Using Presence-Absence Data to Build and Test Spatial Habitat Models for the Fisher in the Klamath Region, U.S.A.

Abstract: Forest carnivores such as the fisher ( Martes pennanti ) have frequently been the target of conservation concern because of their association in some regions with older forests and sensitivity to landscape-level habitat alteration. Although the fisher has been extirpated from most of its former range in the western United States, it is still found in northwestern California. Fisher distribution, however, is still poorly known in most of this region where surveys have not been conducted. To predict fisher distribution across the region, we created a multiple logistic regression model using data from 682 previously surveyed locations and a vegetation layer created from satellite imagery. A moving-window function in a geographic information system was used to derive landscape-level indices of canopy closure, tree size class, and percent conifer. The model was validated with new data from 468 survey locations. The correct classification rate of 78.6% with the new data was similar to that achieved with the original data set (80.4%). Whereas several fine-scale habitat attributes were significantly correlated with fisher presence, the multivariate model containing only landscape- and regional-scale variables performed as well as one incorporating fine-scale data, suggesting that habitat selection by fishers may be dominated by factors operating at the home-range scale and above. Fisher distribution was strongly associated with landscapes with high levels of tree canopy closure. Regional gradients such as annual precipitation were also significant. At the plot level, the diameter of hardwoods was greater at sites with fisher detections. A comparison of regional fisher distribution with land-management categories suggests that increased emphasis on the protection of biologically productive, low- to mid-elevation forests is important to ensuring the long-term viability of fisher populations.     

Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.     

The importance of spatial autocorrelation,extent and resolution in predicting forest bird occurrence

Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250 km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC > 0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function.     

Triangulation based inclusion probabilities: a design-unbiased sampling approach

A probabilistic sampling approach for design-unbiased estimation of area-related quantitative characteristics of spatially dispersed population units is proposed. The developed field protocol includes a fixed number of 3 units per sampling location and is based on partial triangulations over their natural neighbors to derive the individual inclusion probabilities. The performance of the proposed design is tested in comparison to fixed area sample plots in a simulation with two forest stands. Evaluation is based on a general approach for areal sampling in which all characteristics of the resulting population of possible samples is derived analytically by means of a complete tessellation of the areal sampling frame. The example simulation shows promising results. Expected errors under this design are comparable to sample plots including a much greater number of trees per plot.     

Wood Density as a Conservation Tool: Quantification of Disturbance and Identification of Conservation‐Priority Areas in Tropical Forests

Abstract: Inventories of tree species are often conducted to guide conservation efforts in tropical forests. Such surveys are time consuming, demanding of expertise, and expensive to perform and interpret. Approaches to make survey efforts simpler or more effective would be valuable. In particular, it would be good to be able to easily identify areas of old‐growth forest. The average density of the wood of a tree species is closely linked to its successional status. We used tree inventory data from eastern Borneo to determine whether wood density can be used to quantify forest disturbance and conservation importance. The average density of wood in a plot was significantly and negatively related to disturbance levels, with plots with higher wood densities occurring almost exclusively in old‐growth forests. Average wood density was unimodally related to the diversity of tree species, indicating that the average wood density in a plot might be a better indicator of old‐growth forest than species diversity. In addition, Borneo endemics had significantly heavier wood than species that are common throughout the Malesian region, and they were more common in plots with higher average wood density. We concluded that wood density at the plot level could be a powerful tool for identifying areas of conservation priority in the tropical rain forests of Southeast Asia.     

