Forest Health Monitoring and Forest Inventory Analysis Programs Monitor Climate Change Effects in Forest Ecosystems

The Forest Health Monitoring (FHM) and Forest Inventory and Analyses (FIA) programs are integrated biological monitoring systems that use nationally standardized methods to evaluate and report on the health and sustainability of forest ecosystems in the United States. Many of the anticipated changes in forest ecosystems from climate change were also issues addressed in sections of FHM's National Technical Report 1991 to 1998. The integrated FHM and FIA monitoring systems are currently establishing baseline conditions (status and change) in most States for many of the expected effects, and are projected to have full implementation for all States and Territories in 2003. These monitoring systems utilize a broad suite of indicators of key ecosystem components and processes that are responsive to many biotic and abiotic stressors, including those anticipated from climate change. These programs will contribute essential information for many decades for many of the anticipated changes in forest ecosystem from increasing carbon dioxide concentrations, changing climatic scenarios, and extreme weather events that are probable in the next 30 to 100 years.     

Mapping forest vegetation patterns in an Atlantic-Mediterranean transitional area by integration of ordination and geostatistical techniques

Aims Forest vegetation variability may be explained by the complex interplay among several spatial structuring factors, including climate and topography. We modelled the spatial variability of forest vegetation assemblages and significant environmental variables along a complex environmental gradient or coenocline to produce a detailed cartographic database portraying the distribution of forests along it.Methods We combined an analysis of ordination coenoclines with kriging over 772 field data plots from the third Spanish National Forest Inventory in an Atlantic–Mediterranean transitional area (northern Spain).Important findings The best fitted empirical semivariogram revealed a strong spatial structure of forest species composition along the complex environmental gradient considered (the climatic–topographic gradient from north to south). The steady and gradual increase of semivariance with a marked lag distance indicates a gradual turnover of forest assemblages according to the climatic–topographic variations (regional or local). Two changes in the slope of the semivariogram suggest the existence of two different scales of spatial variation. The interpolation map by Kriging of forest vegetation assemblages along the main coenocline shows a clear spatial distribution pattern of trees and shrubs in accordance with the spatial variation of significant environmental variables. We concluded that the multivariate geostatistical approach is a suitable technique for spatial analysis of forest systems employing data from national forest inventories based on a regular network of field plots. The development of an assortment of maps describing changes in vegetation assemblages and variation in environmental variables is expected to be a suitable tool for an integrated forest management and planning.     

An additive edge correction for the influence potential of trees

The influence potential on a quadrat (IPQ) is an index for measuring the ecological effect that trees have on understory vegetation observed in a quadrat of a plot. IPQ is defined as the sum of the effect of every trees in the plot, where the effect depends on the size of the tree and the distance between the tree and the quadrat. Since only the trees in the plot have been observed and not the trees outside the plot, the true IPQ may be underestimated. Existing edge corrections are not appropriate for this case. We propose a correction that consists of adding the expected IPQ due to effects of trees outside the plot to the observed IPQ. The expectation is obtained by applying the Campbell theorem for stationary marked point processes. Data from the 1985-86 National Forest Inventory of Finland was used to calculate IPQ for six quadrats systematically allocated to each of 1240 plots. The implementation of the correction for this data is described. The distributions of IPQ with and without the correction proved the existence of edge effects and the effectiveness of the correction to eliminate the bias. This method has the potential to be applied to other additive functions.     

Species are not most abundant in the centre of their geographic range or climatic niche

The pervasive idea that species should be most abundant in the centre of their geographic range or centre of their climatic niche is a key assumption in many existing ecological hypotheses and has been declared a general macroecological rule. However, empirical support for decreasing population abundance with increasing distance from geographic range or climatic niche centre (distance–abundance relationships) remains fairly weak. We examine over 1400 bird, mammal, fish and tree species to provide a thorough test of distance–abundance relationships, and their associations with species traits and phylogenetic relationships. We failed to detect consistent distance–abundance relationships, and found no association between distance–abundance slope and species traits or phylogenetic relatedness. Together, our analyses suggest that distance–abundance relationships may be rare, difficult to detect, or are an oversimplification of the complex biogeographical forces that determine species spatial abundance patterns.     

Implementing REDD+ in Papua New Guinea: Can biodiversity indicators be effectively integrated in PNG's National Forest Inventory?

