EcoCrop Model Research Articles

Dataset of the suitability of major food crops in Africa under climate change

Understanding the extent and adapting to the impacts of climate change in the agriculture sector in Africa requires robust data on which technical and policy decisions can be based. However, there are no publicly available comprehensive data of which crops are suitable where under current and projected climate conditions for impact assessments and targeted adaptation planning. We developed a dataset on crop suitability of 23 major food crops (eight cereals, six legumes & pulses, six root & tuber crops, and three in banana-related family) for rainfed agriculture in Africa in terms of area and produced quantity. This dataset is based on the EcoCrop model parameterized with temperature, precipitation and soil data and is available for the historical period and until mid-century. The scenarios used for future projections are SSP1:RCP2.6, SSP3:RCP7.0 and SSP5:RCP8.5. The dataset provides a quantitative assessment of the impacts of climate change on crop production potential and can enable applications and linkages of crop impact studies to other socioeconomic aspects, thereby facilitating more comprehensive understanding of climate change impacts and assessment of options for building resilience.

Suitability of root, tuber, and banana crops in Central Africa can be favoured under future climates

ContextClimate change is projected to negatively impact food systems in Sub-Saharan Africa. The magnitude of these impacts is expected to be amplified by the extensive reliance on rainfed agriculture and the prevalence of subsistence farming. In the Great Lakes Region of Central Africa, smallholder farming households are largely dependent on root, tuber and banana crops. However, the potential impacts of various climate change scenarios on these crops are not well reported. Yet, data-rich insights about the future impacts of climate change on these crops and the adaptive capacity of food systems in the Great Lakes Region is critical to inform research and development investments towards regional climate change adaptation. ObjectivesWe aimed to gain insights of potential impacts of climate change on root, tuber, and banana crops in the Great Lakes Region, specifically investigating changes to localised crop suitability, planting dates, and identifying potential ‘climate-proof’ variety types of each crop for specific geographies. MethodsWe developed a modified version of the EcoCrop model to analyse the suitability of future climates for four key root, tuber, and banana crops (banana, cassava, potato, and sweetpotato) and a suite of varieties for each (typical, heat-tolerant, drought-tolerant, and early maturing). The model considers only the direct impacts of climate change on crop suitability. It does not consider how climate change impacts crop suitability by affecting the occurrence of extreme weather events or indirect effects on incidence and severity of pest and disease outbreaks. Results and conclusionsOur results demonstrate that climate change will be somewhat favourable to root, tuber, and banana-based systems, with only widespread negative impacts seen for potato. These changes should be qualified by the observation that in most cases the environmental suitability for banana, cassava, and sweetpotato will remain constant or improve if farmers shift planting schedules. Location- and crop-dependent shifts to different variety types were found to be effective in improving suitability under future climates. SignificanceData driven insights generated from this work can be used as a first step in developing spatially explicit recommendations for both farmers and decision-makers on how to adapt to climate change and plan investment in the research needed to adapt root, tuber, and banana-based livelihoods and systems to those long-term changes.

Action needed for staple crops in the Andean-Amazon foothills because of climate change

The Andean-Amazon foothills region, shaped by Andean moist forests and Amazon forests in southwestern Colombia, Napo province in Ecuador, and Ucayali Province and Napo Basin in Peru, provides local and global ecosystem services as food, water, world climate regulation, water purification, and carbon absorption. However, it faces major problems of land-use change that are exacerbated by climate change that affects these ecosystem services. For instance, conventional agriculture contribute to deforestation, soil degradation, and biodiversity loss, which might be further aggravated by climate change–induced droughts, thus reducing staple crop production and, consequently, food security. Cassava (Manihot esculenta Crantz), maize (Zea mays L.), and plantain (Musa paradisiaca L.) are major staple crops in the region. They play a key role for food security and local farmers’ income but are highly exposed to climate risks. This article aims to quantify the level of exposure to climate change (measured as climatic suitability) of these crops in the Andean-Amazon foothills by using the EcoCrop model by the 2030s, 2050s, and 2080s under Representative Concentration Pathway 2.6, 4.5, and 8.5 scenarios. EcoCrop results showed that, whereas cassava will not lose climatic suitability, maize will lose more than half of its current suitable area, and plantain will gain and lose area, which would affect local food security. Globally, these results are important in highlighting adaptive and cost-effective strategies in agriculture and suggest that agricultural crop diversification may improve resilience by promoting the use of local crops varieties.