Mortality of large trees and lianas following experimental drought in an Amazon forest

Severe drought episodes such as those associated with El Ni?o Southern Oscillation (ENSO) events influence large areas of tropical forest and may become more frequent in the future. One of the most important forest responses to severe drought is tree mortality, which alters forest structure, composition, carbon content, and flammability, and which varies widely. This study tests the hypothesis that tree mortality increases abruptly during drought episodes when plant-available soil water (PAW) declines below a critical minimum threshold. It also examines the effect of tree size, plant life form (palm, liana, tree) and potential canopy position (understory, midcanopy, overstory) on drought-induced plant mortality. A severe, four-year drought episode was simulated by excluding 60% of incoming throughfall during each wet season using plastic panels installed in the understory of a 1-ha forest treatment plot, while a 1-ha control plot received normal rainfall. After 3.2 years, the treatment resulted in a 38% increase in mortality rates across all stems >2 cm dbh. Mortality rates increased 4.5-fold among large trees (>30 cm dbh) and twofold among medium trees (10-30 cm dbh) in response to the treatment, whereas the smallest stems were less responsive. Recruitment rates did not compensate for the elevated mortality of larger-diameter stems in the treatment plot. Overall, lianas proved more susceptible to drought-induced mortality than trees or palms, and potential overstory tree species were more vulnerable than midcanopy and understory species. Large stems contributed to 90% of the pretreatment live aboveground biomass in both plots. Large-tree mortality resulting from the treatment generated 3.4 times more dead biomass than the control plot. The dramatic mortality response suggests significant, adverse impacts on the global carbon cycle if climatic changes follow current trends.     

Calibration of the forest vegetation simulator (FVS) model for the main forest species of Ontario,Canada

The forest vegetation simulator (FVS) model was calibrated for use in Ontario, Canada, to predict the growth of forest stands. Using data from permanent sample plots originating from different regions of Ontario, new models were derived for dbh growth rate, survival rate, stem height and species group density index for large trees and height and dbh growth rate for small trees. The dataset included black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.) for the boreal region, sugar maple (Acer saccharum Marsh.), white pine (Pinus strobus L.), red pine (Pinus resinosa Ait.) and yellow birch (Betula alleghaniensis Britton) for the Great Lakes-St. Lawrence region, and balsam fir (Abies balsamea (L.) Mill.) and trembling aspen (Populus tremuloides Michx.) for both regions. These new models were validated against an independent dataset that consisted of permanent sample plots located in Quebec. The new models predicted biologically consistent growth patterns whereas some of the original models from the Lake States version of FVS occasionally did not. The new models also fitted the calibration (Ontario) data better than the original FVS models. The validation against independent data from Quebec showed that the new models generally had a lower prediction error than the original FVS models.     

Contrasting structure and composition of the understory in species-rich tropical rain forests

In large samples of trees > or = 1 cm dbh (more than 1 million trees and 3000 species), in six lowland tropical forests on three continents, we assigned species with >30 individuals to one of six classes of stature at maturity (SAM). We then compared the proportional representation of understory trees (1-2 cm dbh) among these classes. The understory of the three Asian sites was predominantly composed of the saplings of large-canopy trees whereas the African and American sites were more richly stocked with trees of the smaller SAM classes. Differences in class representation were related to taxonomic families that were present exclusively in one continent or another. Families found in the Asian plots but not in the American plot (e.g., Dipterocarpaceae, Fagaceae) were predominantly species of the largest SAM classes, whereas families exclusive to the American plots (e.g., Melastomataceae sensu stricto, Piperaceae, and Malvaceae [Bombacacoidea]) were predominantly species of small classes. The African plot was similar to Asia in the absence of those American families rich in understory species, while similar to America in lacking the Asian families rich in canopy species. The numerous understory species of Africa were chiefly derived from families shared with Asia and/or America. The ratio of saplings (1-2 cm dbh) to conspecific canopy trees (>40 cm dbh) was lower in American plots than in the Asian plots. Possible explanations for these differences include phenology, moisture and soil fertility regimes, phyletic constraints, and the role of early successional plants in forest development. These results demonstrate that tropical forests that appear similar in tree number, basal area, and the family taxonomy of canopy trees nonetheless differ in ecological structure in ways that may impact the ecology of pollinators, dispersers, and herbivores and might reflect fundamental differences in canopy tree regeneration.     