UNFCCC's “Cancun safeguards” (COP 16, 2010) provide a strong call for comprehensive steps to prevent harm to biodiversity from Reducing Emissions from Deforestation and forest Degradation (REDD+) activities and to support its conservation. However, as non-binding “principles” and due to their general wording, they are not operational in the present form. Additionally, the scientific literature on biodiversity monitoring for REDD+ is still very limited, particularly when it comes to REDD+ in tropical forests and at the national scale. Whereas some authors suggest that biodiversity integration can be achieved by means of standardised protocols and techniques, others consider that an effective monitoring of biodiversity in tropical forests at the national scale may be an impossible task to achieve in a cost-effective way. However, recent research offers some functional approaches to tackle the many challenges involved. This paper explores the perspectives and limits of developing and effectively incorporating appropriate biodiversity objectives and indicators in Papua New Guinea's multipurpose National Forest Inventory (PNG's NFI). The PNG's NFI is currently being designed under the UN-REDD programme as a key component of the National Forest Monitoring System that PNG is required to establish in order to participate in a future REDD+ mechanism. We conclude that the challenge cannot be effectively tackled only at the design stage of the NFI, as it needs to address a number of issues related to different stages of the REDD+ preparedness process:

• If biodiversity integration is carried out directly at the NFI stage, it will need to rely on proxies derived from indicators designed to monitor carbon stock change;

• At the planning stage, a carbon–biodiversity overlay map analysis would allow for a preliminary selection of areas of high biodiversity that could be threatened by REDD+ activities either directly or indirectly through “leakage”;

• During the implementation stage, the selection could be refined by identifying a sub-sample of sites where forests are undergoing the greatest changes;

• A comprehensive biodiversity monitoring programme involving field measurements of key species could only be designed once the priority areas have been clearly defined and limited in both number and size.

     

Tree height–diameter allometry across the United States

The relationship between tree height and diameter is fundamental in determining community and ecosystem structure as well as estimates of biomass and carbon storage. Yet our understanding of how tree allometry relates to climate and whole organismal function is limited. We used the Forest Inventory and Analysis National Program database to determine height–diameter allometries of 2,976,937 individuals of 293 tree species across the United States. The shape of the allometric relationship was determined by comparing linear and nonlinear functional forms. Mixed‐effects models were used to test for allometric differences due to climate and floristic (between angiosperms and gymnosperms) and functional groups (leaf habit and shade tolerance). Tree allometry significantly differed across the United States largely because of climate. Temperature, and to some extent precipitation, in part explained tree allometric variation. The magnitude of allometric variation due to climate, however, had a phylogenetic signal. Specifically, angiosperm allometry was more sensitive to differences in temperature compared to gymnosperms. Most notably, angiosperm height was more negatively influenced by increasing temperature variability, whereas gymnosperm height was negatively influenced by decreasing precipitation and increasing altitude. There was little evidence to suggest that shade tolerance influenced tree allometry except for very shade‐intolerant trees which were taller for any given diameter. Tree allometry is plastic rather than fixed and scaling parameters vary around predicted central tendencies. This allometric variation provides insight into life‐history strategies, phylogenetic history, and environmental limitations at biogeographical scales.     

基于森林资源清查数据估算中国森林生物量固碳潜力

森林是全球陆地生态系统中最大的植被碳库和碳汇,森林固碳被认为是各国抵减工业温室气体排放的重要途径,通过森林资源清查数据编制国家温室气体清单也是大多数国家的选择。但是,由于森林固碳本身的复杂性,未来通过森林固碳能够抵消多少工业碳排放往往并不清楚。如何基于森林资源清查数据估算森林的固碳潜力,仍是一个值得深入研究的领域。通过能够公开获得的森林资源清查数据,分起源(人工林和天然林)、36个树种、5个林龄组建立了国家和省两级森林蓄积量年增长量模型,并以第六次森林资源清查期为起点,估算了基线情景(造林、管理、干扰、气候、采伐等条件不变)下2001—2200年前中国森林生物量变化和中国森林生物量固碳潜力。结果认为,天然林蓄积量年增长量一般低于人工林;多数天然林树种的蓄积量增长过程符合理论上认为的中间高、前后低的逻辑斯蒂曲线形式,即中龄林、近熟林、成熟林年增长量高,幼龄林和过熟林年增长量低;人工林蓄积量增长过程多为前期高、后期低的形式,即幼龄林、中龄林和近熟林年增长量高,成熟林和过熟林年增长量低。基线情景下中国森林碳容量为12.82 Pg C,其中人工林为6.6 Pg C,天然林为6.2 Pg C;相对于2001年碳储量来说,到2200年中国森林生物量固碳潜力为6.52 Pg C。综合已有研究认为,中国森林生物量固碳潜力为6.52—13.57 Pg C。本研究可以用于优化森林生长过程模型,为我国森林管理政策的制定提供参考。     

Evidence of non‐stationary relationships between climate and forest responses: Increased sensitivity to climate change in Iberian forests