Improving African bean productivity in a changing global environment

Common bean (Phaseolus vulgaris) cultivation delivers income to farmers and nutrition to consumers in sub-Saharan Africa. With a growing population and land scarcity, there will be greater pressure to intensify common bean and other crops in the region. However, high temperatures and increased drought may reduce common bean yields in Africa. Climate change impacts on climbing beans are not yet clear. Therefore, the objective of this study was to evaluate the expected impact of climate change on suitability for climbing bean cultivation. The study identifies areas suitable to cultivate climbing beans in sub-Saharan Africa, taking into account the present climate as well as the predicted future climate. The analysis compares and evaluates the performance of two ecological niche models—Ecocrop and MaxEnt—under future climatic conditions, according to global circulation models of the last Intergovernmental Panel on Climate Change (IPCC) report. The Ecocrop model results showed a wide common bean distribution in comparison with those of MaxEnt, which showed a better approximation to the current distribution of climbing beans. The MaxEnt model performed well as judged by validation statistics and comparison with climbing bean production data. Overall, the models project climate change to decrease the suitability of climbing beans in Africa. The results suggest that rising temperatures and variable rainfall will most severely affect bean production in countries of southern Africa such as Zambia, Zimbabwe, Malawi, and Mozambique. In other parts of the tropics, climbing bean cultivation may suffer rising temperatures and more variable rainfall at higher latitudes, as opposed to areas near the equator. The study suggests where agricultural specialists can promote climbing beans in Africa and other regions of the world, where they are highly suitable and not yet widely cultivated. Researchers can improve studies such as this one for beans and other crops by developing more detailed calibration and validation data sets for modeling efforts.

Future changes in mean temperature and total precipitation and climate suitability of yam (Dioscorea spp.) in major yam-growing environments in India

The experiment was conducted to project climatic changes in major yam-growing environments and also calibrated and evaluated the eco crop model to study the impact of 2030 climate change on yam climate suitability in major yam-growing environments in India. The current climate and future climate projections of 22 GCMs from the SRES-A1B emission scenario were used. The projected change in annual mean temperature and total annual precipitation in yam-growing areas ranged from 0.9 to 1.3°C and from 9 to 128 mm respectively. The calibrated data were used to constrain the eco crop model to find out the suitability of current and future climatic conditions. The results of projected climate change over the Indian yam-growing areas using 22 GCMs of SRES-A1B emission scenario revealed that change in suitability will be in the range of-2.04 to 23.5 per cent.

Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor)

The Law of the Minimum is often implemented using t-norm or fuzzy intersection. We propose the use of t-conorm or fuzzy union for climate suitability assessment of a grass species using annual ryegrass (Lolium multiflorum Lam.) as an example and evaluate the performance for alfalfa (Medicago sativa L.) and sorghum (Sorghum bicolor L.). The ORF and ANDF models, which are fuzzy logic systems based on t-conorm and t-norm between temperature and moisture conditions, respectively, were developed to assess the quality of climate conditions for crops. The parameter values for both models were obtained from existing knowledge, e.g., the EcoCrop database. These models were then compared with the EcoCrop model, which is based on the t-norm. The ORF model explained greater variation (54%) in the yield of annual ryegrass at 84 site-years than the ANDF model (43%) and the EcoCrop model (5%). The climate suitability index of the ORF model had the greatest likelihood of occurrence of annual ryegrass compared to the other models. The ORF model also had similar results for alfalfa and sorghum. We emphasize that the fuzzy logic system for climate suitability assessment can be developed using knowledge rather than presence-only data, which can facilitate more complex approaches such as the incorporation of biotic interaction into species distribution modeling.

