Using abundance and habitat variables to identify high conservation value areas for threatened mammals

The present study used abundance and habitat variables to design High Conservation Value Forests for wildlife protection. We considered great apes (Gorilla gorilla gorilla and Pan troglodytes troglodytes) as model species, and we used nest surveys, dietary analysis and botanical inventories to evaluate whether the traditional methods that use abundance data alone were consistent with the survival of the species. We assumed that setting a local priority area for animal conservation can be made possible if at least one variable (abundance or habitat variables) is spatially clustered and that the final decision for a species may depend on the pattern of spatial association between abundance, nesting habitat and feeding habitat. We used Kernel Density Estimation to evaluate the spatial pattern of each biological variable. The results indicate that all three variables were spatially clustered for both gorillas and chimpanzees. The abundance variables of both animal species were spatially correlated to their preferred nesting habitat variables. But while the chimpanzee feeding habitat variable was spatially correlated to the abundance and nesting habitat variables, the same pattern was not observed for gorillas. We then proposed different methods to be considered to design local priority areas for the conservation of each great ape species. Alone, the abundance variable does not successfully represent the spatial distribution of major biological requirements for the survival of wildlife species; we, therefore, recommend the integration of the spatial distribution of their food resources to overcome the mismatch caused by the existence of a biological interaction between congeneric species.     

Connectivity with primary forest determines the value of secondary tropical forests for bird conservation

Species extinctions caused by the destruction and degradation of tropical primary forest may be at least partially mitigated by the expansion of regenerating secondary forest. However, the conservation value of secondary forest remains controversial, and potentially underestimated, since most previous studies have focused on young, single‐aged, or isolated stands. Here, we use point‐count surveys to compare tropical forest bird communities in 20–120‐year‐old secondary forest with primary forest stands in central Panama, with varying connectivity between secondary forest sites and extensive primary forest. We found that species richness and other metrics of ecological diversity, as well as the combined population density of all birds, reached a peak in younger (20‐year‐old) secondary forests and appeared to decline in older secondary forest stands. This counter‐intuitive result can be explained by the greater connectivity between younger secondary forests and extensive primary forests at our study site, compared with older secondary forests that are either (a) more isolated or (b) connected to primary forests that are themselves small and isolated. Our results suggest that connectivity with extensive primary forest is a more important determinant of avian species richness and community structure than forest age, and highlight the vital contribution secondary forests can make in conserving tropical bird diversity, so long as extensive primary habitats are adjacent and spatially connected.Abstract in Spanish is available with online material.     

基于高分辨率遥感影像的北亚热带森林生物量反演

以北亚热带湖北省太子山林场为研究对象,基于高空间分辨率GF-2与SPOT-6卫星影像,提取不同窗口大小下的纹理信息与光谱信息,利用随机森林回归算法,并结合野外实测106块样地的生物量数据,建立不同影像下的太子山林场森林生物量反演模型。结果显示：（1） GF-2和SPOT-6虽然空间分辨率有差异,但是从其不同波段反射率的相关系数（0.75、0.78、0.73、0.61）发现,两种影像的波段反射率具有较高的相关性,说明两者的辐射性能相近;（2）通过分析不同纹理特征对生物量模型的影响,发现均值和对比度纹理参数对生物量反演具有很好的效果。（3）高分辨率的遥感数据在生物量反演中具有较好的表现,且GF-2生物量模型精度（R²=0.88,RMSE=27.11 Mg/hm²）与SPOT-6生物量模型的精度（R²=0.89,RMSE=23.93 Mg/hm²）相近。（4）两种影像对不同森林类型的生物量预测值不存在显著差异,都适合对不同林分类型的生物量进行预测。     

Phylogenetic dimension of tree communities reveals high conservation value of disturbed tropical rain forests

Aim

The conversion of old‐growth tropical forests into human‐modified landscapes threatens biodiversity worldwide, but its impact on the phylogenetic dimension of remaining communities is still poorly known. Negative and neutral responses of tree phylogenetic diversity to land use change have been reported at local and landscape scales. Here, we hypothesized that such variable responses to disturbance depend on the regional context, being stronger in more degraded rain forest regions with a longer history of land use.

