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Climatic impacts on crop yield and its variability in Nepal: Do they vary across seasons and altitudes?
Abstract
A rapid change in climate patterns potentially driven by global warming is considered to be greatest threats to agriculture. However, little is known about how the change in climate concretely affects agricultural production especially in Nepal with respect to seasons and regions of different altitudes. To examine this issue, we seek to empirically identify the impact of climatic variation on agricultural yield and its variability by utilizing the data of rice, wheat and climate variables in the central region of Nepal. The main focus is on whether the impacts vary across seasons, altitudes and the types of crops. For this purpose, we employ a stochastic production function approach by controlling a novel set of season-wise climatic and geographical variables. The result shows that an increase in the variance of both temperature and rainfall has adverse effects on crop productions in general. On the other hand, a change in the mean levels of the temperature and rainfall induces heterogeneous impacts, which can be considered beneficial, harmful or negligible, depending on the altitudes and the kinds of crops. These results imply that adaptation strategies must be tailor-made in Nepalese agriculture, considering growing seasons, altitudes and the types of crops.
... Different crops vary in their sensitivity to global warming due to changes in temperature and precipitation. With 1 • C rise in mean air temperature, the reduction of rice yield is ranging from 6.66% to 7.2% (Krishnan et al., 2007;Poudel and Kotani, 2013), while 10% decrease in rice yield have been observed with each 1 • C increase in growing-season minimum temperature in the dry season (Peng et al., 2004a). The reduction influences from climate change to crops can also vary regionally (Hasegawa et al., 2022) and compensated by the carbon fertilizing effect (Chen et al., 2022). ...
... Models that predict crop yield influenced by climate change can be categorized into process-based crop models (Sultan et al., 2014;Koehler et al., 2013) and empirical models (Poudel and Kotani, 2013). The process models have a more detailed setup of different phases of crop growth and have better prediction performance in more granular spatial scales. ...
... It also demonstrates that a higher temperature is the most critical factor that will cause a significant yield reduction in cassava. It agrees with many previous process-based or statistical works showing that extremely high temperatures will likely reduce the crop yield (including cassava) globally and regionally (Roudier et al., 2011;Poudel and Kotani, 2013;Bellotti et al., 2012). ...
Significant shock of climate change on crop yield will challenge the performance of bio-crop on substituting fossil energy to mitigate climate change. Taking cassava-to-ethanol system in Guangxi Province of South China as an example, we coupled a random forest (RF) model with 10 Global climate models (GCMs) outputs to predict the future cassava yields. Subsequently, the net energy value (NEV) and greenhouse gas (GHG) emissions of the cassava-to-ethanol system across varied topographies are assessed using a life cycle analysis. We demonstrate that the abrupt increases in temperatures are the primary contributors to declining yields. Notably, cassava yields in hilly regions decline more than those in plains and display greater variability among concentration pathway scenarios over time. Future NEV and GHG performance of cassava-to-ethanol will undergo significant decreases over time, especially within the high concentration pathway scenario (NEV decrease 28%, GHG increase 3.4% from 2006 to 2100). The performance reductions in hilly area are exacerbated by more harvest loss and labor and material inputs during the "field-to-wheel", negating its energy advantage over fossil fuels. Therefore, adopting a lower concentration pathway and favoring plantation in plains could maintain cassava-to-ethanol as a viable climate mitigation strategy. Our research also advances the methodological approach to climate change adaptation within the domain of life cycle assessment.
... Firstly, it provides the disaggregated analysis by establishing a clear distinction about the impacts of climate change between low and high altitudes. Currently, existing literature considers nationally or regionally aggregated impacts of climate change on crop yields and their variability (see, e.g., Burke and Emerick 2016;Chen et al. 2016;McCarl et al. 2008;Poudel and Kotani 2013;Zhang et al. 2017). However, global evidence shows that the impacts of climate change on agriculture are specific to crops and locations even within a country (see, e.g., Jones and Thornton 2003;Moat et al. 2017;Rahn et al. 2018;Ray et al. 2019). ...
... In the literature, regional differences were controlled in the regression by including the dummy variables for the administrative regions (e.g. Chen et al. 2016;McCarl et al. 2008;Poudel and Kotani 2013;Zhang et al. 2017). However, there can be a difference in climate among places in each administrative region since there can be various agro-ecological situations within a region. ...
... On the other hand, our result about the effect of temperature variations on maize yield is consistent with the finding of previous literature about the impacts of climatic variables on maize production is Sub-Saharan Africa (Adisa et al. 2018;Cairns et al. 2013;Ray et al. 2019). The positive side of the nonlinear effect of temperature on the mean yield of wheat in highland areas is partly consistent with the findings of Poudel and Kotani (2013) who reported a positive relationship of temperature on the mean yield of wheat in Nepal. However, the negative sign of the coefficient of quadratic term indicates that yield starts to decrease after a certain threshold of the temperature. ...
Impacts of climate change can differ from one region to another. We combine the household-level panel data with weather and climate data to examine the heterogeneity of the impacts of climate change on crop yields across different crops and agro-ecologies in Ethiopia. Our results show that climate change will induce an increase in coffee and teff yields by 31% and 8.3%, respectively, at high altitudes by the years 2041–2060 compared to 1988–2018, under a medium emissions scenario. Conversely, it will reduce coffee yield by 3% at low altitudes, and barley, maize, and wheat yield by 22.7%, 48%, and 10%, respectively, at high altitudes. These findings suggest that tailoring agricultural development programs and climate adaptation strategies to address location and crop-specific sensitivity to climate change may help to build resilience and improve the livelihood of smallholder farmers.
... Chen et al. (2004) and McCarl et al. (2008) have used this approach to estimate the Just-Pope stochastic production function (Just and Pope, 1978) and measure the climatic impacts on U.S agriculture. Poudel and Kotani (2013) have used this approach to estimate the climatic impacts on rice and wheat yield in Nepal. This approach has a major advantage in estimating the climatic impacts on the mean and variability of crop yields. ...
... 3 Since its establishment, Odisha comprised 13 districts until the 1990s when the districts were partitioned to create a total of 30 districts. 4 Significant intra-seasonal variations in temperature and precipitation might be a consequence of climate change and has the potential to affect agricultural yields (Poudel and Kotani, 2013). 2000; Barnwal et al., 2010). ...
The relatively higher sensitivity of the agriculture sector to adverse climatic impacts poses significant challenges to the food security of developing nations, including India. While the climatic impacts on Indian agriculture are well documented, there is a dearth of research addressing the inter-regional diversities in the impacts. Furthermore, existing studies are mostly restricted to the impacts on mean agricultural yield, overlooking the impacts on yield variability. This study investigates climatic impacts on rice yield in Odisha, a coastal Indian state, employing district-level panel data from 1995 to 2017. This study uses the Feasible Generalized Least Squares (FGLS) approach to estimate the climatic impacts on the mean yield and yield variance of rice. In addition, the study uses the quantile regression method to measure how climatic impacts differ across different quantiles of rice yield distribution. Using the agro-climatic zone level dummies empowers the study to account for local weather and soil conditions. The results of the study reveal substantial heterogeneity in the climatic impacts across agro-climatic zones and conditional quantiles of rice yield distribution. The heterogeneity in climatic impacts highlights the significance of strategic and tactical adaptation measures.
JEL Classification: Q50, Q51, Q54
... The random error denoted as ϵ possesses an average value of zero and a variance of (σ 2 ). Evaluating the parameters of f(X) yields insights into the average impact of the independent variables on crop yield, while h(X) reveals their influence on the variability of crop yield [8]. Building upon the works of Chen et al. [9] and Sarker et al. [9], the production function is assessed in the following form: = ( , ) + ( , ) Panel Unit Root Test: Before proceeding with model estimation, conducting a panel unit root test for each study variable is advisable to ensure stationarity [8; 9]. In this study, the Fisher-type test was employed, and the Augmented Dicky-Fuller (ADF) test was selected due to its more reliable outcomes [10]. ...
... The random error denoted as ϵ possesses an average value of zero and a variance of (σ 2 ). Evaluating the parameters of f(X) yields insights into the average impact of the independent variables on crop yield, while h(X) reveals their influence on the variability of crop yield [8]. Building upon the works of Chen et al. [9] and Sarker et al. [9], the production function is assessed in the following form: = ( , ) + ( , ) Panel Unit Root Test: Before proceeding with model estimation, conducting a panel unit root test for each study variable is advisable to ensure stationarity [8; 9]. In this study, the Fisher-type test was employed, and the Augmented Dicky-Fuller (ADF) test was selected due to its more reliable outcomes [10]. ...
India's primary source of agricultural water is the monsoons. Because so many Indians make their living from agriculture, even the effect of climate change on monsoons, floods, and droughts will make the population much more vulnerable. We use Just & Pope's stochastic production function to evaluate how climatic conditions affect Uttar Pradesh's agricultural output probability distribution. Weather and climate affect agricultural performance. Climate change endangers its land, water, and other natural resources.
... Crop output is negatively impacted by climate change, with rapidly shifting climate patterns brought on by global warming being the biggest threat to agriculture [9] [10]. However, our understanding of the precise impacts of climate change on agricultural production remains restricted [10]. ...
... Crop output is negatively impacted by climate change, with rapidly shifting climate patterns brought on by global warming being the biggest threat to agriculture [9] [10]. However, our understanding of the precise impacts of climate change on agricultural production remains restricted [10]. Crop simulation models, commonly employed for predicting crop growth and development under different climatic conditions, face a significant challenge due to the complex non-linear relationships between crops and weather. ...
This study presents a predictive application for rice and corn crop yields in Quezon Province, Philippines, using advanced machine learning techniques, with a focus on the Gaussian Process Regression model. The desktop application utilizes weather parameters as inputs to forecast crop volumes, offering farmers valuable insights for optimized planting and harvesting decisions. Through rigorous evaluation, the Gaussian Process Regression model consistently outperforms other models, demonstrating its accuracy and potential for practical use in the agricultural sector. With an overall Mean Absolute Percentage Error (MAPE) of 3.39%, this tool holds promise for enhancing food security and sustainable agriculture while serving as a model for similar initiatives in other regions. Furthermore, this research highlights the crucial role of data-driven approaches in addressing climate change impacts on agriculture, offering a tangible solution for a more food-secure future. The study underscores the wider potential of data science and machine learning in addressing pressing global concerns, promoting more resilient and sustainable agricultural practices and ensuring a food-secure future for all.
... The theoretical background behind this approach is the plant growth or final agriculture yield that depends on several input parameters such as water, soil, economic inputs and climate variables that are employed as explanatory variables. Statistical models have been widely used in assessing the climate change impact on crop yields (Arshad et al. 2017;Lobell and Burke 2010;Poudel and Kotani 2013;Wang et al. 2014). Lobell and Burke (2010) studied the climate change effect on maize yields using 20,000 maize trials dataset in Africa. ...
... The result indicated that each degree day above 30 °C reduces the final yield by 1% and 1.7% in optimal rainfed and drought conditions. Poudel and Kotani (2013) measured climate change impacts on the rice and wheat yields in Nepal. The result indicated that a 1 °C rise in summer temperature caused the rice yield to decline by 0.10% in low altitude regions, and by 0.001% in the mid-latitude region. ...
The evidence of climate variability among developing countries has stressed agriculture sector. Promoting sustainable development will create an opportunity to enhance the rural livelihoods that are prone to frequent climate shocks. The present study estimates the climate change impact on three crop yields (Rice, Maize and Finger Millet) using fine scale climate dataset constructed at regional context for 20 districts over 21 years (1992–2012). Fixed effect panel regression method was used to examine change in crop yields to climate response. The results indicate consistently negative impact of temperature on crop yields. The regional dimension specified in the study suggested special attention for semi-arid and arid region as the magnitude of impact is significantly large.KeywordsClimate VariabilityCrop ProductivityPanel Regression Approach
... Kejadian anomali iklim seperti perubahan intensitas dan pola curah hujan, kenaikan temperatur udara, kekeringan, banjir, dan peningkatan intensitas serangan hama dan penyakit merupakan gejala perubahan iklim yang dapat berdampak pada produktivitas tanaman pertanian khususnya tanaman pangan (Suryana, 2014). Hal tersebut menjadikan perubahan iklim sebagai salah satu tantangan serius yang harus dihadapi berbagai negara di dunia dalam pemenuhan kebutuhan pangan, termasuk Indonesia (Suwarno, 2010;Syaukat, 2011;Poudel and Kotani, 2013;Shikwambana, Malaza and Shale, 2021). Fenomena perubahan iklim yang berpengaruh terhadap sektor pertanian khususnya tanaman pangan diantaranya fenomena El Nino Southern Oscillation (ENSO) (Ismail and Chan, 2019; Li et al., 2019; Sarvina and Sari, 2020). ...