Projected climate changes and environment suitability of foot yam in major growing areas of India

The projected climatic changes were in the major elephant foot yam growing environments of India which were identified based on expert knowledge and from literature review; and also calibrated and evaluated the EcoCrop model, of FAO to study the impact of 2030 climate the suitability of elephant foot yam in the major growing environments of India. The current and future climatic projections of 22 Global Circulation models from the SRES-A1B emission scenario were used for the study. A total of 9345 unique coordinates, as points was obtained as elephant foot yam presence points in India. The projected change in annual mean temperature and total annual precipitation in the major growing areas ranged from 0.9 to 1.2°C and from 19 to 68 mm respectively. The calibrated data were used to drive the EcoCrop model to find out the suitability of current and future climatic conditions. The change in suitability for all the 22 GCMs used was calculated on pixel basis and the mean suitability change indicate that elephant foot yam is actually positively impacted in the current growing areas of India with 0.8 to 9.6% changes in climate suitability. The overall suitability change in the major elephant foot yam growing areas showed that the crop is potentially highly resilient to future climatic changes.

Effects of Climate and Land Use Change on Food Security: a Case Study of Phra Nakhon Si Ayutthaya Province, Thailand

Addressing climate change for food security poses a great challenge to social welfare in developing countries where agricultural sector plays a significant role in driving economic growth and sustaining livelihoods. Natural climate variability and anthropogenic emissions introduce the considerable effects on agriculture yields and productivity, including nexus of food-water-energy. This paper aims at exploring land suitability for rice farmland in Phra NaKhon Si Ayuttaya province. Projection of temperature and precipitation over a province in 2050 in according to representative concentration pathway (RCP) 4.5 and 8.5 scenarios show a few increase in mean monthly temperature, monthly maximum temperature and minimum temperature about 0.5 to 1 degree celcius. Annual precipitation tends to be reduced for RCP 8.5 in comparison to RCP 4.5. Land suitability for growing rice is simulated by using EcoCrop model which requires input parameters from temperature and precipitation projection in 2050. Results reveal a decreasing in land suitability for rice both under RCP 4.5 and 8.5 scenarios. Agricultural land use tends to be transformed into residential and industrial land by 2050, resulting in the reduction in agricultural land and rice production. Successful adaptation to climate change in the agricultural sector needs to be encouraged by government to build robust cooperative efforts from all stakeholders.Keywords: Climate change; rice; Phra Nakhon Si Ayuttaya, food security; adaptation

Improvement of spatial modelling of crop suitability using a new digital soil map of Tanzania

Climate change is projected to have widespread impacts on the climate suitability and geographical distribution of agricultural crops. Simulations were conducted on the suitability of common beans (Phaseolus vulgaris L.) in Tanzania under progressive climate change, taking into account a soil fertility constraint. The results were used to assess the effects of incorporating information on soil fertility, more specifically soil organic carbon (SOC) content, into the niche-based EcoCrop model, which was previously based only on climate data. Extending the model improved the correlation between predicted suitability and production statistics at the regional level. Simulated suitability was highly sensitive to SOC-related model parameters, implying that it is critical to incorporate these parameters in order to improve estimates of crop suitability. Simulations using the best parameterisation identified showed that low SOC is currently more limiting for common bean suitability than climate in 51% of the Tanzanian land area (protected areas excluded). However, future projections suggest that climate will be more limiting for the geographic distribution of common beans than SOC in the near future (2030). Spatial data on predicted SOC levels and other soil properties in future scenario modelling are needed for better identification of suitable areas for common bean production.

Projected changes in mean temperature and total precipitation and climate suitability of cassava (Manihot esculenta) in major growing environments of India

Cassava (Manihot esculenta Crantz) is an important food crop of India cultivated in an area of 228 000 ha for food, feed and fuel, contributes to food security, equity, poverty alleviation and environmental protection. This study examined the projected climatic changes in the major cassava growing environments of India and also calibrated and evaluated the EcoCrop model to study the impact of 2030 climate on cassava climate suitability in the major growing environments of India. The current climate and future climate projections of 22 GCMs from the SRES-A1B emission scenario were used for the study. The projected change in annual mean temperature and total annual precipitation in the major growing areas ranged from 0.9 to 1.2ºC and from 6.8 to 112.4 mm, respectively. The calibrated data were used to drive the EcoCrop model to find out the suitability of current and future climatic conditions. The change in suitability for all the 22 GCMs used was calculated on pixel basis and the mean suitability change indicate that cassava is actually positively impacted in the current growing areas of India with -2.2 to 15% changes in climate suitability. This study concluded that cassava is potentially highly resilient to future climatic changes and it can become a future crop in India, where other crops would fail due to climate change.

