简介：Background:Overthelastdecades,manyforestsimulatorshavebeendevelopedfortheforestsofindividualEuropeancountries.Theunderlyinggrowthmodelsareusuallybasedonnationaldatasetsofvaryingsize,obtainedfromNationalForestInventoriesorfromlong-termresearchplots.Manyofthesemodelsincludecountry-andlocation-specificpredictors,suchassitequalityindicesthatmayaggregateclimate,soilpropertiesandtopographyeffects.Consequently,itisnotsensibletocomparesuchmodelsamongcountries,anditisoftenimpossibletoapplymodelsoutsidetheregionorcountrytheyweredevelopedfor.However,thereisaclearneedformoregenericallyapplicablebutstilllocallyaccurateandclimatesensitivesimulatorsattheEuropeanscale,whichrequiresthedevelopmentofmodelsthatareapplicableacrosstheEuropeancontinent.ThepurposeofthisstudyistodeveloptreediameterincrementmodelsthatareapplicableattheEuropeanscale,butstilllocallyaccurate.Wecompiledandusedadatasetofdiameterincrementobservationsofover2.3milliontreesfrom10NationalForestInventoriesinEuropeandasetof99potentialexplanatoryvariablescoveringforeststructure,weather,climate,soilandnutrientdeposition.Results:Diameterincrementmodelsarepresentedfor20species/speciesgroups.Selectionofexplanatoryvariableswasdoneusingacombinationofforwardandbackwardselectionmethods.Theexplainedvariancerangedfrom10%to53%dependingonthespecies.Variablesrelatedtoforeststructure(basalareaofthestandandrelativesizeofthetree)contributedmosttotheexplainedvariance,butenvironmentalvariableswereimportanttoaccountforspatialpatterns.Thetypeofenvironmentalvariablesincludeddifferedgreatlyamongspecies.Conclusions:ThepresenteddiameterincrementmodelsarethefirstoftheirkindthatareapplicableattheEuropeanscale.Thisisanimportantsteptowardsthedevelopmentofanewgenerationofforestdevelopmentsimulatorsthatcan

简介：Allometric方程为喇嘛森林发展了，在南部的Benin定位了，韦斯特非洲，被使用估计三种植被类型的碳股票：没受到干扰的森林，降级的森林，和休闲。没受到干扰的森林的碳存货在休闲比那高在降级的森林和3.4次里比那高2.7倍。森林的结构建议单个种类通常在更低的直径班上被集中。碳存货断然与树密度有关被相关到基础区域并且否定地，建议在更高的直径班上的树显著地作出贡献到全部的碳股票。学习证明大树组成一个重要部件在采样途径包括在林地完成精确的碳quantification。从把超过30%喇嘛森林变换成在1946和1987每年等于260,563.17大量碳的年之间的农田的采伐森林的历史的排出物(为生物资源水池的t公司2/year)仅仅。学习解释了生物资源模型和地面真相数据的应用程序估计森林的引用碳存货。