简介：Watershedmanagementisanever-evolvingpracticeinvolvingthemanagementofland,water,biota,andotherresourcesinadefinedareaforecological,social,andeconomicpurposes.Inthispaper,weexplorethefollowingquestions:Howhaswatershedmanagementevolved?Whatnewtoolsareavailableandhowcantheybeintegratedintosustainablewatershedmanagement?Toaddressthesequestions,wediscusstheprocessofdevelopingintegratedwatershedmanagementstrategiesforsustainablemanagementthroughtheincorporationofadaptivemanagementtechniquesandtraditionalecologicalknowledge.Weaddressthenumerousbenefitsfromintegrationacrossdisciplinesandjurisdictionalboundaries,aswellastheincorporationoftechnologicaladvancements,suchasremotesensing,GIS,bigdata,andmulti-levelsocial-ecologicalsystemsanalysis,intowatershedmanagementstrategies.WeusethreecasestudiesfromChina,Europe,andCanadatoreviewthesuccessandfailureofintegratedwatershedmanagementinaddressingdifferentecological,social,andeconomicdilemmasingeographicallydiverselocations.Althoughprogresshasbeenmadeinwatershedmanagementstrategies,therearestillnumerousissuesimpedingsuccessfulmanagementoutcomes;manyofwhichcanberemediedthroughholisticmanagementapproaches,incorporationofcutting-edgescienceandtechnology,andcross-jurisdictionalcoordination.Weconcludebyhighlightingthatfuturewatershedmanagementwillneedtoaccountforclimatechangeimpactsbyemployingtechnologicaladvancementsandholistic,cross-disciplinaryapproachestoensurewatershedscontinuetoservetheirecological,social,andeconomicfunctions.Wepresentthreecasestudiesinthispaperasavaluableresourceforscientists,resourcemanagers,governmentagencies,andotherstakeholdersaimingtoimproveintegratedwatershedmanagementstrategiesandmoreefficientlyandsuccessfullyachieveecologicalandsocio-economicmanagementobjectives.

简介：ThispaperestablishedanintegratedstandgrowthmodelofMongolianoak(ISGM_oak)usingthedatafrom61permanentsampleplotsmeasuredin1997and2007.ISGM_oakisagroupofnonlinearsimultaneousequations.Themethodofnonlinearerror-in-variablesimultaneousequationsisusedtoestimatetheparametersofISGMoakwiththestatisticalsoftwareForstat2.0,sotheparameterestimationofthegroupofcorrelatedequationsinISGMoakisunbiasedandtheequationsarecompatible.Modelvalidationusingbootstrapmethodshowedthatboththeaveragerelativeerrorandsquareerrorarelessthan15percent.TheISGM_oakmodelcanbeusedtosimulatethestandgrowthwithdifferentvaluesofsiteindex,standdensityandtodrawstanddensitymanagementdiagramfordecision-making.

简介：当为林地生产提起机械化层次时，林地机械的合适的匹配是重要的。在匹配的过程，林地机械不必仅仅为解决问题的专家知识，而且改进方法。我由在一个分析、层次的过程计算各种各样的林地机器的量的参数的类似建议基于盒子的推理的联合(CBR)(RBR)并且基于规则的推理。我计算了在森林工业过去常启用更好的选择的机械的类似并且设备匹配。我建议基于单个参数重量在申请的进程在被修改的偏差的广场的和调整方法的重量值。在系统设计的过程期间，我提出了一个设计方法知识库并且产生了推理的一张动态网集成森林工业的过程的框架机械选择和重量值调整。这启用推理效率的完全的系统和改进的范围的扩大。我用一个实际例子表明这个方法的有效性和有实行可能。

简介：Background:Bioenergyisre-shapingopportunitiesandimperativesofforestmanagement.Thisstudydemonstrates,throughacasestudyinScotspine(PinussylvestrisL.),howforestbioenergypoliciesaffectstandmanagementstrategies.Methods:Optimizationstudieswereexaminedfor15Scotspinestandsofdifferentinitialstanddensities,sitetypes,andtemperaturesumregionsinFinland.StanddevelopmentwasmodeledusingthePipeQualstandsimulatorcoupledwiththesimulation-optimizationtoolOptiForBioenergytoassessthreeforestbioenergypoliciesonenergywoodharvestfromearlythinnings.Results:Theoptimalsolutionsmaximizingbarelandvalueindicatethatconventionalforestmanagementregimesremainoptimalforsparsestands.Energyharvestsoccurredonlywhenprofitable,ledtolowerfinancialreturns.Aforestbioenergypolicywhichincludedcompulsoryenergywoodharvestingwasoptimalfordenserstands.Atahigherinterestrate(4%),increasingenergywoodpricepostponedenergywoodharvesting.Inaddition,ourresultsshowthatearlythinningsomewhatreducedwoodqualityforstandsinfertilesites.Forlessfertilesites,thechangeswereinsignificant.Conclusions:Aconstraintofprofitableenergywoodharvestisnotrational.Itisoptimaltocarryoutthefirstthinningwithaflexibleforestbioenergypolicydependingonstanddensity.