Wild rice (Oryza spp.) germplasm collections from gangetic plains and eastern region of India: Diversity mapping and habitat prediction using ecocrop model

Wild Rice (Oryza Spp.) Germplasm Collections from Gangetic Plains and Eastern Region of India: Diversity Mapping and Habitat Prediction using Ecocrop Model Wild rice collections form the priority target group among rice germplasm for characterization, evaluation, conservation and utilization. So far 889 accessions of wild rice (Oryza spp.) germplasm were collected by ICAR-NBPGR from Gangetic Plains and eastern region of India in last four decades. Passport information on assembled germplasm was used to know habitat specificity and diversity pattern to predict their distribution; this will help execution of explorations. Germplasm accessions belonging to six different wild rice taxa–Oryza meyeriana var. granulata (4), O. nivara (484), O. officinalis (50), O. rufipogon (367), O. sativa var. spontanea (18) and Porteresia coarctata (10) were collected from Gangetic Plains and eastern region of India. GIS mapping had shown that maximum numbers of wild rice species were collected from north-western and north-eastern regions of Odisha. In this study, we used current (1950-2000) and projected climate data for 2050 through ‘EcoCrop’ model to predict habitat suitability areas for wild rice. Predicted habitat suitability map (1950-2000) had shown that at present >80% area of Gangetic Plains and eastern region of India are suitable for wild rice occurrence. Projection for 2050 indicated that nearly 47.7% areas becoming less suitable for wild rice distribution, indicating urgent need for exploration in prioritized areas for wild rice, particularly in these regions of India....

The Importance of Soil Fertility Constraints in Modeling Crop Suitability Under Progressive Climate Change in Tanzania

Spatial crop suitability models are important planning tools for agricultural development, especially regarding climate change adaptation. The original version of the EcoCrop model predicts crop suitability based on monthly temperature and precipitation, without taking into account soil constraints. Recently, continuous soil property maps of Tanzania were produced (Vagen et al, submitted) based on data from systematic surveys across sub-Saharan Africa. The aim of the present study was to assess the effects of incorporating information on soil fertility constraints, such as low soil organic carbon content (SOC) into the EcoCrop model. Crop suitability maps derived with and without consideration of low SOC were compared. SOC values were extracted for 1036 locations of common bean (Phaseolus vulgaris L.) presence and the 2-percentile (0.9% SOC) was taken as a lower limit for suitability. The EcoCrop model was then run with current climate data, with and without SOC as a limiting factor, to create suitability maps. An independent spatial point dataset of registered bean presence/absence (n=1113), and regional production statistics were used for validation. The agreement between bean presence and bean suitability was higher (Cohen's unweighted kappa=0.06) when low SOC was included in the model compared to when only climate was considered (kappa=0.02). The regional statistics showed that the proportion of the area where low SOC restricted the suitability was negatively correlated with the proportion of the area planted with beans (r =-0.42, p=0.07). In summary, we identified a lower limit of SOC for the soil to be suitable for common beans production and investigated the importance of taking this soil fertility constraint into account for accurate suitability modelling. It was concluded that for more accurate suitability modelling, e.g. for decision support for adaptation to climate change, low SOC should be considered as a constraining factor.

