove inadequacies in quality control to fetch high prices abroad.

The incumbent government has accelerated its efforts to attract foreign investment by gearing up the Special Investment Facilitation Council and to broaden the horizons of CPEC during its second phase and digitalise economic sources. Chinese investment in Special Economic Zones would help diversify Pakistan’s export basket. Thus, the agriculture sector is expected to be upgraded. Green economy will be boosted by improving the conditions of farmers; developing infrastructure and markets; promoting climate friendly agriculture; focusing on robust technology transfer; and leveraging the expertise of agriculturists. It will enable Pakistan to support global response to complex transnational challenges of growing food and water insecurity and to substantially improve its agricultural output.

Published in The Express Tribune, May 12 th , 2024.

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