Habitat Suitability Models and the Shortfall in Conservation Planning for African Vertebrates

Abstract:  Ongoing loss of biodiversity requires identifying large-scale conservation priorities, but the detailed information on the distribution of species required for this purpose is often missing. We present a systematic reserve selection for 1223 African mammals and amphibians in which habitat suitability models are used as estimates of the area occupied by species. In the framework of the World Conservation Union (IUCN) Global Amphibian Assessment and IUCN Global Mammal Assessment, we collected the geographic range (extent of occurrence) and habitat preferences for each species. We used the latter to build species-specific habitat suitability models inside geographic ranges, and for 181 species we verified the models by comparing suitability levels to presence-absence data collected in the field. We then used the suitable areas as estimators of the area of occupancy and compared the results of systematic reserve selection based on geographic ranges to those based on estimated areas of occupancy. Our results showed that the reserve system would need a 30-100% expansion to achieve minimal conservation targets, concentrated in the tropics, where species richness reaches a maximum. Comparative analyses revealed that using geographic ranges, which overestimate the area occupied by species, underestimates the total amount of area that needs to be conserved. The area selected for conservation doubled when we used the estimated area of occupancy in place of the geographic ranges. This happened because the suitable areas potentially occupied by each species overlapped less than their geographic ranges. As a result, any given protected area contained fewer species than predicted by the analysis of ranges. Because species are more specialized than our estimates of distribution based on extent of occurrence suggest, we propose that this is a general effect in systematic conservation planning.     

Bayesian Networks and Adaptive Management of Wildlife Habitat

Abstract: Adaptive management is an iterative process of gathering new knowledge regarding a system's behavior and monitoring the ecological consequences of management actions to improve management decisions. Although the concept originated in the 1970s, it is rarely actively incorporated into ecological restoration. Bayesian networks (BNs) are emerging as efficient ecological decision‐support tools well suited to adaptive management, but examples of their application in this capacity are few. We developed a BN within an adaptive‐management framework that focuses on managing the effects of feral grazing and prescribed burning regimes on avian diversity within woodlands of subtropical eastern Australia. We constructed the BN with baseline data to predict bird abundance as a function of habitat structure, grazing pressure, and prescribed burning. Results of sensitivity analyses suggested that grazing pressure increased the abundance of aggressive honeyeaters, which in turn had a strong negative effect on small passerines. Management interventions to reduce pressure of feral grazing and prescribed burning were then conducted, after which we collected a second set of field data to test the response of small passerines to these measures. We used these data, which incorporated ecological changes that may have resulted from the management interventions, to validate and update the BN. The network predictions of small passerine abundance under the new habitat and management conditions were very accurate. The updated BN concluded the first iteration of adaptive management and will be used in planning the next round of management interventions. The unique belief‐updating feature of BNs provides land managers with the flexibility to predict outcomes and evaluate the effectiveness of management interventions.     

江苏省陆栖濒危脊椎动物物种丰富度及分布格局

采用实地调查与资料收集相结合的方法,以县(市)为基本地理单元建立江苏省陆栖濒危脊椎动物二元分布数据库;基于GIS技术,研究濒危动物物种丰富度格局;依据地理单元中物种组成的相似程度进行聚类分析,探讨江苏省濒危动物相似性分布格局。结果显示,江苏省陆栖濒危脊椎动物共有35科62属83种;西南部丘陵山区、盐城、连云港及启东地区濒危物种丰富度较高,江苏中部地区(主要为泰州和淮安)濒危物种丰富度较低,这与江苏省生物多样性分布热点基本一致,濒危物种丰富度与总物种丰富度之间呈极显著正相关关系(P<0.01,n=73),Pearson相关系数为0.869;依据物种组成相似性,当组间距离分别为23.8、20.6、18.8时,江苏省73个基本单元可聚为3、4、5组,该聚类结果表明江苏省陆栖濒危脊椎动物分布受自然地理亚区、地形地貌以及人为活动的共同影响。     

Sensitivity Analyses of Spatial Population Viability Analysis Models for Species at Risk and Habitat Conservation Planning

Abstract:  Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.     

