Jaime Roberto Padilla-MartínezCarola PaulKai HusmannJosé Javier Corral-Rivas...
1-13页
查看更多>>摘要：Multispecies forests have received increased scientific attention,driven by the hypothesis that biodiversity im-proves ecological resilience.However,a greater species diversity presents challenges for forest management and research.Our study aims to develop basal area growth models for tree species cohorts.The analysis is based on a dataset of 423 permanent plots(2,500 m2)located in temperate forests in Durango,Mexico.First,we define tree species cohorts based on individual and neighborhood-based variables using a combination of principal component and cluster analyses.Then,we estimate the basal area increment of each cohort through the gener-alized additive model to describe the effect of tree size,competition,stand density and site quality.The principal component and cluster analyses assign a total of 37 tree species to eight cohorts that differed primarily with regard to the distribution of tree size and vertical position within the community.The generalized additive models provide satisfactory estimates of tree growth for the species cohorts,explaining between 19 and 53 percent of the total variation of basal area increment,and highlight the following results:i)most cohorts show a"rise-and-fall"effect of tree size on tree growth;ii)surprisingly,the competition index"basal area of larger trees"had showed a positive effect in four of the eight cohorts;iii)stand density had a negative effect on basal area increment,though the effect was minor in medium-and high-density stands,and iv)basal area growth was positively correlated with site quality except for an oak cohort.The developed species cohorts and growth models provide insight into their particular ecological features and growth patterns that may support the development of sustainable management strategies for temperate multispecies forests.
查看更多>>摘要：Background:No studies have documented long-term trends in aboveground biomass(AGB)for mixed-dipterocarp forests(MDF),the dominant rain forest type in tropical wet equatorial Asia.In our study,we sought to document such trends over forty years across three sites representing lowland to lower montane elevations.Methods:To do this,we established fifty 100 m × 25 m plots in 1978 across three sites sampled along an elevation gradient,identified as mature old-growth forest.We measured trees for diameter at breast height that we iden-tified to species and tagged.We took wood samples to calculate species wood-specific gravity.We re-measured plots in 1998 and again in 2018.Results:We show standing AGB for all sites combined to be 517.52 Mg-ha-1 in 1978,but this declined by 17％over 40 years to 430.11 Mg-ha-1.No differences exist among sites in AGB primarily because of considerable within site variation;but interactions of time with site show declines across sites were not uniform,one remained about the same.Relatively few species represented a high proportion of the AGB with the top five species comprising between 34％and 65％,depending upon site and year sampled.One species,Mesua nagassarium,represented a disproportionately large amount of AGB and decline over time,particularly at the low elevation site.Conclusions:Our results are directly relevant to estimating AGB and standing carbon sequestered in MDF.Our study is the first to demonstrate varying but overall,declining trends in amounts of AGB among forests making predictions of biomass and standing carbon in MDF difficult over wide regions.
查看更多>>摘要：Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decision-making.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to under-estimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.
查看更多>>摘要：Understanding the spatial variation,temporal changes,and their underlying driving forces of carbon sequestra-tion in various forests is of great importance for understanding the carbon cycle and carbon management options.How carbon density and sequestration in various Cunninghamia lanceolata forests,extensively cultivated for timber production in subtropical China,vary with biodiversity,forest structure,environment,and cultural factors remain poorly explored,presenting a critical knowledge gap for realizing carbon sequestration supply potential through management.Based on a large-scale database of 449 permanent forest inventory plots,we quantified the spatial-temporal heterogeneity of aboveground carbon densities and carbon accumulation rates in Cunninghamia lanceolate forests in Hunan Province,China,and attributed the contributions of stand structure,environmental,and management factors to the heterogeneity using quantile age-sequence analysis,partial least squares path modeling(PLS-PM),and hot-spot analysis.The results showed lower values of carbon density and sequestration on average,in comparison with other forests in the same climate zone(i.e.,subtropics),with pronounced spatial and temporal variability.Specifically,quantile regression analysis using carbon accumulation rates along an age sequence showed large differences in carbon sequestration rates among underperformed and outperformed forests(0.50 and 1.80 Mg·ha-1·yr-1).PLS-PM demonstrated that maximum DBH and stand density were the main crucial drivers of aboveground carbon density from young to mature forests.Furthermore,species diversity and geo-topographic factors were the significant factors causing the large discrepancy in aboveground carbon density change between low-and high-carbon-bearing forests.Hotspot analysis revealed the importance of culture at-tributes in shaping the geospatial patterns of carbon sequestration.Our work highlighted that retaining large-sized DBH trees and increasing shade-tolerant tree species were important to enhance carbon sequestration in C.lanceolate forests.
