Modelling Impacts of Climate Change on Maize (Zea mays L.) Growth and Productivity: A Review of Models, Outputs and Limitations

The use of crop modelling in various cropping systems and environments to project and upscale agronomic decision-making under the facets of climate change has gained currency in recent years. This paper provides an evaluation of crop models that have been used by researchers to simulate maize growth and productivity. Through a systematic review approach, a comprehensive assessment of 186 published articles was carried out to establish the models and parameterization features, simulated impacts on maize yields and adaptation strategies in the last three decades. Of the 23 models identified, CERES-maize and APSIM models were the most dominant, representing 49.7% of the studies undertaken between 1990 and 2018. Current research shows projected decline in maize yields of between 8% - 38% under RCP4.5 and RCP8.5 scenarios by the end of the 21st century, and that adaptation is essential in alleviating the impacts of climate change. Major agro-adaptation options considered in most papers are changes in planting dates, cultivars and crop water management practices. The use of multiple crop models and multi-model ensembles from general circulation models (GCMs) is recommended. As interest in crop modelling grows, future work should focus more on suitability of agricultural lands for maize production under climate scenarios

Land use-based participatory assessment of ecosystem services for ecological restoration in village tank cascade systems of Sri Lanka

Village Tank Cascade System (VTCS) landscapes in the dry zone of Sri Lanka provide multiple ecosystem services (ESs) and benefits to local communities, sustaining the productivity of their land use systems (LUSs). However, there is a lack of adequate scientific research on the ESs of LUSs, despite the recent land use changes that have greatly impacted the provisioning of ESs. Collection of baseline ESs data is a pre-requisite for decision making on ESs-based ecological restoration and management of the VTCS. Thus, this study aimed at assessing ESs of the Mahakanumulla VTCS (MVTCS) located in the Anuradhapura district of Sri Lanka by using a participatory approach involving the integration of local knowledge, expert judgements and LUSs attribute data to assess the ESs. The methodology was designed to integrate the biodiversity and land degradation status of LUSs in a way that is directly linked with the supply of ESs. The study identified twenty-four ESs of the MVTCS based on community perceptions. The identified ESs were assessed as a function of LUSs to develop an ecosystem service supply (ESS) and demand (ESD) matrix model. The results reveal that the current overall ESD for regulating and supporting ESs is higher than the ESS capacity of MVTCS. The assessment also revealed that land degradation and biodiversity deterioration reduce the capacity to provide ESs. Downstream LUSs of the meso-catchment were found to be more vulnerable to degradation and insufficient to provide ESs. Further, the study established that ESs in the MVTCS are generated through direct species-based and biophysical-based providers. In addition, it emerged that social and cultural engagements also played an important role in association with both providers to generate certain types of ESs. Therefore, it can be concluded that VTCS ecological restoration depends on the extent to which integrated effort addresses the levels of ecological complexity, as well as the social engagement of communities and stakeholders. The results of this study provide a scientific basis that can inform future land use decision making and practices that are applicable to successful ESs-based ecological restoration and management of the VTCSs in the dry zone of Sri Lanka

Impact of Land Use/Cover Changes on Soil Erosion in Western Kenya

This study examined the impact of land use/cover changes on soil erosion in western Kenya in the years 1995 and 2017. The study used the GIS-based Revised Universal Soil Loss Equation (RUSLE) modelling approach and remote sensing assessment. The results showed that the average soil loss through sheet, rill and inter-rill soil erosion processes was 0.3 t/ha/y and 0.5 t/ha/y, in the years 1995 and 2017, respectively. Of the total soil loss, farms contributed more than 50%, both in 1995 and 2017 followed by grass/shrub (7.9% in 1995 and 11.9% in 2017), forest (16% in 1995 and 11.4% in 2017), and the least in built-up areas. The highest soil erosion rates were observed in farms cleared from forests (0.84 tons/ha) followed by those converted from grass/shrub areas (0.52 tons/ha). The rate of soil erosion was observed to increase with slope due to high velocity and erosivity of the runoff. Areas with high erodibility in the region are found primarily in slopes of more than 30 degrees, especially in Mt. Elgon, Chereng’anyi hills and Elgeyo escarpments. This study forms the first multi-temporal assessment to explore the extent of soil erosion and seeks to provide a useful knowledge base to support decision-makers in developing strategies to mitigate soil erosion for sustainable crop production

