基于Deep Forest算法的对虾急性肝胰腺坏死病(AHPND)预警数学模型构建

为预报池塘养殖凡纳对虾(Penaeus vannamei)急性肝胰腺坏死病(AHPND)的发生,自2020年开始,笔者对凡纳对虾养殖区开展了连续监测工作,包括与疾病发生相关的环境理化因子、微生物因子、虾体自身健康状况等18个候选预警因子指标,通过数据标准化处理后分析病原、宿主与环境之间的相关性,对候选预警因子进行筛选,基于Python语言编程结合Deep Forest、Light GBM、XGBoost算法进行数据建模和预测性能评判,仿真环境为Python2.7,以预警因子指标作为输入样本(即警兆),以对虾是否发病指标作为输出结果(即警情),根据输入样本和输出结果各自建立输入数据矩阵和目标数据矩阵,利用原始数据矩阵对输入样本进行初始化,结合函数方程进行拟合,拟合的源代码能利用已知环境、病原及对虾免疫指标数据对目标警情进行预测。最终建立了基于Deep Forest算法的虾体(肝胰腺内)细菌总数、虾体弧菌(Vibrio)占比、水体细菌总数和盐度的4维向量预警预报模型,准确率达89.00%。本研究将人工智能算法应用到对虾AHPND发生的预测预报,相关研究结果为对虾AHPND疾病预警预报建立了预警数学模型,并为对虾健康养殖和疾病防控提供了技术支撑和有力保障。

Dendroclimatological study of Sabina saltuaria and Abies faxoniana in the mixed forests of the Qionglai Mountains,eastern Tibetan Plateau

Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.

Community structure and species diversity dynamics of a subtropical evergreen broad-leaved forest in China:2005 to 2020

Here,we characterize the temporal and spatial dynamics of forest community structure and species diversity in a subtropical evergreen broad-leaved forest in China.We found that community structure in this forest changed over a 15-year period.Specifically,renewal and death of common species was large,with the renewal of individuals mainly concentrated within a few populations,especially those of Aidia canthioides and Cryptocarya concinna.The numbers of individual deaths for common species were concentrated in the small and mid-diameter level.The spatial distribution of community species diversity fluctuated in each monitoring period,showing a more dispersed diversity after the 15-year study period,and the coefficient of variation on quadrats increased.In 2010,the death and renewal of the community and the spatial variation of species diversity were different compared to other survey years.Extreme weather may have affected species regeneration and community stability in our subtropical monsoon evergreen broad-leaved forests.Our findings suggest that strengthening the monitoring and management of the forest community will help better understand the long-and short-term causes of dynamic fluctuations of community structure and species diversity,and reveal the factors that drive changes in community structure.

一种基于KMeans与Random Forest的异常温升捕捉方法

针对线路老化、线路过载的火灾频发问题,分析了线路老化、线路过载与异常温升之间的关联性,以电流值、线缆温度作为输入,利用KMeans聚类算法划分可能存在异常温升的区间,通过Random Forest算法识别线路过载问题,可以提前通知用户整改线路,预防火灾的发生。

Twenty years of population dynamics in European beech-oak forest at their rear range margin anticipate changes in its structure and composition

There is an increasing interest in restoring degraded forests,which occupy half of the forest areas.Among the forms of restoration,passive restoration,which involves the elimination of degrading factors and the free evolution of natural dynamics by applying minimal or no management,is gaining attention.Natural dynamics is difficult to predict due to the influence of multiple interacting factors such as climatic and edaphic conditions,composition and abundance of species,and the successional character of these species.Here,we study the natural dynamics of a mixed forest located in central Spain,which maintained an open forest structure,due to intensive use,until grazing and cutting were banned in the 1960s.The most frequent woody species in this forest are Fagus sylvatica,Quercus petraea,Quercus pyrenaica,Ilex aquifolium,Sorbus aucuparia,Sorbus aria and Prunus avium,with contrasting shade and drought tolerance.These species are common in temperate European deciduous forest and are found here near their southern distribution limit,except for Q.pyrenaica.In order to analyze forest dynamics and composition,three inventories were carried out in 1994,2005 and 2015.Our results show that,despite the Mediterranean influence,the natural dynamics of this forest has been mainly determined by different levels of shade tolerance.After the abandonment of grazing and cutting,Q.pyrenaica expanded rapidly due to its lower shade tolerance,whereas after canopy closure and forest densification,shade-tolerant species gained ground,particularly F.sylvatica,despite its lower drought and late-frost tolerance.If the current dynamics continue,F.sylvatica will overtake the rest of the species,which will be relegated to sites with shallow soils and steep slopes.Simultaneously,all the multi-centennial beech trees,which are undergoing a rapid mortality and decline process,will disappear.

Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: an Izmir Regional Forest Directorate case

Disturbances such as forest fires,intense winds,and insect damage exert strong impacts on forest ecosystems by shaping their structure and growth dynamics,with contributions from climate change.Consequently,there is a need for reliable and operational methods to monitor and map these disturbances for the development of suitable management strategies.While susceptibility assessment using machine learning methods has increased,most studies have focused on a single disturbance.Moreover,there has been limited exploration of the use of“Automated Machine Learning(AutoML)”in the literature.In this study,susceptibility assessment for multiple forest disturbances(fires,insect damage,and wind damage)was conducted using the PyCaret AutoML framework in the Izmir Regional Forest Directorate(RFD)in Turkey.The AutoML framework compared 14 machine learning algorithms and ranked the best models based on AUC(area under the curve)values.The extra tree classifier(ET)algorithm was selected for modeling the susceptibility of each disturbance due to its good performance(AUC values>0.98).The study evaluated susceptibilities for both individual and multiple disturbances,creating a total of four susceptibility maps using fifteen driving factors in the assessment.According to the results,82.5%of forested areas in the Izmir RFD are susceptible to multiple disturbances at high and very high levels.Additionally,a potential forest disturbances map was created,revealing that 15.6%of forested areas in the Izmir RFD may experience no damage from the disturbances considered,while 54.2%could face damage from all three disturbances.The SHAP(Shapley Additive exPlanations)methodology was applied to evaluate the importance of features on prediction and the nonlinear relationship between explanatory features and susceptibility to disturbance.

Evolutionary fingerprint, phylogenetic and forest structure of tropical montane Atlantic cloud forests along an elevation gradient

Environmental conditions can change markedly over geographical distances along elevation gradients,making them natural laboratories to study the processes that structure communities.This work aimed to assess the influences of elevation on Tropical Montane Cloud Forest plant communities in the Brazilian Atlantic Forest,a historically neglected ecoregion.We evaluated the phylogenetic structure,forest structure(tree basal area and tree density)and species richness along an elevation gradient,as well as the evolutionary fingerprints of elevation-success on phylogenetic lineages from the tree communities.To do so,we assessed nine communities along an elevation gradient from 1210 to 2310 m a.s.l.without large elevation gaps.The relationships between elevation and phylogenetic structure,forest structure and species richness were investigated through Linear Models.The occurrence of evolutionary fingerprint on phylogenetic lineages was investigated by quantifying the extent of phylogenetic signal of elevation-success using a genus-level molecular phylogeny.Our results showed decreased species richness at higher elevations and independence between forest structure,phylogenetic structure and elevation.We also verified that there is a phylogenetic signal associated with elevation-success by lineages.We concluded that the elevation is associated with species richness and the occurrence of phylogenetic lineages in the tree communities evaluated in Mantiqueira Range.On the other hand,elevation is not associated with forest structure or phylogenetic structure.Furthermore,closely related taxa tend to have their higher ecological success in similar elevations.Finally,we highlight the fragility of the tropical montane cloud forests in the Mantiqueira Range in face of environmental changes(i.e.global warming)due to the occurrence of exclusive phylogenetic lineages evolutionarily adapted to environmental conditions(i.e.minimum temperature)associated with each elevation range.