Climate and forest structure are considered major drivers of forest demography and productivity. However, recent evidence suggests that the relationships between climate and tree growth are generally non‐stationary (i.e. non‐time stable), and it remains uncertain whether the relationships between climate, forest structure, demography and productivity are stationary or are being altered by recent climatic and structural changes. Here we analysed three surveys from the Spanish Forest Inventory covering c. 30 years of information and we applied mixed and structural equation models to assess temporal trends in forest structure (stand density, basal area, tree size and tree size inequality), forest demography (ingrowth, growth and mortality) and above‐ground forest productivity. We also quantified whether the interactive effects of climate and forest structure on forest demography and above‐ground forest productivity were stationary over two consecutive time periods. Since the 1980s, density, basal area and tree size increased in Iberian forests, and tree size inequality decreased. In addition, we observed reductions in ingrowth and growth, and increases in mortality. Initial forest structure and water availability mainly modulated the temporal trends in forest structure and demography. The magnitude and direction of the interactive effects of climate and forest structure on forest demography changed over the two time periods analysed indicating non‐stationary relationships between climate, forest structure and demography. Above‐ground forest productivity increased due to a positive balance between ingrowth, growth and mortality. Despite increasing productivity over time, we observed an aggravation of the negative effects of climate change and increased competition on forest demography, reducing ingrowth and growth, and increasing mortality. Interestingly, our results suggest that the negative effects of climate change on forest demography could be ameliorated through forest management, which has profound implications for forest adaptation to climate change.     

Functional traits and climate drive interspecific differences in disturbance-induced tree mortality

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm-sensitive species had a high height-dbh ratio, low wood density and high maximum growth, while fire-sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales.     

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees

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基于人工神经网络与空间仿真模拟的区域森林碳估算比较——以龙泉市为例

森林是生态系统的重要组成部分,准确估算森林碳储量及其分布对于评价森林生态系统的功能具有重要意义。以龙泉市为研究区,利用2009年99个森林资源清查样地数据和同年度Landsat TM影像数据,采用高斯序列协同仿真(SGCS)与BP神经网络方法(BPNN)分别模拟森林地上部分碳密度及其分布,并进行了对比分析。随机将样本数据分成70个建模样本和29个检验样本。通过模型检验,BP神经网络预测值与实测值的相关性达到0.67,相对均方根误差为0.63,空间仿真方法预测值与实测值的相关性为0.68,相对均方根误差为0.63,空间仿真方法预测能力略高于神经网络方法。仿真结果表明,基于BP神经网络模拟的森林碳总量为11042990 Mg,平均碳密度为36.10 Mg/hm2,总体森林碳密度均值高于样地平均值8.82%。基于空间仿真模拟的森林碳总量为11388657 Mg,平均碳密度为37.23 Mg/hm2,总体森林碳密度均值高于样地平均值9.40%。对比分析可知:高斯协同仿真模拟和BP神经网络虽然在碳总量估算值上与抽样数据估计值相近,但两种方法在估测值的频率分布以及研究区碳分布上有较大的差异。与BP神经网络相比,序列高斯协同模拟结果更接近系统抽样样地实测值,全部样地预测值与实测值的相关性达到0.75,在估计区域森林碳空间分布上有明显优势。在碳密度值域与频率分布方面,序列高斯协同模拟结果分布更合理。综上所述,序列高斯协同模拟在森林碳空间估计方面要优于BP神经网络。     

Travelling to a former sea floor: colonization of forests by understorey plant species on land recently reclaimed from the sea

Questions: What are important forest characteristics determining colonization of forest patches by forest understorey species? Location: Planted forests on land recently reclaimed from the sea, the Netherlands. Methods: We related the distribution of forest specialist species in the understorey of 55 forests in Dutch IJsselmeer polders to the following forest characteristics: age, area, connectivity, distance to mainland (as a proxy for distance to seed source) and path density. We used species of the Fraxino‐Ulmetum association for the Netherlands as reference for species that could potentially occur in the study area. Results: Area and age of the surveyed forests explained a large part of the variation in overall species composition and species number of forest plant species. The importance of connectivity and distance to the mainland of forest habitats became apparent only at a more detailed level of dispersal groups and individual species. The importance of forest parameters differed between dispersal groups and also between individual species. After 60 years, 75% of the potential pool of wind‐dispersed species has reached the polders, whereas this was only 50% for species lacking specific adaptations to long‐distance dispersal. However, the average percentage of successful colonizing species present per forest was substantially lower, ranging from 15 to 37%. Conclusions: The data strongly suggest that the colonization process in polder forests is still in its initial phase, during which easily dispersed species dominate the vegetation. Colonization success of common species that lack adaptations to long‐distance dispersal is affected by spatial configuration of the forests, and most rare species that could potentially occur in these forests are still absent. Implications for conservation of rare species in fragmented landscapes are discussed.     