Analysis of spatio-temporal dynamics of land use and cover changes in Western Kenya

The western region of Kenya is experiencing remarkable land changes resulting from population growth and related impacts. The study used remote sensing and GIS techniques to analyze the land use/cover changes in the years 1995, 2001, 2010 and 2017. Multi-spectral Landsat (TM, ETM + and OLI) images were pre-processed and classified using maximum likelihood algorithm in ENVI version 5.4. The overall classification accuracies in all the images were more than 80%. The results revealed major conversions of each land use/land cover type in varying trends and magnitudes. Between 1995 and 2001, there was an increase in built-up areas by 71%, forest cover by 43%, farms by 5%; and decrease in grassland by 47%. By 2017, the built-up areas had increased by 225% and farms by 17%; the forestland, grassland and water reduced by 38, 10 and 11%, respectively. The observed changes are characterized by increased settlements and encroachment of sensitive ecosystems

Forest cover dynamics and underlying driving forces affecting ecosystem services in western Kenya

Koech, RK ORCiD: 0000-0002-0563-6687Deforestation poses a threat to sustainability of forest ecosystem services and socio-economic development in many parts of Kenya. Understanding the trend and extent of forest cover changes and the underlying driving forces over time is pertinent for sustainable management of ecosystems. However, in many parts of the country, such information is still somewhat unknown due to limited data availability for multi-temporal analysis. This paper focuses on western Kenya, a major agricultural region of biodiversity and water catchments that are under threat from forest cover dynamics. The study analyses the status of the forests in the region with the aim of determining the areal extent of coverage, trends in forest cover, drivers of change and associated impacts of deforestation. To achieve these objectives, remote sensing techniques were used to undertake supervised classification on Landsat images of 1995, 2001, 2010 and 2017 with classification scheme of forest and non-forest land cover classes. The results of the study showed that the changes in forest cover varied over time and space. There was considerable net gain in forest areas by about 43% between the period 1995–2001, and thereafter, a continuous decrease ending in a 12.5% loss by 2017. Deforestation in the region is caused by a combination of complex factors that include population pressure, politics and failures in implementation of policy. This study determined the forest cover dynamics and driving forces across diversified sub-basins, an approach that had not been used by previous studies in the region. Thus, the findings will provide valuable information for decision making pertaining to integrated land use and catchment management in order to realize the enormous benefits of sustainable forest ecosystems. The information will not only be important to the study area, but equally applicable to similar tropical regions

Examining the Impacts of Climate Change, Climate Variability and Land Use/Cover Changes on Rainfed Agriculture in Kenya - Dataset

This dataset has five sets of files. The First file contains information collected from an interview of 210 maize farmers in four counties of western Kenya. The Second, Third and Fifth files contains daily gridded rainfall, maximum temperature and minimum temperature data, respectively, for 33 locations (coordinates provided) in western Kenya for the period 01/01/1981 to 30/10/2018. The Third file has information of 738 occurrence location points of maize crop that were sampled in Kenya

Examining the Impacts of Climate Change, Climate Variability and Land Use/Cover Changes on Rainfed Agriculture in Kenya