查看更多>>摘要：Alpine treeline ecotones are highly sensitive to climate warming.The low temperature-determined alpine treeline is expected to shift upwards in response to global warming.However,little is known about how temperature interacts with other important factors to influence the distribution range of tree species within and beyond the alpine treeline ecotone.Hence,we used a GF-2 satellite image,along with bioclimatic and topographic variables,to develop an ensemble suitable habitat model based on the species distribution modeling algorithms in Biomod2.We investigated the distribution of suitable habitats for B.ermanii under three climate change scenarios(i.e.,low(SSP126),moderate(SSP370)and extreme(SSP585)future emission trajectories)between two consecutive time periods(i.e.,current-2055,and 2055-2085).By 2055,the potential distribution range of B.ermanii will expand under all three climate scenarios.The medium and high suitable areas will decline under SSP370 and SSP585 scenarios from 2055 to 2085.Moreover,under the three climate scenarios,the uppermost altitudes of low suitable habitat will rise to 2,329 m a.s.l.,while the altitudes of medium and high suitable habitats will fall to 2,201 and 2,051 m a.s.l.by 2085,respectively.Warming promotes the expansion of B.ermanii distribution range in Changbai Mountain,and this expansion will be modified by precipitation as climate warming continues.This interaction between temperature and precipitation plays a significant role in shaping the potential distribution range of B.ermanii in the alpine treeline ecotone.This study reveals the link between environmental factors,habitat distribution,and species distribution in the alpine treeline ecotone,providing valuable insights into the impacts of climate change on high-elevation vegetation,and contributing to mountain biodiversity conservation and sustainable development.
查看更多>>摘要：Global climate change can affect tree growth and carbon sink function by influencing plant carbohydrate synthesis and utilization,while elevation can be used as an ideal setting under natural conditions to simulate climate change effects.The effect of elevation on tree growth may depend on organ type.However,the allocation patterns of nonstructural and structural carbohydrates(NSCs and SCs,respectively)in different tree organs and their response to elevation remain unclear.We selected four dominant tree species,Schima superba,Castanopsis eyrei,Castanopsis fargesii and Michelia maudiae,along an elevation gradient from 609 to 1,207 m in subtropical ever-green broad-leaved forests and analyzed leaf,trunk,and fine root NSCs,carbon(C),nitrogen(N)and phosphorus(P)concentrations and the relative abundance of SCs.Leaf NSCs increased initially and then decreased,and trunk NSCs increased with increasing elevation.However,root NSCs decreased with increasing elevation.The relative abundance of SCs in leaves and trunks decreased,while the relative abundance of root SCs increased with increasing elevation.No significant correlations between SCs and NSCs in leaves were detected,while there were negative correlations between SCs and NSCs in trunks,roots,and all organs.Hierarchical partitioning analysis indicated that plant C/N and C/P were the main predictors of changes in SCs and NSCs.Our results suggest that tree organs have divergent responses to elevation and that increasing elevation will inhibit the aboveground part growth and enhance the root growth of trees.A tradeoff between the C distribution used for growth and storage was confirmed along the elevation gradient,which is mainly manifested in the"sink"organs of NSCs.Our results provide insight into tree growth in the context of global climate change scenarios in subtropical forest ecosystems.
查看更多>>摘要：Ongoing encroachment is driving recent alpine shrubline dynamics globally,but the role of shrub-shrub in-teractions in shaping shrublines and their relationships with stem density changes remain poorly understood.Here,the size and age of shrubs from 26 Salix shrubline populations along a 900-km latitudinal gradient(30°-38° N)were measured and mapped across the eastern Tibetan Plateau.Point pattern analyses were used to quantify the spatial distribution patterns of juveniles and adults,and to assess spatial associations between them.Mean intensity of univariate and bivariate spatial patterns was related to biotic and abiotic variables.Bivariate mark correlation functions with a quantitative mark(shrub height,basal stem diameter,crown width)were also employed to investigate the spatial relationships between shrub traits of juveniles and adults.Structural equation models were used to explore the relationships among conspecific interactions,patterns,shrub traits and recruitment dynamics under climate change.Most shrublines showed clustered patterns,suggesting the existence of conspecific facilitation.Clustered patterns of juveniles and conspecific interactions(potentially facilitation)tended to intensify with increasing soil moisture stress.Summer warming before 2010 triggered positive effects on population interactions and spatial patterns via increased shrub recruitment.However,summer warming after 2010 triggered negative effects on interactions through reduced shrub recruitment.Therefore,shrub recruitment shifts under rapid climate change could impact spatial patterns,alter conspecific interactions and modify the direction and degree of shrublines responses to climate.These changes would have profound implications for the stability of alpine woody ecosystems.