... Curah hujan digunakan sebagai proxy ENSO yang didukung oleh korelasi spasial antara ONI (indikator ENSO) dengan curah hujan. Penggunaan curah hujan sebagai proxy perubahan iklim juga dilakukan oleh Syaukat, (2011); Poudel and Kotani, (2013) dan Idumah et al., (2016). Secara matematis, model yang digunakan dalam penelitian ini adalah: ...
Perubahan iklim menjadi salah satu tantangan serius yang dihadapi oleh Indonesia dalam pemenuhan kebutuhan pangan. Salah satu fenomena perubahan iklim yang berpengaruh terhadap sektor pertanian khususnya tanaman pangan adalah El Nino Southern Oscillation (ENSO) yang terdiri dari El Nino dan La Nina. ENSO menyebabkan variabilitas curah hujan sehingga berdampak buruk bagi produksi tanaman pangan seperti padi, jagung dan kedelai. Penelitian ini bertujuan untuk (1) mengidentifikasi provinsi terdampak ENSO di Indonesia dan (2) menganalisis dampak ENSO dan determinan lainnya terhadap produksi tanaman pangan (padi, jagung, kedelai) di provinsi yang terdampak. Penelitian ini menggunakan panel data sekunder tahun 2010-2017 dari 16 provinsi terdampak ENSO. Korelasi Pearson dan regresi panel statis digunakan untuk menjawab tujuan penelitian. Fenomena ENSO diproksi melalui curah hujan. Hasil penelitian menunjukkan sebagian besar provinsi di Indonesia terdampak ENSO, yang terlihat dari korelasi negatif dan signifikan antara Oceanic Nino Index (ONI) dan curah hujan. Regresi panel statis menunjukkan ENSO berpengaruh signifikan terhadap produksi padi dan kedelai melalui indikator curah hujan. El Nino yang disertai penurunan curah hujan signifikan berdampak lebih besar terhadap produksi padi dan kedelai, sedangkan La Nina yang disertai peningkatan curah hujan signifikan memiliki dampak lebih besar terhadap produksi kedelai. Secara umum, El Nino memiliki pengaruh yang lebih besar terhadap produksi tanaman pangan.
... summer is the wettest season with a monthly average rainfall of 321 mm. Altitude-wise plain receives the highest rainfall with an average of 146 mm in spring and 355 mm in the summer [64]. ...
... Everest) in the north. Also, the climate varies from artic to tropical, according to the variation in the altitude [64]. ...
In recognition of the important role of forests in the global carbon cycle, particularly with respects to mitigating carbon dioxide emissions, the ability of accurately and precisely measure the carbon sequestration in forests is increasingly gaining global attention. As being a major part of the carbon cycle, accurate quantification of the forest above ground biomass (FAGB) and net primary productivity (NPP) at local to global scales has become one of a central topic for carbon cycle researchers, foresters, land and resource managers, and politicians. In order to estimate, FAGB and NPP adequately, methodologies, such as forest inventory, remote sensing, and vegetation and carbon modeling have been successfully utilized. However, insufficiency of direct field biomass and NPP observations has severely limited the parameterization, validation, and their estimation. If satellite-derived estimations become precise, efficient and reliable it will help to estimate and monitor forest carbon information in the global forest ecosystem and play a very important role in global climate change mitigation efforts. Despite so many efforts going on, there is still a lack of proper regional and national spatiotemporal FAGB and NPP information in developing countries like Nepal. In addition, there are not many, proper area/nation specific convenient method, for their estimation, that gives a quality estimate with low cost and good replicability, especially for the developing countries. Based on these research problems and research themes, to overcome them our objectives can be broadly classified as i) develop a two-scale FAGB estimation method with the use of multi-resolution optical imageries and Google Earth Very High Resolution (GEVHR) imageries as virtual sample plots, ii.) estimation and spatiotemporal change analysis of forest cover and FAGB in different physiographic regions and forest types of Nepal and iii.) estimation and spatiotemporal trend analysis of NPP in the forest of Nepal with Boreal Ecosystem Productivity Simulator (BEPS) model over years 2000-2015.
For the development of the two-scale method of FAGB estimation, the study was conducted in Chitwan district of Nepal using GeoEye-1 (0.46 m), Landsat (30m) and GEVHR Quick Bird (0.65m) imageries. For the local scale (Kayerkhola watershed), tree crowns of the entire area were delineated by object-based image analysis (OBIA) technique on GeoEye imageries. The overall accuracy of 83% was obtained in the delineation of tree canopy cover (TCC) plot-1. A TCC vs. FAGB model was developed based on TCC from GeoEye and FAGB from field sample plots. The coefficient of determination (R2) of 0.76 was obtained in themodeling and 0.83 in the validation of the model. To upscale FAGB to the whole district, open source GEVHR imageries were used as virtual field plots, delineated their TCC and then calculated it’s, FAGB (based on TCC vs. FAGB model). Using Multivariate Adaptive Regression Splines (MARS) machine learning algorithm, model was developed from Landsat 8 bands and vegetation indices. It was then used to extrapolate FAGB in the entire district. This approach considerably reduces field data and commercial very high resolution imageries requirements to achieve two scale forest information and FAGB estimate at high resolution (30m) and accuracy (R2=0.76 & 0.7) with minimal error (RMSE=64 & 38 tons ha-1) at both local and regional scales. The proposed methodology can be one of the promising techniques for the FAGB and carbon estimation in a very cost-efficient way and can be replicated with limited resources and time. It is especially applicable for developing countries with a low budget for carbon estimation and it is very much applicable to the “reducing emissions from deforestation and forest degradation” (REDD+) and “monitoring reporting and verification” (MRV) processes.
In the case of estimation and spatiotemporal analysis of forest cover and FAGB, here, we present so far first national scale forest cover type and FAGB study along with TCC of Nepal at 30m resolution for the year of 2000, 2010 and 2015. With the integrated used of Landsat imageries, field sample plots and Google earth imageries the forest cover type and FAGB of Nepal was estimated. A good overall accuracy of 87% with Kappa statistics of 0.89 was obtained for the forest cover type, classification with OBIA. Similarly, the estimation of FAGB with multiple linear regression was significant enough with aggregate R2 of 0.7 and RMSE 98 tons ha-1 at P<0.001for the year 2010. For the FAGB estimation for the year of 2000 and 2015, the FAGB vs. TCC model with aggregate R2 of 0.8 was used over the TCC estimated for them. The overall forest area of Nepal is found to be gradually increasing from 37.9% of the total area in 2000 to 40.2% in 2010 and 42.8% in 2015. Also, the FAGB was increased from 911million tons in 2000 to 1102 million tons in 2010 and 1109 million tons in 2015. The Broad-leaved closed forest (BLCF), was found to play major role, in terms of total FAGB contribution (47%, 47% and 50% of total contribution for years 2000, 2010 and 2015), forest area occupancy (37%, 36% and 38% of total forest for years 2000, 2010 and 2015), and FAGB productivity (214, 242 and 240 tons ha-1 for 2000, 2010 and 2015). In terms of physiographic region, the plain area was found to produce more FAGB (36%, 42% and 39% of the total FAGB for 2000, 2010 and 2015) although the forest area coverage by it was the least (29%, 30% and 27% of total forest for 2000, 2010 and2015) among the threephysiographic regions. The resulting nationwide wall-to-wall FAGB maps will help to improve the accuracy of carbon dynamic prediction in Nepal. It has huge importance to support diverse issues of environmental conservation. The data has big potential use for national and regional level sustainable land use planning strategies and meeting several global commitments.
In our study, we also aimed to understand the temporal and spatial variations of NPP in the forest of Nepal. The daily, monthly and annual NPP of the forest was estimated using the BEPS model for the years 2000-2015. The Leaf area index (LAI), meteorological datasets and other parameters as soil data, tree cover, biomass, field capacity, and wilting points were the main input for the BEPS model. We found that the NPP value varied spatially and temporally across the whole forest, which is increasing in general, though there were fluctuations in some years. The average daily NPP over the entire study period ranged from 1.3 to 1.7 gm m-2day-1 with highest in years 2014 and lowest in the year 2000 and overall average NPP trend of 1.65 gm m-2day-1. Within the overall forest, the average NPP productivity is generally highest in the plain followed by the hill and least in the mountain physiographical region. Looking at the intra-annual variability, the average monthly NPP ranged from 4.1 to 7.1 kg m-2month-1 with an average of 6.2 kg m-2month-1. The highest NPP rates were generally in the months of October and then May and the lowest in December and January. Mean seasonal NPP is largest during post-monsoon and lowest during the winter period, thereby indicating the importance of soil moisture and solar radiation for vegetation productivity. The average annual NPP is 1.2 kg m-2year-1 and the total average of 19 kg m-2. NPP was found to be highly influenced by LAI, rainfall, solar radiation and temperature mostly positively correlated in overall. The NPP was found to be highly correlated with the LAI especially in the plain region over the years from 2000-2015. In addition, while looking at the variation of NPP on different forest types, the broad-leaved forest was found to have almost 1.7 times more NPP (1.97 gm m-2day-1) than that of needle leaved forest (NPP 1.18 gm m-2day-1). We also found that the slope percent of <15% is more favorable (NPP 2.15 gm m-2day-1) for higher NPP among different slope percent. The result from this study gives us important information on intra and inter annual spatiotemporal trend and variability of NPP in the forest of Nepal overall and in different physiographic regions. It also gives us information on the relation between NPP and various climatic and vegetation parameters. All these information are very important for the proper forest ecosystem monitoring, management, and planning operations.
VII
Keywords: Forest above ground biomass, Forest cover change, Net primary productivity, Spatio-temporal dynamics, Change analysis
... empirical studies on the impacts of climate change on agriculture from around the world. The available studies in this regard have by and large focused on the developed countries (Mendelsohn et al., 1994;Lewandrowski and Schimmelpfennig, 1999;Bryant et al. 2000) though relatively a few studies on developing countries have become available by now (Guiteras, 2009;Sarker et al., 2012;Poudel and Kotani, 2013;Burney and Ramanathan 2014;Singh et al., 2017;Nath and Mandal 2018). ...
... Hence, estimation of this production function helps to find out the impact on output and its variability simultaneously. This approach has been used by researchers like Chen et al. (2004), Isik andDevadoss (2006), McCarl et al. (2008), Cabas et al. (2010), Poudel and Kotani (2013), and Guntukula and Goyari (2020). ...
Brinjal also known as Eggplant is the second most important solanaceous crop after tomato. This
study was a modest attempt to estimate the area under cultivation of brinjal in Karnataka and also to
estimate the demand for brinjal seedlings during 2019-20. In addition, this study has also tried to work out
the economic feasibility of investment on nursery under shade net condition. The results indicated that the
area under brinjal cultivation was estimated to be 17238 hectares and the demand for brinjal seedlings
worked out to 23.94 crores in the state of Karnataka for the year 2019-20. The capital budgeting technique
indicated that, the nursery entrepreneurs had invested 2,59,735/- towards setting up of nursery in an area
of 1000m2
under shade net. Further the economic analysis pointed out that entrepreneurs have realised
gross income of 2,74,540/- and net returns of 62,608/- per crop rotation The capital investment on
brinjal nursery was found to be economically viable in terms of net present worth ( 1,21,723), benefit-
cost ratio (1.30) and Internal Rate of Return (89 per cent).