The effects of shifting vegetation mosaics on habitat suitability for coastal dune fauna—a case study on sand lizards (Lacerta agilis)

Encroachment of tall grasses and shrubs in coastal dunes has resulted in loss of vegetation heterogeneity. This is expected to have negative effects on animal diversity. To counteract encroachment and develop structural heterogeneity grazing is a widely used management practice. Here, we aim to functionally interpret changes in vegetation composition and configuration following grazing management on habitat suitability for sand lizards. Aerial photographs taken over a period of 16 years were used to quantify changes in vegetation composition. A GIS-based method was developed to calculate habitat suitability for sand lizards in a spatially explicit manner, encompassing differences in vegetation structure and patch size. From 1987 to 2003 dune vegetation shifted from small patches of moss and sand to larger patches covered by shrubs and grasses. Grazing management did not have any significant effect on the overall level of heterogeneity, measured as habitat suitability for sand lizards. However, on a more local scale highly suitable patches in 1987 were deteriorating whereas unsuitable patches became more suitable in 2003. This inversion results from a broad shift with shrubs being a limiting habitat element in 1987 to sandy patches being the limiting element in 2003. Future changes are believed to negatively impact sand lizards. The habitat suitability model has proven to be a useful tool to functionally interpret changes in coastal dune vegetation heterogeneity from an animal’s perspective. Further research should aim to include multiple species operating on different scale levels to fully capture the natural landscape dynamics.     

Managing Boreal Forest Landscapes for Flying Squirrels

Abstract: Flying squirrel (Pteromys volans) populations have declined severely during the past few decades, and the species has become a focal species in forest management and the conservation debate in Finland. We compared landscape structure around known flying squirrel home ranges with randomly chosen forest sites to determine which landscape patterns characterize the areas occupied by the species in northern Finland. We sought to identify the key characteristics of the landscape that support the remaining flying squirrel populations. We analyzed landscape structure within circular areas with 1- and 3-km radii around 63 forest sites occupied by flying squirrels, and around 96 random sites. We applied stepwise analysis of the landscape structure where landscapes were built up step-by-step by adding patch types in order of their suitability for the flying squirrel. The land-use and forest-resource data for the analysis were derived from multisource national forest inventory and imported to a geographical information system. Landscape patch types were divided into three suitability categories: breeding habitat (mixed spruce-deciduous forests); dispersal habitat ( pine and young forests); and unsuitable habitat ( young sapling stands, open habitats, water). Flying squirrel landscapes contained more suitable breeding habitat patches and were better connected by dispersal habitats than random landscapes. Our results suggest that for the persistence of the flying squirrel, forest managers should 1) maintain a deciduous mixture, particularly in spruce-dominated forests; 2) maintain physical connectivity between optimal breeding habitats; and 3) impose coarse-grained structures on northeastern Finnish landscapes at current levels of habitat availability.     

基于植被指数和神经网络的热带人工林地上蓄积量遥感估测

热带森林作为陆地生态系统的组成成分之一,研究其蓄积量估测对我们了解其在全球碳循环中的地位和作用有很重要的意义.但遥感估测森林生态参数的精度如何,还是个不确定的问题.利用LANDSAT-TM数据,基于森林清查数据和遥感技术,以尾叶桉和加勒比松为例,对中国南方地区人工林蓄积量估测进行了尝试研究.首先,通过测量样方胸径、树高,建立森林蓄积量估算模型.其次,通过对比分析不同植被指数与森林蓄积量之间的关系,选择合适植被指数组合,建立多元回归和神经网络模型.结果表明:单波段TM数据和大多数植被指数与蓄积量相关性并不好.神经网络比回归分析模拟效果好.而多元回归和神经网络模型大大提高预测精度.本研究方法对大面积的森林蓄积量估测具有一定的参考价值.     