Location

Six regions in Mexico and Brazil.

Methods

We used a large vegetation database (6,923 trees from 686 species) recorded in 98 50‐ha landscapes distributed across two Brazilian and four Mexican regions, which exhibit different degrees of disturbance. In each region, we assessed whether phylogenetic alpha and beta diversities were related to landscape‐scale forest loss, the percentage of shade‐intolerant species (a proxy of local disturbance) and/or the relatedness of decreasing (losers) and increasing (winners) taxa.

Results

Contrary to our expectations, the percentage of forest cover and shade‐intolerant species were weakly related to phylogenetic alpha and beta diversities in all but one region. Loser species were generally as dispersed across the phylogeny as winner species, allowing more degraded, deforested and species‐poorer forests to sustain relatively high levels of evolutionary (phylogenetic) diversity.

Main conclusion

Our findings support previous evidence indicating that traits related to high susceptibility to forest disturbances are convergent or have low phylogenetic signal. More importantly, they reveal that the evolutionary value of disturbed forests is (at least in a phylogenetic sense) much greater than previously thought.

     

Carbon cycling and storage in world forests: biome patterns related to forest age

Forest age, which is affected by stand‐replacing ecosystem disturbances (such as forest fires, harvesting, or insects), plays a distinguishing role in determining the distribution of carbon (C) pools and fluxes in different forested ecosystems. In this synthesis, net primary productivity (NPP), net ecosystem productivity (NEP), and five pools of C (living biomass, coarse woody debris, organic soil horizons, soil, and total ecosystem) are summarized by age class for tropical, temperate, and boreal forest biomes. Estimates of variability in NPP, NEP, and C pools are provided for each biome‐age class combination and the sources of variability are discussed. Aggregated biome‐level estimates of NPP and NEP were higher in intermediate‐aged forests (e.g., 30–120 years), while older forests (e.g., >120 years) were generally less productive. The mean NEP in the youngest forests (0–10 years) was negative (source to the atmosphere) in both boreal and temperate biomes (?0.1 and –1.9 Mg C ha^?1 yr^?1, respectively). Forest age is a highly significant source of variability in NEP at the biome scale; for example, mean temperate forest NEP was ?1.9, 4.5, 2.4, 1.9 and 1.7 Mg C ha^?1 yr^?1 across five age classes (0–10, 11–30, 31–70, 71–120, 121–200 years, respectively). In general, median NPP and NEP are strongly correlated (R²=0.83) across all biomes and age classes, with the exception of the youngest temperate forests. Using the information gained from calculating the summary statistics for NPP and NEP, we calculated heterotrophic soil respiration (R_h) for each age class in each biome. The mean R_h was high in the youngest temperate age class (9.7 Mg C ha^?1 yr^?1) and declined with age, implying that forest ecosystem respiration peaks when forests are young, not old. With notable exceptions, carbon pool sizes increased with age in all biomes, including soil C. Age trends in C cycling and storage are very apparent in all three biomes and it is clear that a better understanding of how forest age and disturbance history interact will greatly improve our fundamental knowledge of the terrestrial C cycle.     

Using probability of persistence to identify important areas for biodiversity conservation

Most attempts to identify important areas for biodiversity have sought to represent valued features from what is known of their current distribution, and have treated all included records as equivalent. We develop the idea that a more direct way of planning for conservation success is to consider the probability of persistence for the valued features. Probabilities also provide a consistent basis for integrating the many pattern and process factors affecting conservation success. To apply the approach, we describe a method for seeking networks of conservation areas that maximize probabilities of persistence across species. With data for European trees, this method requires less than half as many areas as an earlier method to represent all species with a probability of at least 0.95 (where possible). Alternatively, for trials choosing any number of areas between one and 50, the method increases the mean probability among species by more than 10%. This improvement benefits the least-widespread species the most and results in greater connectivity among selected areas. The proposed method can accommodate local differences in viability, vulnerability, threats, costs, or other social and political constraints, and is applicable in principle to any surrogate measure for biodiversity value.     