An Assessment of the Adaptability to Climate Change of Commercially Available Maize Varieties in Zimbabwe

A study was undertaken to assess the adaptability to climate change of commercially available maize varieties in Zimbabwe using 2010, 2020, 2050 and 2080 climate change scenarios. The FAO’s Ecocrop Model was used to assess the suitability of early, short, medium and long season maize varieties grown under rainfed conditions in different agro-ecological regions (1 to 5) whose agricultural potential decreases progressively due to the amount of rainfall received. Regions 1 and 2 conditions are projected to decrease in size by 14%, region 3 by 26%, while regions 4 and 5 are projected to increase by 40%. The area suitable for growing early low yielding maize varieties will remain at nearly 100% in regions 1 and 2. The area suitable for growing medium maturing varieties will decline to below 20% in regions 4 and 5. Overall, only 2% of Zimbabwe s’ land area, mainly in region 1, will be suitable for growing high yielding late maturing maize varieties. The paper concludes that the currently available maize germplasm in the country is not suitable for the projected climate change conditions.

CLIMATE CHANGE IN THE SUBTROPICS: THE IMPACTS OF PROJECTED AVERAGES AND VARIABILITY ON BANANA PRODUCTIVITY

The potential for bananas to produce year round is best expressed when water is abundant and daily temperatures are in the range of 20-30°C. Zones with these conditions produce fruit for the global market. However, banana production, mainly for national markets, has developed in many subtropical areas under less than optimum conditions. Bananas are an important cash crop in southern Brazil, Paraguay and Argentina, in countries of North Africa, the Middle East and southern Africa, and in China and northern India. In these regions, bananas are subject to sub-optimum temperatures and short days. Highly favorable temperatures and long days in the summer may also include short periods of extreme temperatures above 35°C, while rainfall is also highly variable. The effects of climate change on selected subtropical production areas were modeled in a two-step procedure using the EcoCrop model, under current growing conditions and for 2020 and 2050 using a set of 19 IPCC (Intergovernmental Panel on Climate Change) Global Climate Models (GCMs) under the SRES-A2 (business as usual) emission scenario. The modeling showed that current suitability for banana production in the subtropics is much lower than in the tropics with great variation in suitability within the subtropics. Of nine subtropical regions considered, two have improved conditions by 2020s, four are largely unaffected and three have a lower suitability. Our analysis also showed that, in terms of environmental conditions, certain sites are widely represented globally, offering options for technology transfer between sites. Other sites have few similar sites, which means that sites need to be carefully selected for approaches to technology development and transfer. The study leveraged site-specific information with widely available tools to understand potential effects of climate change in the subtropics. However, in order to fully understand the impacts of climate change on banana, the modeling tools used here need to be fully suited for semi-perennial crops to capture the effects of seasonal temperature and rainfall variability on crop cycle length and potential yields.

Empirical approaches for assessing impacts of climate change on agriculture: The EcoCrop model and a case study with grain sorghum

Climate has been changing in the last three decades and will continue changing regardless of any mitigation strategy. Agriculture is a climate-dependent activity and hence is highly sensitive to climatic changes and climate variability. Nevertheless, there is a knowledge gap when agricultural researchers intend to assess the production of minor crops for which data or models are not available. Therefore, we integrated the current expert knowledge reported in the FAO-EcoCrop database, with the basic mechanistic model (also named EcoCrop), originally developed by Hijmans et al. (2001). We further developed the model, providing calibration and evaluation procedures. To that aim, we used sorghum (Sorghum bicolor Moench) as a case study and both calibrated EcoCrop for the sorghum crop and analyzed the impacts of the SRES-A1B 2030s climate on sorghum climatic suitability. The model performed well, with a high true positive rate (TPR) and a low false negative rate (FNR) under present conditions when assessed against national and subnational agricultural statistics (min TPR=0.967, max FNR=0.026). The model predicted high sorghum climatic suitability in areas where it grows optimally and matched the sorghum geographic distribution fairly well. Negative impacts were predicted by 2030s. Vulnerabilities in countries where sorghum cultivation is already marginal are likely (with a high degree of certainty): the western Sahel region, southern Africa, northern India, and the western coast of India are particularly vulnerable. We highlight the considerable opportunity of using EcoCrop to assess global food security issues, broad climatic constraints and regional crop-suitability shifts in the context of climate change and the possibility of coupling it with other large-area approaches.