Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e...Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e.g.,climate change)anthropogenic pressures has benefited considerably from new field-and statistical-techniques.We used machine learning and bibliometric structural topic modelling to identify 20 latent topics comprising four principal fields from a corpus of 16,952 forest ecology/forestry articles published in eight ecology and five forestry journals between 2010 and 2022.Articles published per year increased from 820 in 2010 to 2,354 in 2021,shifting toward more applied topics.Publications from China and some countries in North America and Europe dominated,with relatively fewer articles from some countries in West and Central Africa and West Asia,despite globally important forest resources.Most study sites were in some countries in North America,Central Asia,and South America,and Australia.Articles utilizing R statistical software predominated,increasing from 29.5%in 2010 to 71.4%in 2022.The most frequently used packages included lme4,vegan,nlme,MuMIn,ggplot2,car,MASS,mgcv,multcomp and raster.R was more often used in forest ecology than applied forestry articles.R software offers advantages in script and workflow-sharing compared to other statistical packages.Our findings demonstrate that the disciplines of forest ecology/forestry are expanding both in number and scope,aided by more sophisticated statistical tools,to tackle the challenges of redressing forest habitat loss and the socio-economic impacts of deforestation.展开更多
Ice storms,as important sources of frequent and injurious disturbances,drive forest dynamics in the Northern Hemisphere.However,stand-level differential vulnerability to ice storms and the associated factors that pred...Ice storms,as important sources of frequent and injurious disturbances,drive forest dynamics in the Northern Hemisphere.However,stand-level differential vulnerability to ice storms and the associated factors that predispose forest stands remain unclear.This is particularly concerning in the subtropics where the frequency of ice storms is predicted to increase with global warming.Here we assessed how the impact on three forest stands(early and late secondary-growth forests,and old-growth forests)differed after an extreme ice storm during 20–21 March 2022,and identified the abiotic and biotic factors that determine the damage intensity in the Shennongjia World Natural Heritage Site,a biodiversity conservation hotspot in central China.We found a stand-specific‘middomain effect’where the late secondary-growth forest sustained the most severe damage,the early secondarygrowth forest sustained the least,and the old-growth forest suffered an intermediate amount.‘Crown broken’was the most severe damage type across all three forest stands,although the proportion of‘branch broken’was also high in the old-growth forest.Topography played a significant role in determining the vulnerability of the early secondary-growth forest to severe ice storms whereas the forest structure and composition were important factors in explaining the damage rates in the old-growth forest,although they differed among the damage categories.In contrast,topography,forest structure and composition generally explain the intensity of damage in the late secondary-growth forests.Our results highlight that,in subtropical forests,the intensity of damage caused by severe ice storms and related determining factors are stand-level dependent.We also suggest exploring potential management strategies(e.g.,slow-growing hardwood species that can resist storms should be the main species for reforestation in early secondary-growth forests)to mitigate the risk of future severe ice storms,as well as other wind-related climatic extremes.展开更多
基金financially supported by the National Natural Science Foundation of China(31971541).
文摘Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e.g.,climate change)anthropogenic pressures has benefited considerably from new field-and statistical-techniques.We used machine learning and bibliometric structural topic modelling to identify 20 latent topics comprising four principal fields from a corpus of 16,952 forest ecology/forestry articles published in eight ecology and five forestry journals between 2010 and 2022.Articles published per year increased from 820 in 2010 to 2,354 in 2021,shifting toward more applied topics.Publications from China and some countries in North America and Europe dominated,with relatively fewer articles from some countries in West and Central Africa and West Asia,despite globally important forest resources.Most study sites were in some countries in North America,Central Asia,and South America,and Australia.Articles utilizing R statistical software predominated,increasing from 29.5%in 2010 to 71.4%in 2022.The most frequently used packages included lme4,vegan,nlme,MuMIn,ggplot2,car,MASS,mgcv,multcomp and raster.R was more often used in forest ecology than applied forestry articles.R software offers advantages in script and workflow-sharing compared to other statistical packages.Our findings demonstrate that the disciplines of forest ecology/forestry are expanding both in number and scope,aided by more sophisticated statistical tools,to tackle the challenges of redressing forest habitat loss and the socio-economic impacts of deforestation.
基金supported by the National Natural Science Foundation of China(Nos.32201545,31971541).
文摘Ice storms,as important sources of frequent and injurious disturbances,drive forest dynamics in the Northern Hemisphere.However,stand-level differential vulnerability to ice storms and the associated factors that predispose forest stands remain unclear.This is particularly concerning in the subtropics where the frequency of ice storms is predicted to increase with global warming.Here we assessed how the impact on three forest stands(early and late secondary-growth forests,and old-growth forests)differed after an extreme ice storm during 20–21 March 2022,and identified the abiotic and biotic factors that determine the damage intensity in the Shennongjia World Natural Heritage Site,a biodiversity conservation hotspot in central China.We found a stand-specific‘middomain effect’where the late secondary-growth forest sustained the most severe damage,the early secondarygrowth forest sustained the least,and the old-growth forest suffered an intermediate amount.‘Crown broken’was the most severe damage type across all three forest stands,although the proportion of‘branch broken’was also high in the old-growth forest.Topography played a significant role in determining the vulnerability of the early secondary-growth forest to severe ice storms whereas the forest structure and composition were important factors in explaining the damage rates in the old-growth forest,although they differed among the damage categories.In contrast,topography,forest structure and composition generally explain the intensity of damage in the late secondary-growth forests.Our results highlight that,in subtropical forests,the intensity of damage caused by severe ice storms and related determining factors are stand-level dependent.We also suggest exploring potential management strategies(e.g.,slow-growing hardwood species that can resist storms should be the main species for reforestation in early secondary-growth forests)to mitigate the risk of future severe ice storms,as well as other wind-related climatic extremes.