Responses of species abundance distribution patterns to spatial scaling in subtropical secondary forests

To quantify and assess the processes underlying community assembly and driving tree species abundance distributions(SADs) with spatial scale variation in two typical subtropical secondary forests in Dashanchong state‐owned forest farm, two 1‐ha permanent study plots (100‐m × 100‐m) were established. We selected four diversity indices including species richness, Shannon–Wiener, Simpson and Pielou, and relative importance values to quantify community assembly and biodiversity. Empirical cumulative distribution and species accumulation curves were utilized to describe the SADs of two forests communities trees. Three types of models, including statistic model (lognormal and logseries model), niche model (broken‐stick, niche preemption, and Zipf‐Mandelbrodt model), and neutral theory model, were estimated by the fitted SADs. Simulation effects were tested by Akaike's information criterion (AIC) and Kolmogorov–Smirnov test. Results found that the Fagaceae and Anacardiaceae families were their respective dominance family in the evergreen broad‐leaved and deciduous mixed communities. According to original data and random sampling predictions, the SADs were hump‐shaped for intermediate abundance classes, peaking between 8 and 32 in the evergreen broad‐leaved community, but this maximum increased with size of total sampled area size in the deciduous mixed community. All niche models could only explain SADs patterns at smaller spatial scales. However, both the neutral theory and purely statistical models were suitable for explaining the SADs for secondary forest communities when the sampling plot exceeded 40 m. The results showed the SADs indicated a clear directional trend toward convergence and similar predominating ecological processes in two typical subtropical secondary forests. The neutral process gradually replaced the niche process in importance and become the main mechanism for determining SADs of forest trees as the sampling scale expanded. Thus, we can preliminarily conclude that neutral processes had a major effect on biodiversity patterns in these two subtropical secondary forests but exclude possible contributions of other processes.     

森林生态系统土壤保持价值的年内动态

以定位观测数据位基础,选用日雨量模型和通用土壤流失方程,研究了5种森林生态系统土壤保持价值的年内动态。研究表明,季节雨林、次生林、人工橡胶林、阔叶红松林和次生白桦林的土壤保持价值分别为570.29、347.87、174.65、14.31元.hm-.2a-1和8.76元.hm-.2a-1。土壤保持价值各月分配不均,5-10月的土壤保持价值占全年土壤保持价值的80%以上。西双版纳3种森林生态系统土壤保持价值构成中,保持土壤养分的价值高达60%以上。长白山2种森林生态系统的土壤保持价值构成有所不同,阔叶红松林以减少泥沙淤积价值为主,而次生白桦林以保持土壤养分价值为主。土壤保持价值构成中,减少废弃地价值的不足总价值的10%。     

Using landscape history to predict biodiversity patterns in fragmented landscapes

Landscape ecology plays a vital role in understanding the impacts of land‐use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape ‘terrageny’, which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over‐estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human‐modified landscapes.     

Uncertainty in the detection of disturbance spatial patterns in temperate forests