Putting Density Back into the Habitat‐Quality Equation: Case Study of an Open‐Nesting Forest Bird

Abstract: Ecological traps and other cases of apparently maladaptive habitat selection cast doubt on the relevance of density as an indicator of habitat quality. Nevertheless, the prevalence of these phenomena remains poorly known, and density may still reflect habitat quality in most systems. We examined the relationship between density and two other parameters of habitat quality in an open‐nesting passerine species: the Ovenbird (Seiurus aurocapilla). We hypothesized that the average individual bird makes a good decision when selecting its breeding territory and that territory spacing reflects site productivity or predation risk. Therefore, we predicted that density would be positively correlated with productivity (number of young fledged per unit area). Because individual performance is sensitive to events partly determined by chance, such as nest predation, we further predicted density would be weakly correlated or uncorrelated with the proportion of territories fledging young. We collected data in 23 study sites (25 ha each), 16 of which were located in untreated mature northern hardwood forest and seven in stands partially harvested (treated) 1–7 years prior to the survey. Density explained most of the variability in productivity (R²= 0.73), and there was no apparent decoupling between density and productivity in treated plots. In contrast, there was no significant relationship between density and the proportion of territories fledging ≥1 young over the entire breeding season. These results suggest that density reflects habitat quality at the plot scale in this study system. To our knowledge this is one of the few studies testing the value of territory density as an indicator of habitat quality in an open‐nesting bird species on the basis of a relatively large number of sizeable study plots.     

Use of an Airborne Lidar System to Model Plant Species Composition and Diversity of Mediterranean Oak Forests

Abstract: Airborne lidar is a remote‐sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three‐dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape‐level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first‐and‐last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar‐ and field‐measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar‐measured vegetation height (R²= 0.50, p < 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground‐truthing and its timing relative to acquisition of lidar data.     

Landscape evaluation in conservation: molecular sampling and habitat modeling for the Iberian lynx.

Conservation of endangered species requires comprehensive understanding of their distribution and habitat requirements, in order to implement better management strategies. Unfortunately, this understanding is often difficult to gather at the short term required by rapidly declining populations of many rare vertebrates. We present a spatial habitat modeling approach that integrates a molecular technique for species detection with landscape information to assess habitat requirements of a critically endangered mammalian carnivore, the Iberian lynx (Lynx pardinus), in a poorly known population in Spain. We formulated a set of model hypotheses for habitat selection at the spatial scale of home ranges, based on previous information on lynx requirements of space, vegetation, and prey. To obtain the required data for model selection, we designed a sampling protocol based on surveys of feces and their molecular analysis for species identification. After comparing candidate models, we selected a parsimonious one that allowed (1) reliable assessment of lynx habitat requirements at the scale of home ranges, (2) prediction of lynx distribution and potential population size, and (3) identification of landscape management priorities for habitat conservation. This model predicted that the species was more likely to occur in landscapes with a higher percentage of rocky areas and higher cover of bushes typical of mature mediterranean shrubland mosaics. Its accuracy for discriminating lynx presence was approximately 85%, indicating high predictive performance. Mapping model predictions showed that only 16% of the studied areas constitute potential habitat for lynx, even though the region is dominated by large extents of well-preserved native vegetation with low human interference. Habitat was mostly clumped in two nearby patches connected by vegetation adequate for lynx dispersal and had a capacity for 28-62 potential breeding territories. The lynx population in Sierra Morena is probably the largest persisting today, but it is still critically small for optimism about its long-term persistence. Model results suggest habitat conservation and restoration actions needed for preserving the species, including reconciliation of hunting management with preservation of mature shrubland over large areas (particularly in rocky landscapes). The approach presented here can be applied to many other species for which the ecological information needed to develop sound habitat conservation strategies is lacking.     