Keywords: Brinjal, Cultivation, Nursery, Demand, Feasibility, Enterprise profit.
... For instance, Cabas et al. (2009) found that increases in both temperature and rainfall variability harm crop production in Nepal and Canada, while temperature variability has been found to have a negative effect on key crops in the US (McCarl et al., 2008). Changes in mean and growing season temperature and rainfall induce heterogeneous impacts, which can be regarded as harmful, beneficial or even negligible, depending on altitude and type of crop (Poudel & Kotani, 2013). ...
Recent scientific literature shows that in many developing countries, variability in rainfall and temperature in growing season has detrimental effects on agricultural output, especially when the variability is high. It is yet unclear to what extent or threshold these variations impair the agricultural productivity in some parts of Africa. In this study, we answer this research question using a dynamic panel threshold model on a panel dataset of East African countries for the period 1961–2020. We incorporate climate variables disaggregated into growing and non-growing seasons. The empirical results indicate that growing rainfall variability has significant effects on agricultural output. More specifically, we found a significant negative effect from rainfall variability in spring and summer, when precipitation variability exceeds thresholds of −0.533 mL and −0.902 mL respectively. However, these effects are indistinguishable from zero in fall season. Regarding a growing-season temperature variability, we found no significant effects across seasons. Policy implications are discussed.
... This apparent contradiction can be explained by the different roles these factors play in vegetation growth. Temperature often controls the extent of the growing period, especially in colder climates (Poudel & Kotani, 2013). A warmer year can lead to a prior initiation of the growing period and an advanced culmination, resulting in a higher annual NDVI (Yu et al., 2023). ...
Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann–Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson’s correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year⁻¹, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.
... The implication of increased temperature adversely affects the yield of major crops, including rice, wheat and maize (Howden et al., 2007;Lobell et al., 2012;Lobell et al., 2013). Further increases in temperatures are expected to reduce the yield of rice, wheat and maize in Tarai, Nepal because the temperature has reached maximum threshold levels of rice and wheat (Karna, 2014;Poudel & Kotani, 2013). ...
Climate change perceptions of Indigenous peoples (IP) are important because of their close connection with nature and the environment. This study assesses climate change insights of the Tharu in Bardiya district of Nepal in relation to climate variability and water sector-related hazards, focussing on Indigenous knowledge (IK) for adaptation and mitigation in agriculture. Tharu are the first settlers in Tarai, Nepal and largely depend on farming. Our sequential mixed-method approach first quantifies perceptions and then analyses qualitative information from participatory methods. We found the Tharu have perceived a temperature increase but a rainfall decrease; the former is validated with weather data, but not the rainfall trend due to high annual variation. The high ranking of flooding in both villages and drought in Bikri indicates the importance of the water sector and related hazards. Tharu have used Indigenous as well as scientific knowledge for weather predictions, coping and adaptation to water-related hazards in agriculture-based livelihoods. As the application of IK-based traditional agricultural practices has decreased due to their lower yield than modern agricultural practices, there is need for documentation, research and policy actions to integrate IK and science to reduce climatic vulnerability and increase productivity of resilient agricultural practices. ARTICLE HISTORY
... Furthermore, exceeding 29.9 C during the daytime maxima leads to a decline in rice productivity (Karn, 2014;Olufemi et al., 2020). The alteration of rainfall has a notable impact on the area under rice cultivation in Nepal (Poudel and Kotani, 2013;Chandio et al., 2021;Rayamajhee et al., 2021). More than 50 thousand hectares of rice-growing area were affected by erratic rainfall from 2013 to 2014 (Khadka et al., 2020;Regmi, 2020) and nearly 127 thousand hectares of land faced natural calamities from 2017 to 2018 (Chaudhary et al., 2020;Upendram et al., 2023). ...
The rice seed sub-sector plays a vital role in the self-sufficiency of rice grain and food security in the context of changing climate. Thus, it is imperative to understand the perception of rice seed growers towards climate change and identify the major adaptation strategies against climate change along with their significant determinants. In this light, our study used data from 223 rice seed growers in the Chitwan district of Nepal using purposive sampling followed by simple random sampling from Bharatpur Metropolitan City and Madi Municipality. Descriptive statistics were used to illustrate perception and adaptation strategies. The growers were categorized as adopters or non-adopters of strategies using the adoption index. Probit regression was used to determine the significant determinants of the adoption of strategies. The findings revealed that 71% of growers perceived climate change: increased temperature and decreased frequency of rainfall. Varietal selection, green manuring, planting time, improved water management and nutrient management were the major adaptation strategies adopted in the study area. From the regression analysis, years of formal education, experience, contact with extension agents and training were found to be significant determinants of the adoption of strategies. The farmers of Madi were found to be more likely to adopt the adaptation strategies. It is therefore recommended that the local and provincial-level governments explore the institutional service provision system and socioeconomic characteristics while considering the location for better farm-level adoption of strategies. The study is useful for poli-cymakers to deliberately target formal education, extension services and training for increased adoption of adaptation strategies in the face of climate change. The identified adaptation strategies and their significant determinants are applicable for the rice seed farming system in similar agro-ecological regions globally.
... Wheat cultivation has been a longstanding practice in Nepal, in various regions such as Terai, river basins, mid-hills, and high hills, occurring in the winter season from October to July. Though it is cultivated as a winter crop, differences in geography and topography makes the sowing period of wheat differ in different portions of the country (Poudel, 2013). It is produced on 0.70 million hectares of land in the country yielding about 2.2 million metric tons with a productivity of 3.08 Mt ha -1 (MoALD, 2020). ...
A field experiment was conducted at the Agronomy farm of Nepal Agricultural Research Council (NARC), Khumaltar, Lalitpur to evaluate the effect of sowing dates and seed rates on yield and yield attributes of wheat. The experiment was laid in a split-plot design with three replications treated with 4 sowing dates as the main plot factor (12 th Nov, 27 th Nov, 12 th Dec, and 27 th Dec) and 4 seed rates as subplot factor (100 kg ha-1 , 120 kg ha-1 , 140 kg ha-1 and 160 kg ha-1). Results revealed that the leaf area index was significantly affected by sowing dates and was comparatively superior in 2 nd sowing date (27 th Nov) wheat. Similarly, in the case of seed rates, the leaf area index was influenced significantly and was recorded to be increasing with an increase in seed rates. Phenological parameters like days to 50% heading, flowering, and maturity were observed maximum (116, 123, and 179 days, respectively) in early sown wheat and reduced with the subsequent delay in sowing. Maximum values of yield and yield attributes like effective tillers per meter square (635.6), spike length (9.56 cm), grains per spike (41.49), grain yield (7.59 Mt ha-1), and straw yield (9.58 Mt ha-1) were observed in the wheat sown in 2 nd date (on 27 th Nov) which differed significantly to wheat sown on other dates. Seed rates had no significant influence on grain yield and yield attributes. Thousand-grain weight was found maximum (46.26 g) in early sown wheat (on 12 th Nov sown wheat, reduced with the subsequent delay in sowing, and the harvest index was observed as maximum (0.51) under December 27 sown wheat. Though the yield and its attributes were not influenced significantly by seed rate, the maximum yield (6.18 Mt ha-1) was observed in wheat sown at the rate of 120 kg ha-1. Considering seed yield and its parameters, 2 nd date of sowing wheat (27 th Nov) and seed rate of 100 kg ha-1 could be the best option to uplift the productivity of wheat in rainfed lowland conditions of Lalitpur, Nepal.
... Earlier studies (e.g. McCarl et al., 2008;Poudel & Kotani, 2013) used the mean-variance analysis developed by Just and Pope (1978) to examine the impacts of weather variables on yield variability. A key finding is that about one-third of yield variability can be attributed to global climate variability (Ray et al., 2015). ...
Stable agricultural production has been substantially challenged by increasingly frequent calamitous weather conditions. For winter wheat, continuous precipitation during the harvest season is particularly detrimental. This study utilises a county‐level panel dataset of agricultural production in China for the period of 1998–2016 to evaluate the impact of continuous precipitation on the downside risk of winter wheat yield. Results show that the continuous precipitation during the harvest season remarkably increases the downside risk of winter wheat yield. At the same time, the progressive adoption of harvest machinery in recent decades has effectively mitigated the downside risk of winter wheat yield driven by continuous precipitation. The mitigation effects of harvest mechanisation are more pronounced for plain areas with better‐developed transportation infrastructure.
... While rainfall variability is capable of influencing maize yield, many of these studies reported that temperature is capable of contributingto changes in yield of approximately 50%; relative humidity can increase yields when it is high throughout the growing season Bogale et al., 2022;Odekunle et al., 2007). Previous work shows that prolonged dry spells combined with high temperatures are likely to have a significant impact on yield Bogale et al., 2022;Jägermeyr et al., 2021;Odekunle et al., 2007;Poudel and Kotani, 2013), particularly for cassava. Cassava yields are affected by several factors, though, including the amount of rainfall at the start and end of the growing season, but also fertiliser use, and resistance to pests/mildew, such as nematode moulds (Adiele et al., 2020;De Bauw et al., 2021;Onasanya et al., 2021). ...
... The fixed effects estimators in panel data models rely on variations in weather across time within a spatial unit (i.e. district) to find the influence of weather parameters on the crops yield (Chen, McCarl, and Schimmelpfennig 2004;Deschênes and Greenstone 2007;Kim and Pang 2009;McCarl, Villavicencio, and Wu 2008;Poudel and Kotani 2013;Schlenker and Roberts 2006). In the Indian context, empirical studies relied on this approach to assess the influence of historical weather change on crops yield (e.g. ...
The study analyzed the historical functional relationship between weather change and crops yield in Telangana state. This study uses 42 years of district-level data of three crops-viz., rice, maize, and groundnut. The estimated Panel-Corrected Standard Error (PCSE) model results found that the impact of weather variables on crop yield are season specific and varies across crops in Telangana. In both Kharif and Rabi seasons, crop yields are more sensitive to average maximum temperature (TMax), average minimum temperature (TMin), and rainfall variables. Non-weather variables, including fertilizer, irrigation, and labor, significantly influence crop yield in the state and play a role in neutralizing the effects of weather variables. Further, the influence of weather-related variables on crop yield differs on different growth phases of the crops across seasons in Telangana. The study findings clarify the idiosyncratic climatic impacts on agriculture in Telangana and call for location and season-specific adaptation policies to minimize future climatic stress.
... Farmers in mountainous or hilly agro-ecological zones (AEZs) face several challenges, including adverse climatic conditions, limited opportunities for income diversification and limited access to financial resources. As a result, they face greater difficulties in adapting to climate change, as predicted and explained by intersectionality theory.Similar studies, particularly in Nepal, such as byPoudel and Kotani (2013),Merrey et al. (2018),Thapa and Hussain (2021), also reported that CCA strategies in Nepalese agriculture should be tailored based on the AEZs. ...
Nepal is one of the most vulnerable countries to climate change, which is negatively affecting agricultural production and food security. However, the role of agro-ecological zones and social groups in climate change adaptation (CCA) and its impact on smallholder farmers in Nepal remains unexplored. To fill this gap, this study aimed to identify the effect of agro-ecological zones and social groups on smallholder farmers' adaptation to climate change using the multivariate probit model. Multistage sampling was used to collect data from 400 households in three agro-ecological zones of Nepal. These zones were highland (mountainous region), midland (hilly region) and lowland (terai/plain region). The results of our study showed that farmers in the Mountain region are more likely to adopt off-farm activities and temporary migration as a CCA strategy than those in the Terai/plain agro-ecological zone. In the Terai/Plain, farmers mainly adopt small-scale irrigation and agroforestry. In terms of social groups, the Brahmin group was more likely to adopt new crop varieties and small-scale irrigation than the Sudra group. The Sudra farmers preferred temporary migration and off-farm activities more than the Brahmins. Our study shows that policies to promote the adoption of CCA strategies need to take into account location and social group differences in order to improve the adaptive capacity of the most vulnerable farmers. Mountain and Sudra farmers need support to adapt to climate change and sustain agriculture. K E Y W O R D S agro-ecological zones, climate change, multivariate probit model, social groups, sustainable development
... Hence, Guntukula and Goyari's (2020) findings confirm that climate variability affects the yields of seasonal crops differently. In addition, Poudel and Kotani's (2013) results have supported that changes in temperature and rainfall affect crop productivity differently depending on the crop species and cultivated areas. Based on the analysis of temperature and total rainfall changes, the projection of energy crop productivity reveals that the greatest positive effect will be on oil palm productivity, followed by cassava, when the temperature rises above the average level. ...