Globally and over a longer period, climate change continues to pose negative impacts to the agricultural sector. In particular, Sub-Saharan Africa (SSA) has been well known as a continent that is highly susceptible to climate change due to over reliance on rainfed agriculture, multiple stressors and low capacity to cope. Land use/cover change is also a locally pervasive and worldwide trend that has notable implications on ecological trends, sustainability of ecosystem services, communities and biodiversity. Kenya, like other countries in SSA, has experienced remarkable and far-reaching land use/cover changes over time as a consequence of variable climate, population pressure, environmental degradation, land fragmentation and unsustainable agricultural practices that have contributed to food insecurity and increased vulnerabilities. However, information is scant on how climate variability and land use/cover changes could affect current and future ecological suitability for production of main food crops under rainfed conditions. Thus, to bridge the gap, this study analysed the trend of climate variability and land use/cover changes and their impacts using a case study of western Kenya, an area of high agricultural potential, as a classic example of an affected region. The outcome of a systematic review of 186 journal articles published in different parts of the world show a projected reduction in maize yields of between 8-38% by the end of the 21st century due to climate change. In Africa, an ecological niche modelling using the Maximum Entropy (MaxEnt) approach to examine land suitability for major food crops identified two major shifts: 11.1-22.0% expansion in areas suitable for production of maize, and a 1.6-7.3% decline in areas suitable for production of millet and sorghum. In Kenya, the assessment showed a potential for increase in unsuitable areas for maize production by an average of between 1.9–3.9% and a decrease of moderately suitable areas by 14.6–17.5%. The change in the suitable and highly suitable areas in the country is an increase of between 17–20% and 9.6%, respectively, under climate change. The loss of suitability for production of food crops is likely to cause detrimental impacts on food security for the communities as uncertainties of projected climate variability and change unfold Hydrological modeling of the temporal trends of rainfall variability using Mann-Kendall test and Sen's slope estimator in the major maize growing counties of western Kenya revealed noticeable decrease of March-April-May rainfall, and an increase in September-October-November rainfall. Under RCP 8.5, the results show a projected seasonal shift and an increase in intensity of major rains from March-April-May to June-July-August, which is likely to affect climatic suitability for cultivation and production of key crops in the region. The multi-index characterization of drought on a 12-month time series show a likelihood of moderate to extreme drought years under RCP 4.5 and RCP 8.5 climatic scenarios. The western Kenya region has also experienced spatial and temporal land use/cover changes of varying trends and magnitudes in the years 1995, 2001, 2010 and 2017. Classification of multi-spectral Landsat images show that between 1995 and 2001, there was an increase in builtup areas by 71%, forestland by 43%, farms by 5%" and decrease in grassland by 47%. By 2017, the built-up areas had increased by 225% and farms by 17%" while the forestland, grassland and water reduced by 38%, 10% and 11%, respectively. The observed changes were characterised by increased settlements and encroachment of sensitive ecosystems. The use of GIS-based Revised Universal Soil Loss Equation (RUSLE) modelling approach and remote sensing techniques to examine the impacts of land use/cover changes on land degradation due to sheet, rill and inter-rill soil erosion processes in western Kenya resulted to average soil loss of 0.3 ton/ha/year and 0.5 ton/ha/year, in the years 1995 and 2017, respectively. Of the total soil loss, farms contributed more than 50%, both in 1995 and 2017 followed by grass/shrub (7.9% in 1995 and 11.9% in 2017), forest (16% in 1995 and 11.4% in 2017), and the least in built up areas. The highest soil erosion rates were observed in farms cleared from forests (0.84 tons/ha) followed by those converted from grass/shrub areas (0.52tons/ha). The rate of soil erosion was observed to increase with slope due to high velocity and erosivity of the run-off. Soils susceptible to highest erosion rates are found primarily in slopes of more than 30 degrees, especially in Mt. Elgon, Chereng'anyi hills and Elgeyo escarpments. The maize farmers in western Kenya perceived reduced rainfall with erratic patterns to be the major climatic risk affecting crop production. The non-climatic factors were identified as inadequate farm size, limited extension services, land degradation and low soil fertility. The major adaptation strategies undertaken by the farmers included change in planting dates by either planting early or late during a season, diversification of crops, growing early maturing cultivars and use of drought-tolerant varieties. The use of logistic and multiple linear regression models revealed the key determinants of adaptation strategies by the farmers to include farm size, income and extension training. Understanding farmers' responses to climate change in rainfed crop production systems could assist in planning adaptation strategies towards sustainable crop production. The findings of this thesis are subject to uncertainties, which are associated with the modelling tools used, reliability and quality of climatic and crop occurrence data. Future changes in climatic scenarios could result to changes in bioclimatic variables, causing different shifts in climatic suitability and would be a consideration in future investigation. In addition, the use of one region as a case study for the scope on local perceptions limit the diversity of the results. Thus, future work can explore additional diversified cases to create a collection for comparison across regions, ecological and climatic zones. Overall, this research provides knowledge and information on how climate variability and land use/cover changes affect rainfed agriculture. Such knowledge provides a wider perspective of the issues alongside the local perceptions that are inherent in addressing the associated challenges and in decision making related to land use planning, land degradation management, drought preparedness and adaptation of crop production under climate change