Aboveground biomass stocks of species-rich natural forests in southern China are influenced by stand structural attributes,species richness and precipitation

Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.

Stand dynamics of old-growth hemlock forests in central Bhutan are shaped by natural disturbances

Understanding how past disturbances have influenced the development of forests is critical for deciphering their current structure and composition and forecasting future changes.In this study,dendrochronological methods were applied to uncover the disturbance history of old-growth hemlock-dominated forests in central Bhutan.Analysis of tree-ring samples from two old-growth hemlock stands,located in two different topographic settings,identified the importance of gap-phase dynamics in facilitating recruitment and growth releases and producing complex,multi-aged structure s over time.One site showed evidence of a near stand-replacing disturbance in the late 1700s,while the other showed no evide nce of high-severity disturbance at any time over the last 400 years.At both sites low-to medium-severity disturbances,some of which appear to be associated with cyclones originating in the Bay of Bengal,dominated the disturbance regime.The hemlock stands exhibited a significant positive association between cyclone occurrence and growth release events and between recruitment pulses and growth release events.From 1800 to 1970 there was an increase in recruitment of angiosperm tree species at most sites and a corresponding decline in conifer recruitment.Over the past 50 years there has been little new recruitment;this may be due to light limitation in the understory from shade-tolerant angiosperms and bamboo in the lower strata of these stands.Significant variations in disturbance dynamics and recruitment were observed across the study sites,suggesting that other factors,such as topography and climate,may be influencing long-term stand development patterns.This study highlights the complex interplay between historical disturbance regimes and tree recruitment in shaping the age and size structures of old-growth hemlock forests in central Bhutan.It also provides new insights into the dynamics of these forests that can be used to support effective forest conservation and management in the future.

Effects of urbanization and forest type on species composition and diversity,forest characteristics,biomass carbon sink,and their associations in Changchun,Northeast China:implications for urban carbon stock improvement

Differences in forest attributes and carbon sequestration of each organ and layer between broadleaved and conifer forests of central and outer urban areas are not well-defined,hindering the precise management of urban forests and improvement of function.To clarify the effect of two forest types with different urbanization intensities,we determined differences in vegetation composition and diversity,structural traits,and carbon stocks of 152 plots(20 m×20 m)in urban park forests in Changchun,which had the largest green quantity and carbon density effectiveness.We found that 1.1-fold thicker and healthier trees,and 1.6-to 2.0-fold higher,healthier,denser,and more various shrubs but with sparser trees and herbs occurred in the central urban forests(p<0.05)than in the outer forests.The conifer forests exhibited 30–70%obviously higher tree aboveground carbon sequestration(including stem and leaf)and 20%bigger trees,especially in the outer forests(p<0.05).In contrast,1.1-to 1.5-fold higher branch stocks,healthier and more diverse trees were found in broadleaved forests of both the inner and outer forests(p<0.05).Plant size and dominant species had similarly important roles in carbon stock improvement,especially big-sized woody plants and Pinus tabuliformis.In addition,a higher number of deciduous or needle species positively affected the broadleaved forest of the central urban area and conifer forest of the outer urban area,respectively.These findings can be used to guide precise management and accelerate the improvement of urban carbon function in Northeast China in the future.

Sustaining forest biodiversity:Exploring the effect of long-term natural disturbance dynamics on contemporary lichen communities in primary forest ecosystems