In recent years, biofuels have played an important role in the economic development of Thailand as a clean and environmentally-friendly source of energy that can be produced in the agricultural sector. Thailand has particularly high efficiency in energy crop production, making the country a valuable reserve energy source. The main purpose of this study is to examine the potential impact of climate change on energy crop productivity in Thailand, specifically for sugarcane, cassava, and oil palm, using panel data analysis from 1995 to 2020 at the provincial level throughout the country. The expected yield and variance of the yield are estimated using Just and Pope’s procedure. The empirical results reveal that temperature and rainfall have different effects on the efficiency of energy crop production. The estimated potential impact indicates that higher temperatures above the average level affect energy crop productivity more than rainfall changes in different directions. The findings conclude that in order to maximize domestic energy crop productivity, it is necessary to prepare the cultivation areas to suit the local climate and weather conditions.
... Summary of serial correlation results of rainfall and temperature data during Rabi season Pre-estimation specification tests: Prior to applying the data for Just-Pope model, the data on climate change variables and yields of chickpea are examined for stationarity by employing the ADF-Fisher-type, LLC test and Harris-Tzavalis test(Poudel and Kotani, 2013; ...
Farmers usually do not know the precise output that is affected by climatic factors such as temperature and rainfall and are characterized by inter-annual variability, part of which is caused by global climate change. No study covers the influences of climate factors on yield and yield risk in the context of chickpea farming in Andhra Pradesh, India. In this context, this study aimed to investigate the trends in climate change variables during Rabi season (October to January, 1996-2020) and evaluated their variability on chickpea yields across different agro-climatic zones in Andhra Pradesh by employing Just and Pope production function. Four non-parametric methods-Alexandersson’s Standard Normal Homogeneity Test, Buishand’s Range Test, Pettitt’s Test and Von Neumann’s Ratio Test are applied to detect homogeneity in the data. Mann–Kendall (MK) test and Sen’s slope (SS) method were employed to analyze monthly rainfall trends and minimum and maximum temperature trends. Results of Just and Pope (panel data) quadratic and Cobb-Douglas methods revealed that monthly minimum temperature positively influenced the mean yield of chickpea (0.22% and 0.16%, respectively). However, rainfall (-0.41% and -0.31%) and maximum temperature (-0.08% and -0.04%) negatively influenced the mean yield of chickpea under quadratic and Cobb-Douglas models, respectively. Accordingly, rainfall (0.08% and 0.06%) and maximum temperature (0.83% and 0.72%) positively influenced the yield variability and minimum temperature (-0.77% and -0.67%) reduced yield variability of chickpea under quadratic and Cobb-Douglas models respectively. In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh.
... In this study area, among various impacts of climate change, agricultural productivity reduction is one of the most significant issues. Poudel and Kotani (2013) claim that the increase in the variance of temperature and changes in rainfall patterns adversely impact the production of crops in general. Similarly, uncertain agricultural production patterns, reportedly caused by drought and reduced rainfall, result in a massive reductions in production (Sapkota et al. 2010;Gentle and Maraseni 2012;Gentle et al. 2014). ...
The impacts of climate change are widespread, making watershed areas and watershed-dependent communities particularly vulnerable. The impact is more significant in developing countries where locals rely on watershed resources for their livelihoods. We examine the impacts of climate change and local peoples’ adaptation strategies in Begnas and Rupa watersheds in western Nepal. Using a mixed method approach we collect primary data including questionnaire surveys, field observations, key informant interviews, and focus group discussions. Our results reveal that the temperature around Begnas and Rupa watersheds has been increasing for the last 30 years while precipitation has both been decreasing and becoming more erratic. These fluctuations and anthropogenic activities impact agricultural productivity, degrade ecosystems, and reduce socioeconomic status. Local people use several adaptation strategies in response, including improved seeds, changing cropping patterns, cleaning invasive species in wetlands, constructing irrigation canals, diversifying income-generating activities, and launching sensitization and awareness campaigns. To support climate change adaptation, we recommend that the local government focus on participatory-based planning as well as mainstreaming climate change adaptation in the planning process.
... (Malla, 2008) states higher temperature reduces rice yield in the tropical region and rise of temperature by 4°C reduces the crop yield by 3.4%. Rice crop is more vulnerable to climate change in comparison to wheat (Poudel and Kotani, 2013). Numerous studies on the impact of climate change on rice have been conducted in Nepal by (Karn, 2014) (Malla, 2008) (Regmi, 2007) (Adhikari et al., 2017) but controlled experiment focusing the impact of elevated temperature on rice is limited . ...
... (Malla, 2008) states higher temperature reduces rice yield in the tropical region and rise of temperature by 4°C reduces the crop yield by 3.4%. Rice crop is more vulnerable to climate change in comparison to wheat (Poudel and Kotani, 2013). Numerous studies on the impact of climate change on rice have been conducted in Nepal by (Karn, 2014) (Malla, 2008) (Regmi, 2007) (Adhikari et al., 2017) but controlled experiment focusing the impact of elevated temperature on rice is limited . ...
... The variability in rainfall intensity has a direct negative effect on crop productivity (Nciizah and Wakindiki 2014). This finding is in line with the study of Poudel and Kotani (2013), which found that variability of rainfall generally has adverse impacts on crop productivity, consistent with the Weersink et al.'s (2010) results, which found that variation in seasonal rainfall has a negative effect to the yields of corn, soybean, and winter wheat. Hence, the rainfall intensity ultimately affects the income of the agricultural sector indirectly. ...
This study estimates the impact of climate change on the economic growth of the agricultural sector and its variability using a panel dataset from 1995 to 2019 for 76 provinces in Thailand. The panel data analysis consists of unit root tests for identifying stationary characteristics, autoregressive distributed lag (ARDL) bounds for analyzing cointegration, and pool mean group (PMG) estimation for detecting long-run and short-run effects. The cointegration results indicate the existence of long-run equilibrium in the agricultural economy and its variability to climatic and non-climatic variables. Results from the PMG estimation suggest that extreme weather events have a negative impact on the agricultural economy, but increased total rainfall has a positive association with the agricultural economy. The increases in mean average and mean minimum temperatures will reduce the variability of agricultural growth. The obtained results suggest that the productivity of agricultural households and water resources increases the agricultural revenue and reduces its variability for long-term development in the agricultural sector of Thailand.
... Upland rice neither produces nor emits CH 4 [1]. According to Poudel and Kotani [3] rice crop is more vulnerable to climatic events in comparison to wheat resulting in reduced rice yield in the tropics, while rice crops which were mainly produced in the tropics can now be grown in high altitude [4]. Nepal experiences adverse impact of climate change every year despite its negligible contribution to greenhouse gas emission [5] which could lead to the extinction of aromatic crop varieties like Basmati rice [6]. ...
Open top chamber system was designed for undertaking research into rice crop response to increased temperature during the rainy season at Regional Agricultural Research Station (RARS), Khajura, Banke in 2018. With the objective of determining the efficacy of the chamber system and to generate possible differences in climate which could alter plant response between ambient and chamber system, 5 different rice varieties (Radha-4, Sukhkhadhan-3, Sukhkhadhan-2, IR83383-G-B-141-1 and IR87751-20-4-4-2) with three temperature conditions were used: ambient condition, an open-top chamber with 1.2m height enclosed from the base with plastic sheet and open-top chamber with 1.5 m height enclosed from the base with a plastic sheet. With 3.1⁰C higher temperature Sukkhadhan-2 produced higher (p < 0.05) grain yield 4.33 t/ha under chamber condition in contrast to open field (2.93 t/ha) as well as higher (p < 0.05) biomass yield 13.62 t/ha under elevated temperature. Also, Sukhkhadhan-2 attained (p < 0.01) maximum height (87 cm) under chamber conditions compared to open field (73 cm) during harvest. Sukhkhadhan-3 showed (p < 0.05) a longer panicle length (26 cm) under chamber than normal field condition (24 cm). The Radha-4 variety produced (p < 0.05) more filled grains per panicle (169) under chamber conditions than ambient conditions (112). The consideration of crop variety is a good adoption measure to minimize the incidence of elevated temperature in the farming system.
... Water stress as a result of the decrease in humidity, intense light, and strong winds, can cause average granule size to decrease in wheat, affecting the crop's overall yield (Hurkman & Wood, 2011). If the temperature of the atmosphere rises, the temperature of the leaf surface rises as well, impacting primary production (Poudel & Kotani, 2013). Heat stress causes starch quality to deteriorate in maize, granule size to shrink, branch chains to shorten, and yield to drop (Wang & Frei, 2011). ...
Climate change has emerged as a major man-made global environmental problem, characterized by an increase in the earth's air temperature as a result of large-scale emissions of greenhouse gases. Agriculture and climate change are intrinsically linked in different ways, since biotic and abiotic stresses are primarily caused by climate change, all these factors have a detrimental effect on a region's agriculture. Agriculture is affected by climate change in various ways, e.g., heat stress at the reproductive stage, shortening of growing season length, pests or microbes, modification in weeds, and increase in CO2 level. The challenge of changing global climate has driven the scientists' interest, As a result of these changes, global crop production is suffering and global food security is in danger. The current study sheds light on the impacts of climate change on agriculture, as well as the consequences for food security.
... Water stress as a result of the decrease in humidity, intense light, and strong winds, can cause average granule size to decrease in wheat, affecting the crop's overall yield (Hurkman & Wood, 2011). If the temperature of the atmosphere rises, the temperature of the leaf surface rises as well, impacting primary production (Poudel & Kotani, 2013). Heat stress causes starch quality to deteriorate in maize, granule size to shrink, branch chains to shorten, and yield to drop (Wang & Frei, 2011). ...
Climate change has emerged as a major man-made global environmental problem, characterized by an increase in the earth's air temperature as a result of large-scale emissions of greenhouse gases. Agriculture and climate change are intrinsically linked in different ways, since biotic and abiotic stresses are primarily caused by climate change, all these factors have a detrimental effect on a region's agriculture. Agriculture is affected by climate change in various ways, e.g., heat stress at the reproductive stage, shortening of growing season length, pests or microbes, modification in weeds, and increase in CO2 level. The challenge of changing global climate has driven the scientists' interest, As a result of these changes, global crop production is suffering and global food security is in danger. The current study sheds light on the impacts of climate change on agriculture, as well as the consequences for food security.
... First, it is based on crop growth simulation models [15][16][17]. Second, micro econometric models such as the production function approach model [18][19][20] or the Ricardian model [21][22][23][24] are used. ...
Vietnam is located in the tropical monsoon region and it often faces many types of extreme weather events, especially storms and droughts. In addition to the effect of climate change, extreme weather events have been becoming more complicated and difficult to predict, causing heavy losses to many areas and economic sectors of the country. These problems impose a great threat to the country to achieve its socioeconomic targets and sustainable development goals. This study uses a Riparian approach integrated with two-stage Hsiao method using a panel dataset from 2000-2018 to examine the impact of extreme weather events and climate change on the output of agriculture and fishery enterprises in the Central and Central Highlands regions of Vietnam. Findings from the study indicate that extreme weather events and climate change have a negative impact on agriculture and fishery enterprises in the regions. Specifically, the model results show that the value-added loss to agriculture and fishery enterprises as the impact of extreme weather events and climate change may escalate from billion VND 3597.72 to 18,891.2 under different climate change scenarios. The results also indicate the impact of various factors regarding extreme weather events and climate change on the efficiency of enterprises in the study area. Findings from this study provide insights on the impacts of extreme weather events and climate change on value-added of enterprises in the study regions and help to propose appropriate solutions to adapt and mitigate their impacts in the future.