Forest cover dynamics and underlying driving forces affecting ecosystem services in western Kenya

Deforestation poses a threat to sustainability of forest ecosystem services and socio-economic development in many parts of Kenya. Understanding the trend and extent of forest cover changes and the underlying driving forces over time is pertinent for sustainable management of ecosystems. However, in many parts of the country, such information is still somewhat unknown due to limited data availability for multi-temporal analysis. This paper focuses on western Kenya, a major agricultural region of biodiversity and water catchments that are under threat from forest cover dynamics. The study analyses the status of the forests in the region with the aim of determining the areal extent of coverage, trends in forest cover, drivers of change and associated impacts of deforestation. To achieve these objectives, remote sensing techniques were used to undertake supervised classification on Landsat images of 1995, 2001, 2010 and 2017 with classification scheme of forest and non-forest land cover classes. The results of the study showed that the changes in forest cover varied over time and space. There was considerable net gain in forest areas by about 43% between the period 1995–2001, and thereafter, a continuous decrease ending in a 12.5% loss by 2017. Deforestation in the region is caused by a combination of complex factors that include population pressure, politics and failures in implementation of policy. This study determined the forest cover dynamics and driving forces across diversified sub-basins, an approach that had not been used by previous studies in the region. Thus, the findings will provide valuable information for decision making pertaining to integrated land use and catchment management in order to realize the enormous benefits of sustainable forest ecosystems. The information will not only be important to the study area, but equally applicable to similar tropical regions

Impact of land use/cover changes on soil erosion in Western Kenya

Koech, RK ORCiD: 0000-0002-0563-6687This study examined the impact of land use/cover changes on soil erosion in western Kenya in the years 1995 and 2017. The study used the GIS-based Revised Universal Soil Loss Equation (RUSLE) modelling approach and remote sensing assessment. The results showed that the average soil loss through sheet, rill and inter-rill soil erosion processes was 0.3 t/ha/y and 0.5 t/ha/y, in the years 1995 and 2017, respectively. Of the total soil loss, farms contributed more than 50%, both in 1995 and 2017 followed by grass/shrub (7.9% in 1995 and 11.9% in 2017), forest (16% in 1995 and 11.4% in 2017), and the least in built-up areas. The highest soil erosion rates were observed in farms cleared from forests (0.84 tons/ha) followed by those converted from grass/shrub areas (0.52 tons/ha). The rate of soil erosion was observed to increase with slope due to high velocity and erosivity of the runoff. Areas with high erodibility in the region are found primarily in slopes of more than 30 degrees, especially in Mt. Elgon, Chereng’anyi hills and Elgeyo escarpments. This study forms the first multi-temporal assessment to explore the extent of soil erosion and seeks to provide a useful knowledge base to support decision-makers in developing strategies to mitigate soil erosion for sustainable crop production

Analysis of spatio-temporal dynamics of land use and cover changes in Western Kenya

Koech, RK ORCiD: 0000-0002-0563-6687The western region of Kenya is experiencing remarkable land changes resulting from population growth and related impacts. The study used remote sensing and GIS techniques to analyze the land use/cover changes in the years 1995, 2001, 2010 and 2017. Multi-spectral Landsat (TM, ETM + and OLI) images were pre-processed and classified using maximum likelihood algorithm in ENVI version 5.4. The overall classification accuracies in all the images were more than 80%. The results revealed major conversions of each land use/land cover type in varying trends and magnitudes. Between 1995 and 2001, there was an increase in built-up areas by 71%, forest cover by 43%, farms by 5%; and decrease in grassland by 47%. By 2017, the built-up areas had increased by 225% and farms by 17%; the forestland, grassland and water reduced by 38, 10 and 11%, respectively. The observed changes are characterized by increased settlements and encroachment of sensitive ecosystems