In this era of biodiversity loss and climate change,quantifying the impacts of natural disturbance on forest communities is imperative to improve biodiversity conservation efforts.Epiphytic and epixylic lichens are effective forest quality bioindicators,as they are generally long-lived organisms supported by continuity of specific forest structures and their associated microclimatic features.However,how lichen communities respond to the effects of fluctuating historical disturbances remains unclear.Using a dendrochronological approach,this study investigates how natural disturbance dynamics indirectly influence various lichen community metrics in some of Europe's best-preserved primary mixed-beech forests.Mixed modelling revealed that natural historical disturbance processes have decades-long effects on forest structural attributes,which had both congruent and divergent impacts on lichen community richness and composition.Total species richness indirectly benefited from both historical and recent higher-severity disturbances via increased standing dead tree basal area and canopy openness respectively-likely through the presence of both pioneer and late-successional species associated with these conditions.Red-listed species richness showed a dependence on habitat continuity(old trees),and increased with disturbance-related structures(standing dead trees)whilst simultaneously benefiting from periods without severe disturbance events(old trees and reduced deadwood volume).However,if the disturbance occurred over a century in the past,no substantial effect on forest structure was detected.Therefore,while disturbance-mediated forest structures can promote overall richness,threatened species appear vulnerable to more severe disturbance events-a concern,as disturbances are predicted to intensify with climate change.Additionally,the high number of threatened species found reinforce the critical role of primary forest structural attributes for biodiversity maintenance.Hence,we recommend a landscape-scale conservation approach encompassing forest patches in different successional stages to support diverse lichen communities,and the consideration of long-term disturbance dynamics in forest conservation efforts,as they provide critical insights for safeguarding biodiversity in our changing world.

Tree species identity and interaction determine vertical forest structure in young planted forests measured by terrestrial laser scanning

Vertical forest structure is closely linked to multiple ecosystem characteristics,such as biodiversity,habitat,and productivity.Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species.However,the relative importance of species richness,species identity and species interactions for the variation in vertical forest structure remains unclear,mainly because traditional forest inventories do not observe vertical stand structure in detail.Terrestrial laser scanning(TLS),however,allows to study vertical forest structure in an unprecedented way.Therefore,we used TLS single scan data from 126 plots across three experimental planted forests of a largescale tree diversity experiment in Belgium to study the drivers of vertical forest structure.These plots were 9–11years old young pure and mixed forests,characterized by four levels of tree species richness ranging from monocultures to four-species mixtures,across twenty composition levels.We generated vertical plant profiles from the TLS data and derived six stand structural variables.Linear mixed models were used to test the effect of species richness on structural variables.Employing a hierarchical diversity interaction modelling framework,we further assessed species identity effect and various species interaction effects on the six stand structural variables.Our results showed that species richness did not significantly influence most of the stand structure variables,except for canopy height and foliage height diversity.Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites.Species interaction effects were observed to be site-dependent due to varying site conditions and species pools,and rapidly growing tree species tend to dominate these interactions.Overall,our results highlighted the importance of considering both species identity and interaction effects in choosing suitable species combinations for forest management practices aimed at enhancing vertical forest structure.

No generality in biodiversity-productivity relationships along elevation in temperate and subtropical forest landscapes

An improved understanding of biodiversity-productivity relationships(BPRs)along environmental gradients is crucial for effective ecosystem management and biodiversity conservation.The stress-gradient hypothesis suggests that BPRs are stronger in stressful environments compared to more favorable conditions.However,there is limited knowledge regarding the variation of BPRs along elevational gradients and their generality across different landscapes.To study how BPRs change with elevation,we harnessed inventory data on 6,431 trees from152 plots surveyed twice in eight to ten year intervals in mountain forests of temperate Europe and subtropical Asia.We quantified the relationship between aboveground productivity and different biodiversity measures,including taxonomic,functional,and phylogenetic diversity.To elucidate the processes underlying BPRs,we studied the variation of different functional traits along elevation across landscapes.We found no general pattern of BPRs across landscapes and elevations.Relationships were neutral for all biodiversity measures in temperate forests,and negative for taxonomic and functional diversity in subtropical forests.BPRs were largely congruent between taxonomic,functional and phylogenetic diversity.We found only weak support for the stress-gradient hypothesis,with BPRs turning from negative to positive(effect not significant)close to the tree line in subtropical forests.In temperate forests,however,elevation patterns were strongly modulated by species identity effects as influenced by specific traits.The effect of traits such as community-weighted mean of maximum plant height and wood density on productivity was congruent across landscapes.Our study highlights the context-dependence of BPRs across elevation gradients and landscapes.Species traits are key modulating factors of BPRs and should be considered more explicitly in studies of the functional role of biodiversity.Furthermore,our findings highlight that potential trade-offs between conserving biodiversity and fostering ecosystem productivity exist,which require more attention in policy and management.

Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Rapid Increase in Log Populations in Drought-Stressed Mixed-Conifer and Ponderosa Pine Forests in Northern Arizona

Down logs provide important ecosystem services in forests and affect surface fuel loads and fire behavior. Amounts and kinds of logs are influenced by factors such as forest type, disturbance regime, forest management, and climate. To quantify potential short-term changes in log populations during a recent global- climate-change type drought, we sampled logs in mixed-conifer and ponderosa pine (Pinus ponderosa) forests in northern Arizona in 2004 and 2009 (n = 53 and 60 1-ha plots in mixed-conifer and ponderosa pine forests, respectively). Over this short time interval, density of logs, log volume, area covered by logs, and total length of logs increased significantly in both forest types. Increases in all log parameters were greater in mixed-conifer than in ponderosa pine forest, and spatial variability was pronounced in both forest types. These results document rapid increases in log populations in mixed-conifer forest, with smaller changes observed in ponderosa pine forest. These increases were driven by climate-mediated tree mortality which created a pulse in log input, rather than by active forest management. The observed increases will affect wildlife habitat, surface fuel loads, and other ecosystem processes. These changes are likely to continue if climate change results in increased warmth and aridity as predicted, and may require shifts in management emphasis.

Tree structure and diversity shape the biomass of primary temperate mountain forests

Primary forests are spatially diverse terrestrial ecosystems with unique characteristics,being naturally regenerative and heterogeneous,which supports the stability of their carbon storage through the accumulation of live and dead biomass.Yet,little is known about the interactions between biomass stocks,tree genus diversity and structure across a temperate montane primary forest.Here,we investigated the relationship between tree structure(variability in basal area and tree size),genus-level diversity(abundance,tree diversity)and biomass stocks in temperate primary mountain forests across Central and Eastern Europe.We used inventory data from726 permanent sample plots from mixed beech and spruce across the Carpathian Mountains.We used nonlinear regression to analyse the spatial variability in forest biomass,structure,and genus-level diversity and how they interact with plot-level tree age,disturbances,temperature and altitude.We found that the combined effects of genus and structural indices were important for addressing the variability in biomass across different spatial scales.Local processes in disturbance regimes and uneven tree age support forest hete rogeneity and the accumulation of live and dead biomass through the natural regeneration,growth and decay of the forest ecosystem.Structural complexities in basal area index,supporte d by genus-level abundance,positively influence total biomass stocks,which was modulated by tree age and disturbances.Spruce forests showed higher tree density and basal area than mixed beech forests,though mixed beech still contributes significantly to biomass across landscapes.Forest heterogeneity was strongly influenced by complexities in forest composition(tree genus diversity,structure).We addressed the importance of primary forests as stable carbon stores,achieved through structure and diversity.Safeguarding such ecosystems is critical for ensuring the stability of the primary forest,carbon store and biodiversity into the future.

Early response of understory vegetation to the mass dieback of Norway spruce in the European lowland temperate forest

Spruce-dominated forests are commonly exposed to disturbances associated with mass occurrences of bark beetles.The dieback of trees triggers many physical and chemical processes in the ecosystem resulting in rapid changes in the vegetation of the lower forest layers.We aimed to determine the response of non-tree understory vegetation to the mass dieback of Norway spruce(Picea abies)in the first years after the disturbance caused by the European spruce bark beetle(Ips typographus)outbreak.Our study area was the Białowieża Biosphere Reserve covering the Polish part of the emblematic Białowieża Forest,in total 597km^(2).The main data source comprised 3,900 phytosociological relevés(combined spring and summer campaigns)collected from 1,300 systematically distributed forest sites in 2016–2018–the peak years of the bark beetle outbreak.We found that the understory responded immediately to mass spruce dieback,with the most pronounced changes observed in the year of the disturbance and the subsequent year.Shade-tolerant forest species declined in the initial years following the mass spruce dieback,while hemicryptophytes,therophytes,light-demanding species associated with non-forest seminatural communities,as well as water-demanding forest species,expanded.Oxalis acetosella,the most common understory species in the Białowieża Forest,showed a distinct fluctuation pattern,with strong short-term expansion right after spruce dieback,followed by a gradual decline over the next 3–4 years to a cover level 5 percentage points lower than before the disturbance.Thus,our study revealed that mass spruce dieback selectively affects individual herb species,and their responses can be directional and non-directional(fluctuation).Furthermore,we demonstrated that the mass dieback of spruce temporarily increases plant species diversity(α-diversity).