... This study presented that an increase in the variability of temperature and rainfall decreased crop yields and an upsurge in its variability. Similarly, Poudel and Kotani (2013) empirically explored the effect of climatic variation on the yield and yield variability of rice and wheat in Nepal during 1990Nepal during -2006. The primary focus of the authors was on whether the effects of climate vary across a variety of crops, seasons and altitudes. ...
Purpose
This paper aims to evaluate the effects of climate variables on the mean yield and yield variability of major pulse crops in the Telangana state of India.
Design/methodology/approach
Authors have estimated the Just and Pope (1978, 1979) production function using panel data at the district level of four major pulses in nine former districts of Telangana for 36 years during 1980–2015. A three-stage feasible generalized least squares estimation procedure has been followed. The mean yield and yield variance functions have been estimated individually for each of these study crops, namely, Bengal gram, green gram, red gram and horse gram.
Findings
Results have shown that changes in climatic factors such as rainfall and temperature have significant influences on the mean yield levels and yield variance of pulses. The maximum temperature is observed to have a significant adverse impact on the mean yield of a majority of pulses, and it is also a risk-enhancing factor for a majority of pulses except horse gram. However, the minimum temperature is positively related to the mean yields of the study crops except for Bengal gram, and it is having a risk-reducing impact for a majority of study crops. Rainfall is observed to have a negative impact on the mean yields of all pulses, but it is a risk-enhancing factor for only one crop, i.e. Bengal gram. Thus, rising temperatures and excess rainfall are not favorable to the productivity of pulses in study districts.
Research limitations/implications
The present study is based on the secondary data at the district level and is considering only one state. Season-wise primary data, including farm-specific characteristics, could have been better. The projected climate change and its impact on the mean yields and yield variance of pulses need to be considered in a future study.
Originality/value
According to the best of our knowledge, this is the first study to empirically evaluate the impact of climatic variables on the mean yields and yield variability of major pulses in Telangana using a panel data for major pulses and nine districts of 36 years time-series during 1980–2015. The study has given useful policy recommendations.
... In summary, several studies account for the impact of climate change on the agricultural sector in developed countries (Terjung et al., 1984;Warrick, 1984;Easterling et al., 1993;Deschênes & Greenstone, 2007), and in developing countries (Turpie et al., 2002;Isik & Devadoss, 2006;Poudel & Kotani, 2013). Though most of these studies have used the production function approach and the stochastic production function approach to measure the impact of climate change on agriculture and the risk of the changing climate on crop yield (see also Chang, 2002;Schlenker et al., 2006;Isik & Devadoss, 2006;Deschênes & Greenstone, 2007), higher moments of the stochastic production function have not been considered explicitly. ...
... Burke & Emerick, 2016;Butler & Huybers, 2013;Chen et al., 2016;Schlenker & Roberts, 2008;Zhang et al., 2017), and its variability (e.g. Carew, 2017;Carew et al., 2009;Chen et al., 2004;Isik & Devadoss, 2006;McCarl et al., 2008;Poudel & Kotani, 2013). Yet there are evidences for crop-and location-differentiated impacts of climate change on agriculture, which calls for analysis of heterogeneities in key dimensions (see e.g. ...
This doctoral thesis consists of four papers focusing on the heterogeneity and uncertainty in climate policy and agricultural development. The first paper illustrates differences in spouses’ perception of climatic risks and their effect on household’s adoption of climate change adaptation in sub-Saharan Africa. In Kenya, female spouses’ perception of climatic risks increases the household’s likelihood of adopting climate adaptation strategies. The adoption of crop-based strategies for climate change adaptation is positively associated with both female and male spouses’ perceptions of climatic risks in Uganda and Tanzania. While both spouses' climatic risk perceptions have positive associations with livestock-based strategies in Uganda, the association with females’ perception is negative in Tanzania. The second paper assesses how the impacts of climate change vary across crops and agroecosystems in Ethiopia. The empirical results show that climate change will increase coffee and teff yields at high altitudes while it will decrease coffee yield at low altitudes, and barley, maize, and wheat yield at high altitudes by 2060. The third paper provides a systematic review of literature that uses a real-options approach for the analysis of investment in climate adaptation and mitigation actions. The review shows the need for future research incorporating climate uncertainty, risk preferences, and decision-makers’ strategic interactions. The fourth paper models farmers’ opportunity to relocate coffee farms to higher altitudes in Ethiopia as a climate adaptation strategy. The results illustrate how the uncertainty in net returns and high establishment costs may induce farmers to postpone their adaptation actions. The papers presented in this thesis point to the need to take into account the differences in individual behaviours, vulnerabilities and uncertainties in designing climate and development policies.
... Upland rice neither produces nor emits CH 4 because it is never flooded for a significant period [1]. According to Poudel and Kotani [3] rice crop is more vulnerable to climatic events in comparison to wheat resulting in reduced rice yield in the tropics, while rice yield may be benefitted in the temperate region. Rice and other crops which were mainly produced in the tropics can now be grown in high altitude [4]. ...
... The implication of increased temperature adversely affects the yield of major crops, including rice, wheat and maize (Howden et al., 2007;Lobell et al., 2012;Lobell et al., 2013). Further increases in temperatures are expected to reduce the yield of rice, wheat and maize in Tarai, Nepal because the temperature has reached maximum threshold levels of rice and wheat (Karna, 2014;Poudel & Kotani, 2013). ...
Climate change perceptions of Indigenous peoples (IP) are important because of their close connection with nature and the environment. This study assesses climate change insights of the Tharu in Bardiya district of Nepal in relation to climate variability and water sector-related hazards, focussing on Indigenous knowledge (IK) for adaptation and mitigation in agriculture. Tharu are the first settlers in Tarai, Nepal and largely depend on farming. Our sequential mixed-method approach first quantifies perceptions and then analyses qualitative information from participatory methods. We found the Tharu have perceived a temperature increase but a rainfall decrease; the former is validated with weather data, but not the rainfall trend due to high annual variation. The high ranking of flooding in both villages and drought in Bikri indicates the importance of the water sector and related hazards. Tharu have used Indigenous as well as scientific knowledge for weather predictions, coping and adaptation to water-related hazards in agriculture-based livelihoods. As the application of IK-based traditional agricultural practices has decreased due to their lower yield than modern agricultural practices, there is need for documentation, research and policy actions to integrate IK and science to reduce climatic vulnerability and increase productivity of resilient agricultural practices.
... The incidence of climate induced extreme events, particularly drought, has also increased in the region (Shrestha & Aryal, 2011). Changes in precipitation patterns and incidence of drought induce very serious impacts on crop growth and production when they coincide with critical crop stages such as flowering (Poudel & Kotani, 2013). Climate-induced changes are directly affecting the livelihoods of the local farmers who already face high poverty and food insecurity (Gautam, 2019). ...
This study attempted to understand the local perspective on climate change and its impacts on agriculture and household food security in the Karnali region of Nepal – one of the most inaccessible and least researched mountain regions in Nepal. Using the small-scale survey data collected in 2017 from farm households in Tatopani rural municipality of Jumla district, the study found that a majority of households perceived changes in temperature and rainfall patterns, timing of seasons, incidence of drought and water availability, compared with the situation 10 years ago (2007 or earlier). They perceived mixed impacts of climate change on the production of major crops: a decline in the production of brown rice, wheat and barley, and an increase in the production of potato and local beans. Food security analysis showed that farm households had low dietary diversity, and 42% of them were food insecure. Regression analysis found that perceived climate-induced changes in water availability, timing of seasons, incidence of hazards and incidence of crop pest attacks had negative relationship with household food security. Based on the findings, the study suggested some key strategies to improve local food security in the face of climate change in the study area and other similar areas.
... Las plantaciones comerciales a gran escala y los agronegocios asociados, se verán afectados de manera similar (Machovina y Feeley, 2013). La producción de cultivos tiene diferentes impactos dependiendo de la elevación, el tipo de cultivo y temporada de crecimiento (Poudel y Kotani, 2013). Por ejemplo, es probable que el cambio climático genere cambios geográficos en los cultivos y la idoneidad de la tierra, dando como resultado cambios en la aparición de plagas y enfermedades de los cultivos (Cintra et al., 2008), estos impactos pueden suponer una gran amenaza para diferentes cultivos comerciales. ...
The present study presents the design of a monitoring system that shows climate conditions in a plantain crop by generating alerts of climate variables detected outside the optimal production range. Most plantain crops are controlled by a manual operator, which raises operational costs. The monitoring system uses electronic sensors and wireless communication technologies (XBee and GSM) using an embedded Arduino system. This is interpreted in the QT Creator software by interacting with a database developed in MySQL. The system is composed of two field stations where climate variables reading sensors are located. A monitoring station for supervision is located outside the agricultural area. It is concluded that the monitoring system presented here allows the user to monitor plantain crops remotely and to have access to a history of climate records and out-of-range values that permit avoiding crop production losses.
... Prior to applying the data for the Just-Pope model, we examine the stationarity of the data using the ADF-Fisher-type and Levin, Lin, and Chu (LLC) tests, following the argument made by Poudel and Kotani [84] and Sarker et al. [83]. The outcomes of both tests were reported in Table 6. ...
The main purpose of the study was to investigate the effects of climatic change on potato yield and yield variability in Agro-Ecological Zones (AEZs) of Iran during 2041–2070 (2050s). The Statistical Downscaling Model (SDSM) was performed in this study to downscale the outputs of the General Circulation Model (GCM) and to obtain local climate projections under climate scenarios for a future period. The Just and Pope Production function was used to investigate the impacts of climatic change on potato yield. The results showed that the effects of future climatic change on potato yield and its variability would vary among the different AEZs. Potato yield would change in the range from −11% to 36% across different AEZs during the 2050s. Yield variability is expected to vary from −29% to 6%. Much more generally, the results indicated that the major potato producing zones would experience a decrease in mean potato yield in the presence of climate change. Our findings would help policymakers and planners in designing appropriate policies to allocate the lands under potato cultivation among different zones. These results also have important implications for adopting ecological zone-specific strategies to mitigate the reduction in potato yield and meet food security.
... Several previous studies have examined the influence of climate change on crop yields over Nepal (Poudel and Kotani, 2012;Bhatt et al., 2014;Thapa-Parajuli and Devkota, 2016;Pratiksha et al., 2017) and have reported the inconsistent relationship between crop yield and climatic variability. Rise in temperature and change in precipitation patterns have been observed to affect the cropping cycle and crop production adversely (Maharjan and Joshi, 2013). ...
Drought influences agriculture, hydrology, ecology and socio‐economic systems globally. As agriculture is the primary source for livelihoods and contributes to ~27% of Nepalʼs total gross domestic product, it is essential to understand the impact of drought on maize and wheat crop yields to minimize the drought‐related risks. This study presents insights about agricultural drought across Nepal during 1987–2017 using the Standardized Precipitation Evapotranspiration Index (SPEI). The temporal evolution of SPEI time series has revealed frequent occurrences of drought episodes during the cropping cycle of summer maize and winter wheat crops. Moreover, the turning point of the drought was detected in 2000 (1987–2000, 2001–2017) in different regions. The averaged frequency for the SPEIs (1, 3, 6 and 12) of drought years for summer maize (winter wheat) in the western, central and eastern regions increased by 13% (12.5%), 6% (7.5%) and 7% (8%), respectively, from 1987–2000 to 2001–2017. The relationship between Standardized Yield Residual Series, the detrended SPEI at 1–12 lags and soil moisture was observed for both crops. The most correlated crop growth period for summer maize and winter wheat was the sowing and growing period, respectively, indicating the sensitive period of water deficit. Besides, the correlation performed in the two sub‐periods (1987–2000 and 2001–2017) shows that drought impacts increased in the western and central regions, whereas they substantially decreased in the eastern region during the cropping period of summer maize. However, the drought sensitivity for winter wheat was decreased in the western region but significantly increased in the central and eastern regions of Nepal. The results of this study provide important information useful for policymakers in monitoring and mitigating the drought‐related risks on maize and wheat crops in Nepal.
