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Estimation of bioclimatic variables of Mongolia derived from remote sensing data

Frontiers of Earth Science 2022年第2期16卷 323-339页

作者： Munkhdulam OTGONBAYAR Clement ATZBERGER Erdenesukh SUMIYA Sainbayar DALANTAI Jonathan CHAMBERS Institute of Geography and Geoecology Mongolian Academy of Sciences(MAS)Ulaanbaatar 15170Mongolia Institute of Geomatics University of Natural Resources and Life Sciences(BOKU)Vienna 1190Austria School of Arts and Sciences National University of Mongolia(NUM)Ulaanbaatar 14201Mongolia Cooperazione Internazionale Milan 5020151Italy

Global maps of bioclimatic variables currently exist only at very coarse spatial resolution(***).For ecological studies requiring higher resolved information,this spatial resolution is often *** aim of this study is to estimate important bioclimatic variables of Mongolia from Earth Observation(EO)data at a higher spatial resolution of 1 *** analysis used two different satellite time series data sets:land surface temperature(LST)from Moderate Resolution Imaging Spectroradiometer(MODIS),and precipitation(P)from Climate Hazards Group Infrared Precipitation with Stations(CHIRPS).Monthly maximum,mean,and minimum air temperature were estimated from Terra MODIS satellite(collection 6)LST time series product using the random forest(RF)regression *** total precipitation data were obtained from CHIRPS version *** on this primary data,spatial maps of 19 bioclimatic variables at a spatial resolution of 1 km were generated,representing the period *** tested the relationship between estimated bioclimatic variables(SatClim)and WorldClim bioclimatic variables version 2.0(WorldClim)using determination coefficient(R^(2)),root mean square error(RMSE),and normalized root mean square error(nRMSE)and found overall good *** the set of 19 WorldClim bioclimatic variables,17 were estimated with a coefficient of determination(R^(2))higher than 0.7 and normalized RMSE(nRMSE)lower than 8%,confirming that the spatial pattern and value ranges can be retrieved from satellite data with much higher spatial resolution compared to *** the two bioclimatic variables related to temperature extremes(i.e.,annual mean diurnal range and isothermality)were modeled with only moderate accuracy(R^(2) of about 0.4 with nRMSE of about 11%).Generally,precipitation-related bioclimatic variables were closer correlated with WorldClim compared to temperature-related bioclimatic *** overall success of the modeling was attributed to the f

关键词： bioclimatic variables MODIS land surface temperature CHIRPS precipitation

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GIS-based assessment of climate change impacts on forest habitable Aframomum corrorima(Braun)in Southwest Ethiopia coffee forest

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Journal of Mountain Science 2020年第10期17卷 2432-2446页

作者： Ayehu FEKADU Teshome SOROMESSA Bikila Warkineh DULLO Center of Environmental Science Addis Ababa UniversityP.O.Box 1176Addis AbabaEthiopia Department of Plant Biology and Biodiversity Management Addis Ababa UniversityP.O.Box 1176Addis AbabaEthiopia

Climate change is thought to have a greater impact on crops that require particular conditions for their *** Ethiopia is a region where important cash crops such as Coffea arabica and Aframomum corrorima(korerima)*** crops are known to require shade for their growth and *** study was conducted to assess the impacts of climate change on an important but neglected cash crop of *** using GIS-based species distribution *** meteorological data and bioclimatic data from WorldClim were used to map past,present,and future distribution of the crop in the Coffee Forest System of Southwest ***,96 key informants were interviewed and completed questionnaires to complement the distribution *** key informants mapped the history and present occurrences of *** and based on this,ground-truthing survey was *** interpolation method of the Inverse Distance Weighted was used in ArcGIS 10.5 to develop bioclimatic variables for modeling past and present distribution while data from IPCC(AR4)Emissions Scenarios was used for the future occurrence prediction using Principal Component *** best bioclimatic variables were selected and MaxEnt was used to model past,present and future distribution of *** output of our model was validated using Area Under the Curve(AUC)*** and precipitation are the most important environmental variable,then temperature increased by 1.3°C in the past(from 1988 to 2018)while it is predicted to increase further by at least 1.4°C before *** the contrary,precipitation decreased by an average of 10.1 mm from the past while it is predicted to decrease further by 12.5 mm before *** model shows that the area suitable for korerima in 1988 was 20,638.2 ha and it was reduced by half and became 10,545.3 ha in 2018,similarly predicted to shrink into 3225.5 ha by *** findings from the key informants confirm the model res

关键词： Aframomum corrorima Coffee forest bioclimatic variables Suitability GIS MaxEnt

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Modelling the Current and Future Spatial Distribution Area of Shea Tree (<i>Vittelaria paradoxa</i>C. F. Gaertn) in the Context of Climate Change in Benin

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American Journal of Climate Change 2021年第3期10卷 263-281页

作者： Yasminath Judith Follone Avaligbé Faki Oyédékpo Chabi Césaire Paul Gnanglè Orou Daouda Bello Ibouraïma Yabi Léonard Ahoton Aliou Saïdou Integrated Soil and Crop Management Research Unit Laboratory of Soil Sciences Crop Sciences School Faculty of Agronomic Sciences University of Abomey-Calavi Abomey-Calavi Benin Agricultural Research Centre (CRA) of Agonkanmey National Agricultural Research Institute of Benin (INRAB) Cotonou Benin Laboratory Pierre PAGNEY “Climate Water Ecosystem and Development (LACEEDE)” Department of Geography and Land Management (DAGT) Faculty of Human and Social Sciences (FASHS) University of Abomey-Calavi Abomey-Calavi Benin

In Benin, Shea tree (Vitellaria paradoxa) is one of the agroforestry species of great socio-economic importance for local populations. Given the actual variation in the climate parameters, it is necessary to anticipate the future spatial distribution of Shea trees as an adaptation strategy and for designing relevant conservation strategies. The aim of the present research was to evaluate the influence of climate change on the distribution areas of Shea trees in Benin. Occurrence data consisting of geographic coordinates of Shea trees in Benin as well as bioclimatic variables were recorded. Furthemore, additional presence points were collected from the Global Biodiversity Information Facility database website. Current and future environmental data for the study area were obtained from the Africlim website. bioclimatic variables (moisture and temperature), monthly maximum and minimum temperatures and annual rainfall were collected from Worldclim synoptic stations website for the period 1970-2000. The aridity index was created from the potential evapotranspiration (PET) and annual rainfall, using spatial analysis tools of ArcGIS. The impact of current and future environmental conditions on favourable Shea trees’ growing area was assessed following the maximum entropy (MaxEnt) approach under two climate scenarios (RCP 4.5 and RCP 8.5). Under the current climate conditions, 80% of Benin territory and 79% of the protected areas were highly favourable for Shea trees growing and conservation. However, all climate scenarios projected the significant decrease of 14% to 19% of the distribution of favourable for Shea tree growing area and 26% to 30% of the protected areas by 2055 in favour of non-favourable for the trees’ distribution. The protection of habitats favourable for the species development, coupled with a quick restoration of the species through the use of appropriate vegetative propagation techniques are required to sustain the species’ conservation in Benin and mai

关键词： bioclimatic variables Agroforestry Scenario Analysis Adaptation Strategy Conservation

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