The use of individual-based models in the study of the spatial patterns of disturbances has opened new horizons in forest ecosystem research. However, no studies so far have addressed (i) the uncertainty in geostatistical modelling of the spatial relationships in dendrochronological data, (ii) the number of increment cores necessary to study disturbance spatial patterns, and (iii) the choice of an appropriate geostatistical model in relation to disturbance regime. In addressing these issues, we hope to contribute to advances in research methodology as well as to improve interpretations and generalizations from case studies.We used data from the beech-dominated Žofínský Prales forest reserve (Czech Republic), where we cored 3020 trees on 74 ha. Block bootstrap and geostatistics were applied to the data, which covered five decades with highly different disturbance histories. This allowed us to assess the general behavior of various mathematical models. Uncertainty in the spatial patterns and stability of the models was measured as the length of the 95% confidence interval (CI) of model parameters.According to Akaike Information Criterion (AIC), the spherical model fitted best at the range of ca. 20 m, while the exponential model was best at the range of ca. 60 m. However, the best fitting models were not always the most stable. The stability of models grew significantly with sample size. At <500 cores the spherical model was the most stable, while the Gaussian model was very unstable at <300 cores. The pure nugget model produced the most precise nugget estimate. The choice of model should thus be based on the expected spatial relations of the forest ecosystem under study. Sill was the most stable parameter, with an error of ±6–20% for ≥1110 core series. By contrast, practical range was the most sensitive, with an error of at least ±59%. The estimation of the spatial pattern of severe disturbances was more precise than that of fine-scale disturbances.The results suggest that with a sample size of 1000–1400 cores and a properly chosen model, one reaches a certain precision in estimation that does not increase significantly with growing sample size. It appears that in temperate old-growth forests controlled by fine-scale disturbances, it is necessary to have at least 500 cores to estimate sill, nugget and relative nugget, while to estimate practical range at least 1000 cores are needed. When choosing the best model, the stability of the model should be considered together with the value of AIC. Our results indicate the general limits of disturbance spatial pattern studies using dendrochronological and geostatistical methods, which can be only partially overcome by sample size or sampling design.     

Using neutral landscapes to identify patterns of aggregation across resource points

Many organisms are aggregated within resource patches and aggregated spatially across landscapes with multiple resources. Such patchy distributions underpin models of population regulation and species coexistence, so ecologists require methods to analyse spatially‐explicit data of resource distribution and use. I describe a method for analysing maps of resources and testing hypotheses about how resource distribution influences the distribution of organisms, where resource patches can be described as points in a landscape and the number of organisms on each resource point is known. Using a mark correlation function and the linearised form of Ripley's K‐function, this version of marked point pattern analysis can characterise and test hypotheses about the spatial distribution of organisms (marks) on resource patches (points). The method extends a version of point pattern analysis that has wide ecological applicability, it can describe patterns over a range of scales, and can detect mixed patterns. Statistically, Monte Carlo permutations are used to estimate the difference between the observed and expected values of the mark correlation function. Hypothesis testing employs a flexible neutral landscape approach in which spatial characteristics of point patterns are preserved to some extent, and marks are randomised across points. I describe the steps required to identify the appropriate neutral landscape and apply the analysis. Simulated data sets illustrate how the choice of neutral landscape can influence ecological interpretations, and how this spatially‐explicit method and traditional dispersion indices can yield different interpretations. Interpretations may be general or context‐sensitive, depending on information available about the underlying point pattern and the neutral landscape. An empirical example of caterpillars exploiting food plants illustrates how this technique might be used to test hypotheses about adult oviposition and larval dispersal. This approach can increase the value of survey data, by making it possible to quantify the distribution of resource points in the landscape and the pattern of resource use by species.     

中国潜在植被空间分布格局

潜在植被作为一种与所处立地达到平衡的演替终态,反映的是无人类干扰情况下,立地所能发育形成的最稳定成熟的一种顶极植被类型,是一个地区现状植被的发展趋势。潜在植被的研究能够真实反映气候条件对植被形态变化的影响,是植被-环境分类与关系研究的起点,也是全球变化与陆地生态系统研究的关键。以综合顺序分类法为基本理论基础,在GIS研究方法支持下,利用我国2348个气象台站1961～1990年30a的气候资料,对我国潜在植被类型进行了划分,得出以下结论：（1）分布在我国的潜在植被类型有41类,表现出了我国潜在植被的多样性特征;从面积相对比例来看,我国潜在植被在分布面积上很不均匀,面积最大的寒冷潮湿多雨冻原、高山草甸类分布面积达到1526188km^2,面积最小的炎热微干稀树草原类分布面积仅为13km^2。（2）海拔0～6800m之间,是我国潜在植被主要分布的海拔界限,并且此海拔段植被多样性随海拔变化呈现出一定的规律性,即随海拔增加植被多样性显著下降。（3）我国潜在植被的空间分布很好的体现了三向地带性规律,而决定这种分布的主要原因是太阳辐射的纬度性变化、距离海洋的远近引起水分条件变化以及由海拔高度引起的从基带向上热量和干湿变化。（4）我国潜在植被空间格局在重心分布上,主要表现为空间聚集（P1、P2、P3、P4、P5、P6）和空间线型邻接（L1、L2、L3）两个主要特征。     