... Estimating the impact of climate change on crop yield and the evaluation of appropriate adaptation and mitigation strategies are of extreme concern (Jalota et al., 2012;Dharmarathna et al., 2014) to either stabilize or improve the crop yields. Several studies at various places have confirmed that rice cultivation without considering proper adaptation and mitigation strategies is problematic (Adejuwon, 2006;Wassmann et al., 2009;Iizumi et al., 2011;Tao et al., 2012;Poudel and Kotani, 2013). Recent literature has also reported the adequateness of proper agronomic adaptation strategies in relation to climate-induced yield losses in different regions (Tingem and Rivington, 2009;Chhetri and Easterling, 2010;Gouache et al., 2012;Mishra et al., 2013). ...
Purpose
The purpose of this paper is to consider the climatic variables and evaluate the role of non-climatic factors that delicately influence agriculture. This study has come across various adaptation strategies such as modification in cultivation practices such as shifting planting dates, water-saving techniques and strategic nutrient management. Meanwhile, we are trying to forget the ground reality that a majority of the farmers are not aware of climate-resilient production technologies. However, farmers modify themselves in this climate change scenario for sustainable production. The practise of these adaptation strategies helps to reduce vulnerability to improve their “socio-economic status” and the “quality of life”.
Design/methodology/approach
The present study was attempted to document all the indigenous practices, which are practised by paddy-growers over time for confronting the climate crisis in the Hyderabad-Karnataka region of Karnataka state, India. A cross-sectional and questionnaire-based survey was conducted to collect primary data. The pre-tested interviewing questionnaire consisted of 7 sections with 51 questions. A total of 90 paddy-growing farmers of the region was selected as respondents for the survey. The descriptive statistics was used to analyse the collected data.
Findings
In respect of adopted strategies, the vast majority (96.67%) of the farmers had used crops as livestock fodder as they fall back in case of failure, followed by the majority (72.22%) of the selected appropriate varieties. Cent per cent of the farmers adopted the construction of waterways along the slope for safe disposal of rainwater. An overwhelming portion of the farmers adopted levelling of the land in between the bunds (96.67%) and construction of bunds to conserve moisture (95.56%). The majority (76.67%) of the farmers intensified agricultural activities on irrigated land. Nearly half of them (47.78%) paddy growers were practising zero tillage to save time and money.
Research limitations/implications
The current study was carried out in a few districts of Karnataka. Hence, any policy framed based on the outcomes of this study may not conform to the policy specification needs in general to other parts of the country. The farmers did not maintain record books for updating various records. Therefore, the accuracy of data depends on the memory of the respondents. However, the researcher had made every possible effort to make sure that the data collected are the best of the knowledge of the respondents and bear minimal distortions.
Practical implications
The major constraints to applying agricultural adaptation strategies in the study area have been a general lack of knowledge, expertise and data on climate change issues; a lack of specific climate change institutions to take on climate change work and the need for a better institutional framework in which to implement adaptation. Actions to address these gaps include, namely, training programmes for local government officials, dedicated research activities and post-graduate courses and the initiation of specific institutional frameworks for climate change. Furthermore, improving and strengthening human capital, through education, outreach and extension services, improves decision-making capacity at every level and increases the collective capacity to adapt.
Social implications
Hyderabad-Karnataka is already under pressure from climate stresses, which increases vulnerability to further climate change and reduces adaptive capacity. The adverse effects of climate change have a devastating effect particularly on paddy cultivation, which is the mainstay of most Hyderabad-Karnataka Region. This has affected food production with its resultant effect on widespread poverty. Farmers in the study area have developed traditional agricultural adaptation strategies to cope with climate variability and extreme events. Experience with these strategies needs to be shared among communities.
Originality/value
Though the many literatures were available on the adaptation strategies for climate change this research is one of the few studies to document the farmer led adaptation strategies. This study provides a better understanding of the importance of farmer led adaptation strategies which in turn helps to develop or modify the existing adaptation technologies to cope up with climate change. The authors have come across various adaptation strategies such as modification in cultivation practices such as shifting planting dates, water-saving techniques and strategic nutrient management. Meanwhile, we are trying to forget the ground reality that the majority of the farmers are not aware of climate-resilient production technologies. However, farmers modify themselves in this climate change scenario for sustainable production. The practise of these adaptation strategies helps to reduce vulnerability to improve their “socio-economic status” and the “quality of life”. Therefore, farmer-led adaptation strategies to confront with a change in climate require to be recorded.
The species composition of bumblebees (Bombus species) across the elevation gradients in Chitwan-Annapurna Landscape (CHAL) was studied from April to November 2019. We performed opportunistic surveys to collect the bumblebee specimens. The walking transects were followed in the accessible places along the Kaligandaki, Marshyandi, and Budhigandaki river basins in different habitats (e.g., agricultural, forest, grassland and home garden). We identified 16 Bombus species from the sampling areas. The highest relative abundance was of B. haemorrhoidalis (20%), followed by B. festivus (20%) and B. eximius (19%). The least abundant species were B. branickii, B. miniatus, B. novus, and B. pressus with 1% relative abundance of each. We examined the effects of elevation on bumblebee richness and found a significant relationship. The Highest species richness was detected in the mid-elevation. Likewise, the highest species richness and diversity were found in the forest habitat in Gorkha site (n = 12, Shannon index H’ = 2.18) followed by the grassland habitat of the Mustang site (n = 11, Shannon index H’ = 2.10). Whereas, comparatively, species diversity was higher in habitats of the Gorkha site comparing Manang and Mustang. The elevation gradients create immense variations in microclimatic conditions and vegetation dynamics, which influence bumblebee abundance, species richness and diversities in different habitats in the study area. The mid-elevation range (2000–3000 m asl) of CHAL exhibited the highest species richness probably due to the higher availability of pollinator-dependent flowering plants in this range. The landcover composition and anthropogenic activities along the elevation gradient is the governing factor for the species composition, distribution and diversity of bumblebees in CHAL. We recommend to decision-makers for formulating their conservation strategies under a socio-ecological framework.
This study investigates the relationship between climate variables such as rainfall amount, temperature, and carbon dioxide (CO2) emission and the triple dimension of food security (availability, accessibility, and utilization) in a panel of 25 sub-Saharan African countries from 1985 to 2018. After testing for cross-sectional dependence, unit root and cointegration, the study estimated the pool mean group (PMG) panel autoregressive distributed lag (ARDL). The empirical outcome revealed that rainfall had a significantly positive effect on food availability, accessibility, and utilization in the long run. In contrast, temperature was harmful to food availability and accessibility and had no impact on food utilization. Lastly, CO2 emission positively impacted food availability and accessibility but did not affect food utilization. The study took a step further by integrating some additional variables and performed the panel fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression to ensure the robustness of the preceding PMG results. The control variables yielded meaningful results in most cases, so did the FMOLS and DOLS regression. The Granger causality test was conducted to determine the causal link, if any, among the variables. There was evidence of a short-run causal relationship between food availability and CO2 emission. Food accessibility exhibited a causal association with temperature, whereas food utilization was strongly connected with temperature. CO2 emission was linked to rainfall. Lastly, a bidirectional causal link was found between rainfall and temperature. Recommendations to the national, sub-regional, and regional policymakers are addressed and discussed.
The consequences of climate change threaten existing agriculture systems across Zimbabwe. The researchers examined the possibility and potential for developing a smallholder farmer driven macadamia nuts value chain. Using the case of Chipinge district, Manicaland province, Zimbabwe, the study evaluated the potential of macadamia nut value chain functions as a climate change resilience strategy in Zimbabwe. Challenges faced by actors and positive developments made in incorporating smallholders into the macadamia nuts production sector were explored. The role of local markets and producers in the international trade in macadamia nuts were also examined, using a modified stakeholder analysis framework. Triangulation, a mixed methodology, was used to adequately capture the various quantitative and qualitative dimensions along the macadamia nuts value chain pillars. A sample of 220 farming units including Estates, A1 and A2 farmers was proportionately selected for the study. Primary data were collected from Key Informants through interviews and personal communications. Secondary data were collected from Agritex officers, buyers, and the Macadamia Association of Zimbabwe farmers’ records. The production-marketing interface for macadamia nuts is weakly coordinated in the study area as shown by the rudimentary production systems especially for the A1 and A2 farmers. Results show that the major missing links are the limited application of extension driven production enhancers and the limited visibility of farmers in more rewarding export markets. Production scales have, however, been increasing with more farmers allocating land towards the macadamia nuts trees. Decentralization of macadamia nuts markets and localized value addition needs to be done to realign domestic and export market prices.
Climate change is a global problem since many countries worldwide are becoming increasingly vulnerable to natural disasters. Numerous climate models in various studies project a decline in agricultural productivity that will mainly be due to excessive heat in tropical and subtropical regions, especially in Southeast Asia. As a Southeast Asian country, Malaysia is no exception to this problem. Hence, the present study aimed to examine the impact of climate change on rice yields in Malaysia. A panel data approach was adopted using data from 1987 to 2017 on eight granary areas in Peninsular Malaysia. The main objectives were to assess the impact of climate variables (i.e., minimum and maximum temperature and precipitation) on rice yield and the variance of the impact during the main season and off-season. Our regression results indicate that precipitation was not statistically significant in all model specifications for both the main and off-season. While the maximum temperature was found to be negatively associated with yield during the off-season, the minimum temperature showed a positive effect in both cropping seasons. We used the HadGEM3-GC31 N512 resolution model based on the high-emission Shared Socioeconomic Pathways 8.5 scenario (SSPs-8.5) from the High-Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercom-parison Project Phase 6 (CMIP6) to project future climate change in 2030 and 2040. The projected results indicate that rice yield would show a more positive trend by 2040 when compared to the previous decade, ranging from −0.02 to 19.85% during the main season and −2.77 to 7.41% during the off-season. Although rice yield is likely to increase in certain areas, other areas are projected to experience negative effects. Hence, adaptation at the farm level remains crucial, specifically during the off-season, since climate change could widen the gaps in rice yields between cropping seasons and among granary areas.
Given the multidimensional nature of climate change issues, decision-making in climate change adaptation is a complex process, and suitable decision support methods are needed. The aim of this paper was to rank saltwater intrusion adaptation options for farmers in two provinces in the central coastal region of Vietnam using the analytical hierarchy process method. Data for the analysis were obtained through a literature review, field observations, and face-to-face interviews and focus group discussions with key informants. We combined two ways of weighting to arrive at final scores for each of the identified adaptation options: prioritizing criteria and subcriteria by pairwise comparison and rating the different alternatives with respect to the lowest level subcriteria. In doing so, we also investigated differences in the priority sets and final rankings of the analytical hierarchy process applications in both provinces. In our study, we worked with group consensus scores on both the criteria weights and the ratings for the different adaptation options for each of the criteria. Our results revealed that “sustainability and equity” was the most important criteria, while coherence ranked lowest. The final ranking of adaptation options differed between both provinces due to differences in the geographical and socioeconomic characteristics of the study areas. The consistency ratios for all pairwise matrices were less than 0.1, indicating that judgments from the focus group discussions with respect to the different criteria were highly consistent. A sensitivity analysis of our results confirmed the robustness of the rankings in our research.
Nepal Himalayas combine Oriental and Sino-Japanese zoogeographic realms as well as those of the eastern and western Himalayas. Physiography coupled with the diverse local climates has enriched the biodiversity of the Nepal Himalayas. The order Chiroptera constitutes more than 25% of the mammalian fauna and forms the most speciose group of mammals in Nepal, where bats are recorded within a wide range of elevations from 64m to 4154m. Climate variation in the past has been observed and projected change has been predicted, and an evaluation of the climate change impact on biodiversity and habitats has been initiated. However, none of the studies has assessed the impact of climate change on bats in the Himalayan range including Nepal, despite bats represent the largest mammalian group in the country. Through Species Distribution Modelling (SDM), we describe the present distribution range for five common species, further assess their response to future climatic changes. Specifically, the occurrence of bats against 10 environmental variables were projected under different climate scenarios; present, Representative Concentration Pathways (RCPs) 4.5 and 8.5 for 2050 and 2070 deploying maximum entropy modeling (MaxEnt). We prepared predicted distribution range maps and estimated area using Arc GIS 10.7.1. Among 10 uncorrelated bioclimatic variables, six contribute to the SDM significantly. Annual precipitation (bio12) is the most common variable for all five species. Two species shows wider present distribution ranges compared to other three. Under the climate change scenarios, although predictions varied among species, similar trends of the range shifting toward northern latitudes and higher elevations are observed. Since the larger part of the current potential distribution range lies outside protected areas, a landscape level conservation approach prioritizing bat conservation is needed. Future surveys should target ground truthing in the western region of the country.