查看更多>>摘要：The structure of plant communities at local scales depends on both the spatial heterogeneity of abiotic envi-ronmental factors and the biotic interactions within the community.However,although environmental filtering due to microtopographic heterogeneity and resource competition among plants caused by spatial variation in tree density and size are considered to be very important in explaining the mechanisms of community assembly,their effects on the processes of individual mortality and recruitment in natural forest regeneration,as well as their relative contributions,are still poorly understood.To address this,we established a 12-ha permanent plot in a subtropical evergreen broad-leaved forest area and measured microtopographic variables such as elevation,slope,aspect,and terrain position index(TPI)using a total station.We monitored the individual mortality and recruitment in forest natural regeneration through repeated surveys at 5-year intervals.We fitted spatial covariance models to jointly use multiple factors from three groups of variables(microtopographic effect,neighborhood density effects,neighborhood size effects)as explanatory variables to analyze their roles in driving the mortality and recruitment of all individual and 12 dominant species in forest natural regeneration at the neighborhood scale.Our results show that:(1)In the crucial early stages of secondary forest restoration,natural regeneration is influenced by a synergy of environmental filtering,due to microtopographic heterogeneity,and resource competition among plants.(2)For distinct species responses,evergreen dominant species'mortality is largely explained by neighborhood effects,while deciduous species are more affected by topographic factors.Furthermore,the adverse effects of larger conspecific trees on younger trees indicate a pattern of competitive pressure leading to mortality among regenerating trees,such pattern emphasis the influence of parent trees on natural regeneration.(3)As trees grow,their interaction with these stressors evolves,suggesting a shift in their resource acquisition strategies and response to neighborhood effects and environmental factors.Despite these changes,the relative importance of topographic factors in determining survival and recruitment success remains constant.This research highlights the importance of considering both environmental and neighborhood effects in forest management,particularly in early secondary forest restoration.
查看更多>>摘要：Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management ap-proaches,enhancing forest fire warnings and emergency response capabilities,and accurately budgeting potential carbon emissions resulting from fires.However,due to the unavailability of spatial information technology,such databases are extremely difficult to build reliably and completely in the non-satellite era.This study presented an improved forest fire risk reconstruction framework that integrates a deep learning-based time series prediction model and spatial interpolation to address the challenge in Sichuan Province,southwestern China.First,the forest fire danger index(FFDI)was improved by supplementing slope and aspect information.We compared the per-formances of three time series models,namely,the autoregressive integrated moving average(ARIMA),Prophet and long short-term memory(LSTM)in predicting the modified forest fire danger index(MFFDI).The best-performing model was used to retrace the MFFDI of individual stations from 1941 to 1970.Following this,the Anusplin spatial interpolation method was used to map the distributions of the MFFDI at five-year intervals,which were then subjected to weighted overlay with the distance-to-river layer to generate forest fire risk maps for reconstructing the forest fire danger database.The results revealed LSTM as the most accurate in fitting and predicting the historical MFFDI,with a fitting determination coefficient(R2)of 0.709,mean square error(MSE)of 0.047,and validation R2 and MSE of 0.508 and 0.11,respectively.Independent validation of the predicted forest fire risk maps indicated that 5 out of 7 historical forest fire events were located in forest fire-prone areas,which is higher than the results determined from the original FFDI(2 out of 7).This proves the effectiveness of the improved MFFDI and indicates a high level of reliability of the historical forest fire risk reconstruction method proposed in this study.
查看更多>>摘要：Volume is an important attribute used in many forest management decisions.Data from 83 fixed-area plots located in central New Brunswick,Canada,are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer's(1967)volume equation.When density was included in the models(Volume=f(Diameter,Height,Density))choice of diameter measure was more important than choice of height measure.When density was not included(Volume=f(Diameter,Height)),the opposite was true.For models with density included,moment-based estimators of stand diameter and height performed better than all other measures.For models without density,largest tree estimators of stand diameter and height performed better than other measures.The overall best equation used quadratic mean diameter,Lorey's height,and density(root mean square error=5.26 m3·ha-1;1.9％relative error).The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha(root mean square error=32.08 m3.ha-1;11.8％relative error).The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.
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维普