FAREAST: a forest gap model to simulate dynamics and patterns of eastern Eurasian forests

Aim This paper describes the forest gap model, FAREAST, its testing and its application to simulating the distribution, composition and dynamics of forests in eastern Eurasia. Location The FAREAST model is tested in north‐eastern China, initially for forests on the elevational gradient of Changbai Mountain, which is located on the border of the People's Republic of China and the Democratic People's Republic of Korea. Subsequently, the model is inspected regionally for other northern Chinese mountains and, finally, it is applied to predict subcontinental forest communities in the Russian Far East. Boreal larch (Larix spp.) forests cover much of the 6 million km² of eastern Eurasia. Mixed broad‐leaved tree species/Korean pine (Pinus koraiensis) forests and spruce/fir (Picea/Abies) forests also occupy considerable areas. Methods The model is tested using three types of information: (1) direct species composition comparisons between simulated and observed mature forests at the same locations; (2) forest type comparisons between simulated and observed forests along altitudinal gradients of several different mountains; and (3) comparison with forest stands in different succession stages of simulated forests. Results Model comparisons with independent data indicate that the FAREAST model is capable of representing many of the broad features of the forests of north‐eastern China. After regional model validation in the north‐eastern region of China, geographical model applications were developed for the forests of the Russian Far East. In simulations at 31 different sites distributed across the entire Russian Far East and including a wide variety of natural forests, the model demonstrates an ability to reproduce observed vegetation pattern. The model simulations are correct with respect to our criteria for 23 of the 31 sites, and there are close results for three other sites. Among the five sites that are incorrectly predicted, four simulations can be corrected by adding a simple assumption to the model for permafrost effects on water balance. Main conclusions Continental‐scale forest cover can be simulated using a forest gap model to represent individual–plant interactions with one another, and their environment, and with parameters that describe the biology of each tree species. It appears that such a model, validated relatively locally (in this case, in north‐eastern China), can then be applied over a much larger region. These results further imply that the Russian Far East forests can be regarded as a natural geographical expansion of north‐eastern Chinese forests. In both regions, forests share not only similar species compositions, but also similar underlying causes of forest successional dynamics.     

中国东部亚热带森林土壤呼吸的时空格局

土壤呼吸是陆地碳循环中仅次于全球总初级生产力的第二大碳通量途径, 揭示土壤呼吸的时空格局对整个陆地碳循环具有重要意义。该文在中国东部亚热带季风气候区, 按纬度梯度由南向北选取深圳梧桐山、杨东山十二度水保护区、宁波天童山3个区域作为研究对象, 于2009年8月至2010年10月测定了不同季节各个区域内代表性植被类型的土壤呼吸速率及地下5 cm处土壤温度, 旨在初步了解中国东部亚热带森林地区土壤呼吸的时空格局及其影响因素。结果显示: 3个区域的土壤呼吸速率均存在显著的季节变化, 其变幅为2.64-6.24 μmol CO₂·m ^-2·s^-1, 总体趋势和地下5 cm处土壤温度的季节变化一致, 均为夏季最高冬季最低; 土壤温度的变化可以解释不同样地土壤呼吸季节变化的58.3%-90.2%; 各样地全年的Q₁₀值从1.56到3.27; 通过离样地最近的气象站点的日平均气温与试验样地地下5 cm处土壤温度之间的线性正相关关系推算出日土壤温度的变化, 利用土壤呼吸速率和地下5 cm处土壤温度之间的指数关系, 估算出各样地全年的土壤CO₂通量为1 077-2 058 g C·m^-2·a^-1, 在全球所有生态系统类型中处于较高水平。