_______________________________________________________________________________________________ The study examines the vulnerability district-level panel data for sixteen years mean maximum temperature is all set especially in Northeast India. The fallouts rice crop is highest in the North region and 20.04 per cent in all India (when compared pronounced in Peninsular India (63.95 deductions disclose that the North region per cent and 22.58 per cent respectively decadal interval (2020-40) and decrease study advocates for raising the net crop through short-duration, climate-responsive cultivation of rice crop, on the other hand. irrigation projects and rainwater harvesting anthropogenic consequences of climate decline in rice crop net revenue over four
The impact of projected global warming on crop yields has been evaluated by indirect methods using simulation models. Direct studies on the effects of observed climate change on crop growth and yield could provide more accurate information for assessing the impact of climate change on crop production. We analyzed weather data at the International Rice Research Institute Farm from 1979 to 2003 to examine temperature trends and the relationship between rice yield and temperature by using data from irrigated field experiments conducted at the International Rice Research Institute Farm from 1992 to 2003. Here we report that annual mean maximum and minimum temperatures have increased by 0.35°C and 1.13°C, respectively, for the period 1979–2003 and a close linkage between rice grain yield and mean minimum temperature during the dry cropping season (January to April). Grain yield declined by 10% for each 1°C increase in growing-season minimum temperature in the dry season, whereas the effect of maximum temperature on crop yield was insignificant. This report provides a direct evidence of decreased rice yields from increased nighttime temperature associated with global warming.
This paper brings out perceptions and observations of Tharu communities (Rana and Chaudhary), inhabitants of Shakarpur VDC of Kanchanpur and Gadariya VDCs of Kailali on climate change and its impacts on their livelihood strategies over the years. In addition, the paper explores some initiatives taken by the local communities to minimize its effects and impacts. Focus Group Discussions (FGD) were organized to collect and analyze vulnerability contexts on climate change and its impact on various sectors like, agriculture, forest, livestock, biodiversity, infrastructure, human casualties and water sources. Similarly, information on available service providers and their contribution was garnered through secondary sources. Local communities are facing these changes over the time and adapting strategies as per their own traditional knowledge, skills and information. Most of these strategies are biodiversity friendly, economically viable and socially acceptable. However, these innovative steps should be shared for larger scale dissemination after validating with scientific review and justifications.
The largest known economic impact of climate change is upon agriculture because of the size and sensitivity of the sector. Warming causes the greatest harm to agriculture in developing countries primarily because many farms in the low latitudes already endure climates that are too hot. This paper reviews several studies that measure the size of the impact of warming on farms in developing countries. Even though adaptation will blunt some of the worst predicted outcomes, warming is expected to cause large damages to agriculture in developing countries over the next century.
"The Challenge The unimpeded growth of greenhouse gas emissions is raising the earth’s temperature. The consequences include melting glaciers, more precipitation, more and more extreme weather events, and shifting seasons. The accelerating pace of climate change, combined with global population and income growth, threatens food security everywhere. Agriculture is extremely vulnerable to climate change. Higher temperatures eventually reduce yields of desirable crops while encouraging weed and pest proliferation. Changes in precipitation patterns increase the likelihood of short-run crop failures and long-run production declines. Although there will be gains in some crops in some regions of the world, the overall impacts of climate change on agriculture are expected to be negative, threatening global food security. Populations in the developing world, which are already vulnerable and food insecure, are likely to be the most seriously affected. In 2005, nearly half of the economically active population in developing countries—2.5 billion people—relied on agriculture for its livelihood. Today, 75 percent of the world’s poor live in rural areas. This Food Policy Report presents research results that quantify the climate-change impacts mentioned above, assesses the consequences for food security, and estimates the investments that would offset the negative consequences for human well-being. This analysis brings together, for the first time, detailed modeling of crop growth under climate change with insights from an extremely detailed global agriculture model, using two climate scenarios to simulate future climate. The results of the analysis suggest that agriculture and human well-being will be negatively affected by climate change: * In developing countries, climate change will cause yield declines for the most important crops. South Asia will be particularly hard hit. * Climate change will have varying effects on irrigated yields across regions, but irrigated yields for all crops in South Asia will experience large declines. * Climate change will result in additional price increases for the most important agricultural crops–rice, wheat, maize, and soybeans. Higher feed prices will result in higher meat prices. As a result, climate change will reduce the growth in meat consumption slightly and cause a more substantial fall in cereals consumption. * Calorie availability in 2050 will not only be lower than in the no–climate-change scenario—it will actually decline relative to 2000 levels throughout the developing world. * By 2050, the decline in calorie availability will increase child malnutrition by 20 percent relative to a world with no climate change. Climate change will eliminate much of the improvement in child malnourishment levels that would occur with no climate change. * Thus, aggressive agricultural productivity investments of US$7.1–7.3 billion are needed to raise calorie consumption enough to offset the negative impacts of climate change on the health and well-being of children." from Text
Changes in the global production of major crops are important drivers of food prices, food security and land use decisions. Average global yields for these commodities are determined by the performance of crops in millions of fields distributed across a range of management, soil and climate regimes. Despite the complexity of global food supply, here we show that simple measures of growing season temperatures and precipitation—spatial averages based on the locations of each crop—explain ~30% or more of year-to-year variations in global average yields for the world's six most widely grown crops. For wheat, maize and barley, there is a clearly negative response of global yields to increased temperatures. Based on these sensitivities and observed climate trends, we estimate that warming since 1981 has resulted in annual combined losses of these three crops representing roughly 40 Mt or $5 billion per year, as of 2002. While these impacts are small relative to the technological yield gains over the same period, the results demonstrate already occurring negative impacts of climate trends on crop yields at the global scale.
With an estimated 798 million people currently "undernourished", meeting the Millennium Development Goal of halving hunger by 2015 is already looking difficult. How will climate change affect this challenge? Climate change models predict that those likely to be most adversely affected are the regions already most vulnerable to food insecurity, notably Africa, which stands to lose substantial agricultural land. An additional threat is the uncertainty climate change brings, including negative interactions between gradual and abrupt changes. However, adaptive behaviour and new technology have not been factored into many climate models. If appropriate mitigation and adaptation measures were implemented now, hunger could be substantially reduced, regardless of climate change. But adaptation comes at high economic cost and those who need it most can afford it least. The article concludes that in order to effectively meet the challenge of climate change, political responses will be just as important as technological change.
For the third consecutive year, drought conditions have been severely affecting agricultural production in Nepal and in some cases turning traditionally surplus production areas into deficit ones. In addition to the heavily drought affected Mid-and Far-Western Regions, flood exacerbated by hailstones and crop diseases in various VDCs caused extensive crop loss. Drought particularly affected the traditionally food surplus areas of the Eastern Terai, particularly Siraha, Saptari and Dhanusha which reported a decline in paddy production of about 30%. A total of 109,855 hectares of paddy land (7.09%) remained fallow in 2006/07 as farmers were unable to plant due to drought. In addition, yields were lower by almost 6%. Paddy crop production consequently declined by 12.5 % compared to last year. The total food grain shortfall for the year 2006/07 has been calculated at 187,748 Mt assuming favorable weather conditions for the winter crop wheat and barley.
This study explores the interaction between climate, water, and agriculture. We test whether surface water withdrawal can help explain the variation of farm values across the United States and whether adding these variables to the standard Ricardian model changes the measured climate sensitivity of agriculture. The paper finds that the value of irrigated cropland is not sensitive to precipitation and increases in value with temperature. Finally, the paper finds that sprinkler systems are used primarily in wet cool sites, whereas gravity and especially drip systems help compensate for higher temperatures. These results indicate that irrigation can help agriculture adapt to global warming.
Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO2 doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO2 experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.
This paper examines the effects of climatic and non-climatic factors on the mean and variance of corn, soybean and winter
wheat yield in southwestern Ontario, Canada over a period of 26years. Average crop yields increase at a decreasing rate with
the quantity of inputs used, and decrease with the area planted to the crop. Climate variables have a major impact on mean
yield with the length of the growing season being the primary determinant across all three crops. Increases in the variability
of temperature and precipitation decrease mean yield and increase its variance. Yield variance is poorly explained by both
seasonal and monthly climate variable models. Projections of future climate change suggest that average crop yield will increase
with warmer temperatures and a longer growing season which is only partially offset by forecast increases in the variability
of temperature and rainfall. The projections would also depend on future technological developments, which have generated
significant increases in yield over time despite changing annual weather conditions.
Impact of elevated CO2 and temperature on rice yield in eastern India was simulated by using the ORYZA1 and the INFOCROP rice models. The crop and weather data from 10 different sites, viz., Bhubaneswar, Chinsurah, Cuttack, Faizabad, Jabalpur, Jorhat, Kalyani, Pusa, Raipur and Ranchi, which differed significantly in their geographical and climatological factors, were used in these two models. For every 1 °C increase in temperature, ORYZA1 and INFOCROP rice models predicted average yield changes of −7.20 and −6.66%, respectively, at the current level of CO2 (380 ppm). But increases in the CO2 concentration up to 700 ppm led to the average yield increases of about 30.73% by ORYZA1 and 56.37% by INFOCROP rice. When temperature was increased by about +4 °C above the ambient level, the differences in the responses by the two models became remarkably small. For the GDFL, GISS and UKMO scenarios, ORYZA1 predicted the yield changes of −7.63, −9.38 and −15.86%, respectively, while INFOCROP predicted changes of −9.02, −11.30 and −21.35%. There were considerable differences in the yield predictions for individual sites, with declining trend for Cuttack and Bhubaneswar but an increasing trend for Jorhat. These differences in yield predictions were mainly attributed to the sterility of rice spikelets at higher temperatures. Results suggest that the limitations on rice yield imposed by high CO2 and temperature can be mitigated, at least in part, by altering the sowing time and the selection of genotypes that possess higher fertility of spikelets at high temperatures.
Climate change influences crop yield vis-à-vis crop production to a greater extent in countries like Nepal where agriculture depends largely on natural circumstances. Plausible scenarios of climate change like higher temperatures and changes in precipitation will directly affect crop yields. Therefore, this study assesses the effect of observed climate variables on yield of major food-crops in Nepal, namely rice, wheat, maize, millet, barley and potato based on regression model for historical (1978-2008) climatic data and yield data for the food-crops. The yield growth rate of all the foodcrops is positive. However, the growth rate for all crops, except potato and wheat, is below population growth rate during the period. Climate variables like temperature and precipitation are the important determinants of crop yields. Trend of precipitation is neither increasing nor decreasing significantly during this period. However, temperature is increasing by 0.7 °C during the period. Climate variables show some influences on the yield of these major food-crops in Nepal. Increase in summer rain and maximum temperature has contributed positively to rice yield. Also, increase in summer rain and minimum temperature has positive impact on potato yield. However, increase in summer rain and maximum temperature adversely affected the yield of maize and millet. Increase in wheat and barley yield is contributed by current trend of winter rain and temperature. Consideration of spatial variation in similar type of study in Nepal that will be helpful in identifying the region more vulnerable to climate change in terms of crop yield is highly recommended.
