<?xml version='1.0' encoding='UTF-8'?><codeBook xmlns="ddi:codebook:2_5" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="ddi:codebook:2_5 https://ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/codebook.xsd" version="2.5" xml:lang="en"><docDscr><citation><titlStmt><titl xml:lang="en">Distribution of Stem Borer Pests and Natural Enemy Species in Kenya and Tanzania under Current Climatic Conditions (1970-2000) and Different Climate Change Scenarios (2041-2060, 2081-2100)</titl><IDNo agency="DOI">doi:10.60507/FK2/OBGEAR</IDNo></titlStmt><distStmt><distrbtr source="archive">bonndata</distrbtr><distDate>2023-09-18</distDate></distStmt><verStmt source="archive"><version date="2023-09-18" type="RELEASED">1</version></verStmt><biblCit>Ines Jendritzki, 2023, "Distribution of Stem Borer Pests and Natural Enemy Species in Kenya and Tanzania under Current Climatic Conditions (1970-2000) and Different Climate Change Scenarios (2041-2060, 2081-2100)", https://doi.org/10.60507/FK2/OBGEAR, bonndata, V1</biblCit></citation></docDscr><stdyDscr><citation><titlStmt><titl xml:lang="en">Distribution of Stem Borer Pests and Natural Enemy Species in Kenya and Tanzania under Current Climatic Conditions (1970-2000) and Different Climate Change Scenarios (2041-2060, 2081-2100)</titl><IDNo agency="DOI">doi:10.60507/FK2/OBGEAR</IDNo><IDNo agency="ZEF Data Portal">b51b4030-fb4a-41c0-9e50-45a329392418</IDNo></titlStmt><rspStmt><AuthEnty affiliation="Center for Development Research, Department Ecology and Natural Resources Management (ZEF C), University of Bonn">Ines Jendritzki</AuthEnty></rspStmt><prodStmt><software>Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595</software></prodStmt><distStmt><distrbtr source="archive">bonndata</distrbtr><contact affiliation="Center for Development Research, Department Ecology and Natural Resources Management (ZEF C), University of Bonn" email="i.jendritzki@gmx.de">Ines Jendritzki</contact></distStmt><holdings URI="https://doi.org/10.60507/FK2/OBGEAR"/></citation><stdyInfo><subject><keyword xml:lang="en">Other</keyword><topcClas vocab="GEMET - Concepts, version 2.4">agricultural ecology</topcClas><topcClas vocab="GEMET - Concepts, version 2.4">agricultural pest</topcClas><topcClas vocab="GEMET - Concepts, version 2.4">integrated pest control</topcClas><topcClas vocab="GEMET - Concepts, version 2.4">climatic change</topcClas><topcClas vocab="GEMET - Concepts, version 2.4">biological pest control</topcClas></subject><abstract xml:lang="en">The research within the scope of which the presented data was generated was part of the funding initiative ‘Knowledge for Tomorrow-Cooperative Research Project in sub-Saharan Africa on Resource, their Dynamics, and Sustainability’ funded by the Volkswagen Foundation. The overall study aimed at investigating the uncertainties in the effectiveness of biological control of stem borers under different climate change scenarios in Kenya and Tanzania. Using the species distribution modelling approach MaxEnt, the research predicts the current and future distribution of three important lepidopteran stem borer pests of maize in eastern Africa, i.e., Busseola fusca (Fuller, 1901), Chilo partellus (Swinhoe, 1885) and Sesamia calamistis (Hampson, 1910), and two of their parasitoids used for biological control, i.e., Cotesia flavipes (Cameron, 1891) and Cotesia sesamiae (Cameron, 1906). Based on these potential distributions and data collected during household surveys with local farmers in Kenya and Tanzania, future maize yield losses are predicted considering three different Global Circulation Models (GCMs) for four different Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP 3-7.0, SSP5-8.5) and two time periods, i.e., 2041-2060 and 2081-2100. 

The rasters show the species predicted current and future distribution for four different SSPs and time periods 2041-2060 and 2081-2100. The distribution rasters are based on a raster displaying probability of habitat suitability which was converted into binary range maps by application of different threshold levels, i.e., 1) Balance training omission, predicted area and threshold values Cloglog threshold, 2) Maximum training sensitivity plus specificity Cloglog threshold, 3) Equal training sensitivity and specificity Cloglog threshold and 4) 10th percentile training presence Cloglog threshold. Grid cells carrying a probability value above the respective threshold show species presence (cell assigned a value of 1), while grid cells with a probability value below the threshold show species absence (cell assigned a value of 0). Accordingly, 4 presence-absence rasters were obtained for a species current distribution and calculated in their sum, while 12 presence-absence rasters were calculated for each climate change scenario, subsequently also calculated in their sum. The raster therefore specifies grid cells where species distribution is predicted to be more (grid cell carrying a high sum value), or less, likely (grid cell carrying a low cell value).</abstract><sumDscr><timePrd cycle="P1" event="start" date="1970-01-01">1970-01-01</timePrd><timePrd cycle="P1" event="end" date="2000-12-31">2000-12-31</timePrd><collDate cycle="P1" event="start" date="2021-05-01">2021-05-01</collDate><collDate cycle="P1" event="end" date="2021-05-01">2021-05-01</collDate><nation>Kenya</nation><geogCover>Tanzania</geogCover><geoBndBox><westBL>29.416667</westBL><eastBL>41.916667</eastBL><southBL>-11.708333</southBL><northBL>4.625</northBL></geoBndBox></sumDscr><notes>This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={b51b4030-fb4a-41c0-9e50-45a329392418}.&lt;br/>
The naming of files follows the syntax: first letters of species name_SSP_time period_binarysum (= sum of 12 binary range maps)</notes></stdyInfo><method><dataColl><sources/></dataColl><anlyInfo/></method><dataAccs><setAvail/><useStmt/><notes type="DVN:TOU" level="dv">&lt;a href="http://creativecommons.org/licenses/by-sa/4.0">CC BY-SA 4.0&lt;/a></notes></dataAccs><othrStdyMat><othRefs>International Centre for Insect Physiology and Ecology (icipe)</othRefs></othrStdyMat></stdyDscr><otherMat ID="f2623" URI="https://bonndata.uni-bonn.de/catalog/downloads/2623/Map-new.PNG" level="datafile"><labl>Map-new.PNG</labl><txt></txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">image/png</notes></otherMat><otherMat ID="f2622" URI="https://bonndata.uni-bonn.de/catalog/downloads/2622/metadata.xml" level="datafile"><labl>metadata.xml</labl><txt></txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">text/xml</notes></otherMat><otherMat ID="f2624" URI="https://bonndata.uni-bonn.de/catalog/downloads/2624/ZEF_bio_stem-borer-distribution-modelled_tanzania-kenya-ras.zip" level="datafile"><labl>ZEF_bio_stem-borer-distribution-modelled_tanzania-kenya-ras.zip</labl><txt></txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat></codeBook>