南亚热带中幼龄针阔混交林碳储量及其分配格局

以南亚热带中幼龄针阔混交林为研究对象,通过典型样地调查法,对森林生态系统各个层次进行取样调查,采用12个样地实测数据和已有生物量模型相结合的方法计算乔木层生物量,灌木层、草本层和凋落物层采用全部收获法测得其生物量,对土壤层的调查采用剖面法加土钻法,代表性样品碳含量的测定采用重铬酸钾-水合加热法。在此基础上,分析了中幼龄针阔混交林碳储量及其分配格局。结果表明,主要造林树种树根、树杆、树枝和树叶碳含量均值分别为45.07%、46.73%、46.30%和47.72%。植物碳含量表现为乔木〉灌木〉草本。乔木碳储量占植被总碳储量比例介于63.38%-94.08%之间,灌木碳储量所占比例介于3.55%-12.67%之间,而草本碳储量仅介于为1.28%-23.95%之间,不同林龄段乔木和灌木碳储量均值随林龄的增加呈上升趋势,而草本碳储量呈下降趋势。土壤碳储量介于106.73-136.61 t·hm^-2之间,土壤碳储量随林龄的增加呈现出先降低后升高的趋势。针阔混交林总碳储量介于134.79-162.60 t·hm^-2之间,分配格局表现为土壤层〉植被层〉凋落物层。土壤层碳储量所占总碳储量比例范围为78.34%-94.45%,植被层所占比例介于4.84%-20.16%之间,凋落物层仅介于0.71%-1.50%之间,中幼龄针阔混交林碳储量主要以土壤固碳为主。研究结果为树种选择、人工林生态系统固碳潜力以及人工碳汇林的经营管理等研究提供科学参考。     

Evaluation of some competition indices for the construction of Lebanon cedar (Cedrus libani A. Rich.) stand models

The purpose of this research is to test the precision of some published competition indices of Lebanon cedar (Cedrus libani A. Rich.) for the estimation of future periodic diameter increment of individual trees. Twenty- nine published competition indices were tested, using fifteen separate sets of data and their pooled values, collected from various stand age and site quality classes Lebanon cedar at Antalya. Temporary sample plots were taken in Elmali-Qamkuyusu (9 sample plots) and Finike-Pinarcik (6 sample plots) in 2001. Every plot was stem mapped (x and y coordinate system), diameter (dbh), total height, crown length, crown diameter and 10-year radial increment were recorded for trees greater than 4 cm in dbh. Then, in order to evaluate these competition indices for the prediction of the periodic diameter increment of the individual trees. Three linear models have been constructed for each competition index. It was found that the competition indices (Daniels et al., 1986; Biging and Dobbertin, 1995; Pukkala and Kolstr?m, 1987; Hegyi, 1974) with larger influence-zone areas produce better results.     

Complex national sampling design for long-term monitoring of protected dry grasslands in Switzerland

We describe a probabilistic sampling design of circular permanent plots for the long-term monitoring of protected dry grasslands in Switzerland. The population under study is defined by the perimeter of a national inventory. The monitoring focus is on the species composition of the protected grassland vegetation and derived conservation values. Efficient trend estimations are required for the whole country and for some predefined target groups (six biogeographical regions and eleven vegetation types). The target groups are equally important regardless of their size. Consequently, intensified sampling of the less frequent groups is essential for sample efficiency. The prior information needed to draw a targeted sample is obtained from the sampling frame and external databases. The logistics and generalized delineation of the target population may pose further problems. Thus, investments in fieldwork and travel time should be well balanced by selecting a cluster sample. Second, any access problems in the field and non-target units in the sample should be compensated for by selecting reserve plots as they otherwise may considerably reduce the effective sample size. Finally, the design has to be flexible as the sampling frame may change over time and sampling intensity might have to be adjusted to redefined budgets or requirements. Likewise, the variables and biological items of interest may change. To fulfil all these constraints and to optimally use the available prior information, we propose a multi-stage self-weighted unequal probability sampling design. The design uses modern techniques such as: balanced sampling, spreading, stratified balancing, calibration, unequal probability sampling and power allocation. This sampling design meets the numerous requirements of this study and provides a very efficient estimator.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.