Production functions to explain regional wheat yields have not been studied extensively in the Canadian prairies. The objective of this study is to employ a Just-Pope production function to examine the relationship between fertilizer inputs, soil quality, biodiversity indicators, cultivars qualifying for Plant Breeders’ Rights (PBR), and climatic conditions on the mean and variance of spring wheat yields. Using regional-level wheat data from Manitoba, Canada, model results show nitrogen fertilizer, temporal diversity, and PBR wheat cultivars are associated with increased yield variance. Mean wheat yield is reduced by the proportion of land in wheat, the interaction of growing temperature and precipitation, and spatial diversity. By contrast, higher soil quality and PBR wheat cultivars increase mean yield. The wheat yield increases attributed to PBR range from 37.2 (1.4%) to 54.5 kg/ha (2.0%). Plant Breeders’ Rights may have enhanced royalties from increased certified seed sales, but the benefits in terms of higher wheat yield or lower yield variability are limited. Future research is required to understand the interactive effects of fertilization practices, genetic diversity, and environmental conditions on regional wheat yield stability.
One of the issues with respect to climate change involves its influence on the distribution of future crop yields. Many studies have been done regarding the effect on the mean of such distributions but few have addressed the effect on variance. Furthermore, those that have been done generally report the variance from crop simulators, not from observations. This paper examines the potential effects of climate change on crop yield variance in the context of current observed yields and then extrapolates to the effects under projected climate change. In particular, maximum likelihood panel data estimates of the impacts of climate on year-to-year yield variability are constructed for the major U.S. agricultural crops. The panel data technique used embodies a variance estimate developed along the lines of the stochastic production function approach suggested by Just and Pope. The estimation results indicate that changes in climate modify crop yield levels and variances in a crop-specific fashion. For sorghum, rainfall and temperature increases are found to increase yield level and variability. On the other hand, precipitation and temperature are individually found to have opposite effects on corn yield levels and variability.
Mean Reversion of Balance of Payments (BOP) is analyzed by panel data methodology using the first generation (Im, Pesaran and Shin’s and Levin, Lin and Chu t-test) and the second generation (cross-sectional augmented ADF statistics) unit root tests on 24 OECD countries over the years ranging from 1982 to 2007. Both of the cross-sectional independence and cross-sectional dependence test results we obtained illustrate that BOP is mean reverting. It follows that the BOP will return to its trend path over time and the assumption of Mundell-Fleming model will be validated. These findings provide strong evidence for the assumption of Mundell-Fleming model.
In the estimation of production functions, ignoring risk considerations can cause inefficient estimates, while biased parameter estimates arise in the presence of sample selection. In the presence of uncertainty and selection bias, the latter introduced by the endogeneity of qualitative characteristics of inputs in crop choice, we show that correcting for risk considerations (a la Just and Pope, 1978, 1979) but not selection bias, can produce incorrect inferences in terms of risk behavior. The arguments raised in this study have estimation and policy implications for stochastic production analysis applied to all goods whose qualitative characteristics can affect sample selection.
The impact of projected global warming on crop yields has been evaluated by indirect methods using simulation models. Direct studies on the effects of observed climate change on crop growth and yield could provide more accurate information for assessing the impact of climate change on crop production. We analyzed weather data at the International Rice Research Institute Farm from 1979 to 2003 to examine temperature trends and the relationship between rice yield and temperature by using data from irrigated field experiments conducted at the International Rice Research Institute Farm from 1992 to 2003. Here we report that annual mean maximum and minimum temperatures have increased by 0.35 degrees C and 1.13 degrees C, respectively, for the period 1979-2003 and a close linkage between rice grain yield and mean minimum temperature during the dry cropping season (January to April). Grain yield declined by 10% for each 1 degrees C increase in growing-season minimum temperature in the dry season, whereas the effect of maximum temperature on crop yield was insignificant. This report provides a direct evidence of decreased rice yields from increased nighttime temperature associated with global warming.
The benefits of nature-based tourism to biodiversity conservation are often presumed but rarely quantified. The relative value placed on attributes of nature parks is unknown, as is the contribution of biodiversity to tourists willingness to visit a particular protected area. We surveyed tourists and foreign residents in Uganda to determine how preferences for particular protected areas are formed. We evaluated tourists demand for elevated biodiversity levels (increased numbers of bird species seen), relative to other protected areas attributes. As the number of bird species increased, tourists demonstrated increased willingness to visit a protected area, independently of all other factors. We used these results to evaluate a revenue-maximizing park management strategy, and consider how revenues from nature-based tourism compare with those from local agricultural land-uses.
The outcome of the "race" between population and food is of enduring contemporary interest. The two variables that are set opposite each other in the race are fundamentally different in character. Population is primarily a stock concept that rises monotonically, whereas food production is overwhelmingly a flow variable that exhibits substantial year-to-year fluctuations. These latter fluctuations, in turn, cause significant economic and nutritional consequences at the household level. Assessing the pattern of these annual fluctuations in cereal yields with respect to their magnitude, geographic incidence, and change over time is thus of evident interest in questions concerning food security. This article assesses the growth and variability of corn, wheat, and rice yields from 1950 to 1994 on a global and regional basis. The results suggest that any broadly held notions of greatly increasing instability in global grain yields are probably wrong. More important, yield variability has not risen significantly between 1950 and 1994 in the developing world as a whole. Instability in corn yields has increased, however, in the developed world--particularly in North America--and in Africa. Higher yield variability is not necessarily a portent of disaster, but adjustments in trade, livestock, or storage are not instantaneous, automatic, or costless. Even world-food "optimists" need to worry about the possible effects of two or three successive "bad" corn crops in North America.
Exponential growth of CO 2 and other greenhouse gasses in the atmosphere is causing climate change. It affects agriculture, forestry, human health, biodiversity, snow coverand aquatic to mountain ecosystems. Changes in climatic factors like temperature, solar radiation and precipitation have potentials to influence crop production. Despite many efforts possible on combating impacts of climate change, there are still difficulties in Nepalese agriculture. With an average of 0.06 o C/yea, a rise in temperature from 1975 to 2006 by 1.8 o C has been recorded in the country. Problem of frequent drought, severe floods, landslides and mixed type of effects in agricultural crops have been experienced in Nepal because of climate change. Study done on CO 2 enrichment technology at Khumaltar revealed that the yield of rice and wheat increased by 26.6% and 18.4% due to double CO 2 , 17.1% and 8.6% due to increase in temperature respectively. A crop simulation model (DSSAT) to study the effects of CO 2 , temperature and rain in NARC showed positive effect in yield of rice and wheat in all regions, but negative effect in maize especially in Terai. In Nepalese agriculture, the time has come for the authorities to find out adaptive measures to mitigate the effects to reduce untold natural calamities and miseries due to recent erratic weather pattern.
Data from a large series of field trials made in Romania is analysed at first and, subsequently, the IATA-Wheat Phenology model is used to calculate the impact of air warming on wheat Triticum aestivum. The results showed the impact of an even or uneven distribution of warming effects. In the first case, the model predicted that the duration of the vegetative period was at least partly reduced in some years. In the second case, the model suggested that if warming will be more pronounced in winter than in spring, an increase in the duration of the vegetative phase of growth may be expected. In case of a spring warming, but unchanged winter temperatures, a substantial decrease may be expected. -from Authors
Climate change is a global challenge that has a particularly strong effect on developing countries such as Nepal, where adaptive
capacity is low and where agriculture, which is highly dependent on climatic factors, is the main source of income for the
majority of people. The nature and extent of the effects of climate change on rural livelihoods varies across Nepal in accordance
with its highly diverse environmental conditions. In order to capture some of this variability, a comparative study was performed
in two different ecological regions: Terai (lowland) and Mountain (upland) in the western development region of Nepal. The
study focuses on perceptions of, and on adaptations to climate change by farmers. Information was collected from both primary
and secondary data sources. Climate data were analyzed through trend analysis. Results show that most farmers perceive climate
change acutely and respond to it, based on their own indigenous knowledge and experiences, through both agricultural and non-agricultural
adaptations at an individual level. The study also shows that there is a need to go beyond the individual level, and to plan
and provide support for appropriate technologies and strategies in order to cope with the expected increasing impacts of climate
change.
KeywordsClimate change–Ecological regions–Indigenous knowledge–Adaptation–Nepal
This study analyses data on winter wheat (Triticum aestivum L.) development and climate from Tongwei County (35°13′N, 105°14′E), Gansu, in the semiarid northwest of China during 1981–2005. Two study sites were chosen: one at Tongwei Meteorological Station, situated at 1798 m above sea level at the foot of LuLu Mountain, and the second on the summit of LuLu Mountain at an altitude of 2351 m. The objective was to investigate whether there were significant trends in the change of climate variables, and whether these changes have significantly affected the development and production of winter wheat at different altitudes above sea level. The results showed that, with changes in temperature and precipitation, there was a significant change in the phenology of winter wheat that crop yields increased at both sites from 1981 to 2005, and that the increase in yields was higher at the high-altitude site. During 1981–1998 the yields at the high-altitude site were lower than at the low altitude site, whereas after 1998 the yields at the high-altitude site were higher than at the low altitude site. In the face of climate change, winter wheat production in this region during 1981–2005 was higher at the higher altitude site than at the lower altitude site. It is expected that, by 2030, the interaction of warming temperature and changed rainfall will have led to a further increase of 3.1% in wheat yields at a low altitude and of 4.0% at a high altitude in the semiarid northwest of China.
The stochastic specification of input-output response is examined. Postulates are set forth which seem reasonable on the basis of a priori theorizing and observed behavior. It is found that commonly used formulations are restrictive and may lead to inefficient and biased results. A function which satisfies the postulates is suggested. Two- and four-stage procedures for estimation of the resulting function are then outlined. The estimators are shown to be consistent and, in the latter case, asymptotically efficient under normality.
The battle to achieve sustainable growth in agricultural production must be fought out along a broad multidisciplinary front. Poverty undermines health and degrades the environment. Environmental problems link the agricultural and health research agendas. Environmental changes underway at the global level will require changes in food production and health practices. Effective bridges must be built between the ‘island empires’ of the agricultural, environmental, and health sciences. More effective linkages must be built between the suppliers of knowledge and technology and the users.
This paper develops an econometric model of stochastic production functions to quantify the impacts of climatic variables on the mean, variance, and covariance of crop yields. The estimates of the production function parameters and their elasticities are utilized to analyse the impacts of the projected climate change on agriculture. The results show that the climate change will have modest effects on the mean crop yields, but will significantly reduce the variance and covariance for most of the crops considered. The results have implications for allocations of agricultural land among crops and for crop production mix.
Evidence exists that climate change will shift the mean and variance of crop yields, challenging the stationarity assumption. The primary reason is that the Fixed Effects model allows researchers to estimate a unit-specific effect for each state in the model. In addition, the Fixed Effects model does not require the restrictive assumption that the state-specific effect is independent of the included covariates as the Random Effects model does. State dummies are included in the regression to capture state-specific effects that are invariant over time. The pattern is somewhat different for corn in the North Plains, where the corresponding changes are 29% and 61%for changes in average climate conditions, and 24% and 76% when higher temperature variability occurs. The regression results show that stationarity does not hold as we find that both the mean and the variance of key climate variables evolved over time.
Because most developing countries depend heavily on agriculture, the effects of global warming on productive croplands are likely to threaten both the welfare of the population and the economic development of the countries. Tropical regions in the developing world are particularly vulnerable to potential damage from environmental changes because the poor soils that cover large areas of these regions already have made much of the land unusable for agriculture. Although agronomic simulation models predict that higher temperatures will reduce grain yields as the cool wheat-growing areas get warmer, they have not examined the possibility that farmers will adapt by making production decisions that are in their own best interests. A recent set of models examines cross-sectional evidence from India and Brazil and finds that even though the agricultural sector is sensitive to climate, individual farmers do take local climates into account, and their ability to do so will help mitigate the impacts of global warming. Copyright 1999 by Oxford University Press.
This paper examines whether electoral motives and government ideology influence short-term economic performance. I employ data on annual GDP growth in 21 OECD countries over the 1951-2006 period and provide a battery of empirical tests. In countries with two-party systems GDP growth is boosted before elections and, under leftwing governments, in the first two years of a legislative period. These findings indicate that political cycles are more prevalent in two-party systems because voters can clearly punish or reward political parties for governmental performance. My findings imply that we need more elaborate theories of how government ideology and electoral motives influence short-term economic performance.
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