中国森林生物多样性动态的灰色预测

我国森林生物多样性动态分析具有少数据和贫信息带来的灰色不确定性, 灰色系统理论是进行相关研究的重要工具。在前人工作的基础上, 作者根据PSR(Pressure-State-Response)模型计算得到1973–1998年间我国5次森林资源连续清查期内的森林生物多样性指数序列, 包括压力指数、森林生态系统多样性指数和森林物种多样性指数, 以及由这3个指数建立的森林生物多样性总指数; 并建立了各个指数的GM(1,1)灰色模型, 预测我国森林生物多样性的动态。结果表明, 在未来2个森林资源连续清查期(大约10年), (1) 我国森林生物多样性指数将继续增加, 且与过去5个森林资源连续清查期相比其增加速度将有所提高; (2) 压力指数将维持继续增大的趋势不变; (3) 森林生态系统多样性指数将维持在当前水平, 有轻微波动; (4) 森林物种多样性指数将继续增加, 但与过去5个森林资源连续清查期相比其增加速度将渐趋平缓。研究表明, 根据PSR模型建立我国森林生物多样性动态的灰色预测模型, 适合我国森林资源管理的实际需要。     

Forest disturbance and recovery in Peruvian Amazonia

Amazonian forests function as biomass and biodiversity reservoirs, contributing to climate change mitigation. While they continuously experience disturbance, the effect that disturbances have on biomass and biodiversity over time has not yet been assessed at a large scale. Here, we evaluate the degree of recent forest disturbance in Peruvian Amazonia and the effects that disturbance, environmental conditions and human use have on biomass and biodiversity in disturbed forests. We integrate tree-level data on aboveground biomass (AGB) and species richness from 1840 forest plots from Peru's National Forest Inventory with remotely sensed monitoring of forest change dynamics, based on disturbances detected from Landsat-derived Normalized Difference Moisture Index time series. Our results show a clear negative effect of disturbance intensity tree species richness. This effect was also observed on AGB and species richness recovery values towards undisturbed levels, as well as on the recovery of species composition towards undisturbed levels. Time since disturbance had a larger effect on AGB than on species richness. While time since disturbance has a positive effect on AGB, unexpectedly we found a small negative effect of time since disturbance on species richness. We estimate that roughly 15% of Peruvian Amazonian forests have experienced disturbance at least once since 1984, and that, following disturbance, have been increasing in AGB at a rate of 4.7 Mg ha⁻¹ year⁻¹ during the first 20 years. Furthermore, the positive effect of surrounding forest cover was evident for both AGB and its recovery towards undisturbed levels, as well as for species richness. There was a negative effect of forest accessibility on the recovery of species composition towards undisturbed levels. Moving forward, we recommend that forest-based climate change mitigation endeavours consider forest disturbance through the integration of forest inventory data with remote sensing methods.     

Quantifying carbon storage and sequestration by native and non-native forests under contrasting climate types

Non-native trees may have significant impacts on the carbon sink capacity of forested lands. However, large-scale patterns of the relative capacity of native and non-native forests to uptake and store carbon remain poorly described in the literature, and this information is urgently needed to support management decisions. In this study, we analyzed 17,065 plots from the Spanish Forest Inventory (covering c. 30 years) to quantify carbon storage and sequestration of natural forests and plantations of native and non-native trees under contrasting climate types, while controlling for the effects of environmental factors (forest structure, climate, soil, topography, and management). We found that forest origin (non-native vs. native) highly influenced carbon storage and sequestration, but such effect was dependent on climate. Carbon storage was greater in non-native than in native forests in both wet and dry climates. Non-native forests also had greater carbon sequestration than native ones in the wet climate, due to higher carbon gains by tree growth. However, in the dry climate, native forests had greater carbon gains by tree ingrowth and lower carbon loss by tree mortality than non-native ones. Furthermore, forest type (classified by the dominant species) and natural forests versus tree plantations were important determinants of carbon storage and sequestration. Native and non-native Pinus spp. forests had low carbon storage, whereas non-native Eucalyptus spp. forests and native Quercus spp., Fagus sylvatica, and Eurosiberian mixed forests (especially not planted ones) had high carbon storage. Carbon sequestration was greatest in Eucalyptus globulus, Quercus ilex, and Pinus pinaster forests. Overall, our findings suggest that the relative capacity of native and non-native forests to uptake and store carbon depends on climate, and that the superiority of non-native forests over native ones in terms of carbon sequestration declines as the abiotic filters become stronger (i.e., lower water availability and higher climate seasonality).     

Dual impacts of climate change: forest migration and turnover through life history

Tree species are predicted to track future climate by shifting their geographic distributions, but climate‐mediated migrations are not apparent in a recent continental‐scale analysis. To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance‐climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large‐scale tree migration. Taken together, this juvenile–adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.