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

Disentangling the effects of management and climate change on habitat suitability for saproxylic species in boreal forests

Forest degradation induced by intensive forest management and temperature increase by climate change are resulting in biodiversity decline in boreal forests.Intensive forest management and high-end climate emission scenarios can further reduce the amount and diversity of deadwood,the limiting factor for habitats for saproxylic species in European boreal forests.The magnitude of their combined effects and how changes in forest management can affect deadwood diversity under a range of climate change scenarios are poorly understood.We used forest growth simulations to evaluate how forest management and climate change will individually and jointly affect habitats of red-listed saproxylic species in Finland.We simulated seven forest management regimes and three climate scenarios(reference,RCP4.5 and RCP8.5)over 100 years.Management regimes included set aside,continuous cover forestry,business-as-usual(BAU)and four modifications of BAU.Habitat suitability was assessed using a speciesspecific habitat suitability index,including 21 fungal and invertebrate species groups.“Winner”and“loser”species were identified based on the modelled impacts of forest management and climate change on their habitat suitability.We found that forest management had a major impact on habitat suitability of saproxylic species compared to climate change.Habitat suitability index varied by over 250%among management regimes,while overall change in habitat suitability index caused by climate change was on average only 2%.More species groups were identified as winners than losers from impacts of climate change(52%–95%were winners,depending on the climate change scenario and management regime).The largest increase in habitat suitability index was achieved under set aside(254%)and the climate scenario RCP8.5(>2%),while continuous cover forestry was the most suitable regime to increase habitat suitability of saproxylic species(up to+11%)across all climate change scenarios.Our results show that close-to-nature management regimes(e.g.,continuous cover forestry and set aside)can increase the habitat suitability of many saproxylic boreal species more than the basic business-as-usual regime.This suggests that biodiversity loss of many saproxylic species in boreal forests can be mitigated through improved forest management practices,even as climate change progresses.

Developing kNN forest data imputation for Catalonia

The combined use of LiDAR(Light Detection And Ranging)scanning and field inventories can provide spatially continuous wall-to-wall information on forest characteristics.This information can be used in many ways in forest mapping,scenario analyses,and forest manage-ment planning.This study aimed to find the optimal way to obtain continuous forest data for Catalonia when using kNN imputation(kNN stands for“k nearest neighbors”).In this method,data are imputed to a certain location from k field-measured sample plots,which are the most similar to the location in terms of LiDAR metrics and topographic variables.Weighted multidimensional Euclidean distance was used as the similarity measure.The study tested two different methods to optimize the distance measure.The first method optimized,in the first step,the set of LiDAR and topographic variables used in the measure,as well as the transformations of these variables.The weights of the selected variables were optimized in the second step.The other method optimized the variable set as well as their transformations and weights in one single step.The two-step method that first finds the variables and their transfor-mations and subsequently optimizes their weights resulted in the best imputation results.In the study area,the use of three to five nearest neighbors was recommended.Altitude and latitude turned out to be the most important variables when assessing the similarity of two locations of Catalan forests in the context of kNN data imputation.The optimal distance measure always included both LiDAR metrics and topographic variables.The study showed that the optimal similarity measure may be different for different regions.Therefore,it was suggested that kNN data imputation should always be started with the optimization of the measure that is used to select the k nearest neighbors.