Synergistic Effects of Subsistence Hunting and Habitat Fragmentation on Amazonian Forest Vertebrates

Abstract: Subsistence game hunting has profound negative effects on the species diversity, standing biomass, and size structure of vertebrate assemblages in Amazonian forests that otherwise remain largely undisturbed. These effects are likely to be considerably aggravated by forest fragmentation because fragments are more accessible to hunters, allow no (or very low rates of  ) recolonization from nonharvested source populations, and may provide a lower-quality resource base for the frugivore-granivore vertebrate fauna. I examined the likelihood of midsized to large-bodied bird and mammal populations persisting in Amazonian forest fragments of variable sizes whenever they continue to be harvested by subsistence hunters in the aftermath of isolation. I used data from a comprehensive compilation of game-harvest studies throughout Neotropical forests to estimate the degree to which different species and populations have been overharvested and then calculated the range of minimum forest areas required to maintain a sustainable harvest. The size distribution of 5564 Amazonian forest fragments—estimated from Landsat images of six regions of southern and eastern Brazilian Amazonia—clearly shows that these are predominantly small and rarely exceed 10 ha, suggesting that persistent overhunting is likely to drive most midsized to large vertebrate populations to local extinction in fragmented forest landscapes. Although experimental studies on this negative synergism remain largely unavailable, the prospect that increasingly fragmented Neotropical forest regions can retain their full assemblages of avian and mammalian species is unlikely.     

Understanding Interaction Effects of Climate Change and Fire Management on Bird Distributions through Combined Process and Habitat Models

Abstract: Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process‐based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf‐area index values were lower in shrubland. This high probability of occurrence likely is related to the species’ use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.     

Estimation of Core Terrestrial Habitat for Stream-Breeding Salamanders and Delineation of Riparian Buffers for Protection of Biodiversity

Abstract:  Many species of wildlife depend on riparian habitats for various life-history functions (e.g., breeding, foraging, overwintering). Although this unique habitat is critical for many species, delineations of riparian zones and buffers for various taxa are lacking. Typically when buffer zones are determined to mitigate edge effects, they are based on criteria that protect aquatic resources alone and do not consider impacts to wildlife and other terrestrial resources. Using two different survey methods (area-constrained daytime searches and nighttime visual encounter searches), we estimated core terrestrial habitat and buffer widths for stream-breeding salamanders in southern Appalachian streams from May to August 2004. A core terrestrial habitat of 27.0 m encompassed 95% of the salamander assemblage (four species of stream plethodontids), and an additional 50 m (to buffer edge effects) yielded a total buffer of 77.0 m. When each species of the assemblage was analyzed separately, the maximum core terrestrial habitat needed for the Blue Ridge two-lined salamander ( Eurycea wilderae ), a dominant member and the farthest-ranging species from the stream, was 42.6 m. Thus, we recommend an overall buffer width of 92.6 m in southern Appalachian streams. To protect stream amphibians and other wildlife dependent on riparian areas, land managers and policy makers must consider conserving more than aquatic resources alone. Developing core terrestrial habitat estimates and buffer zone widths for wildlife populations is a critical first step in the conservation of many semiaquatic organisms and protecting biodiversity.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

A Framework for Evaluating the Effects of Human Factors on Wildlife Habitat: the Case of Giant Pandas

Abstract: To address the complex interactions between humans and wildlife habitat, we developed a conceptual framework that links human factors with forested landscapes and wildlife habitat. All the components in the framework are integrated into systems models that analyze the effects of human factors and project how wildlife habitat would change under different policy scenarios. As a case study, we applied this framework to the Wolong Nature Reserve in Sichuan Province (southwestern China), the largest home of the giant panda ( Ailuropoda melanoleuca ). We collected ecological and socioeconomic data with a combination of various methods ( field observations, aerial photographs, government documents and statistics, interviews, and household surveys) and employed geographic information systems and systems modeling to analyze and integrate the data sources. Human population size has increased by 66% and the number of households in the reserve has increased by 115% since 1975, when the reserve was established. During the same period, the quality and quantity of the giant panda habitat dramatically decreased because of increasing human activities such as fuelwood collection. Systems modeling predicted that under the status quo, human population in the reserve would continue to grow and cause more destruction of the remaining panda habitat, whereas reducing human birth rates and increasing human emigration rates would lower human population size and alleviate human impacts on the panda habitat. Furthermore, our simulations and surveys suggested that policies encouraging the emigration of young people would be more effective and feasible than relocating older people in reducing human population size and conserving giant panda habitat in the reserve.     

污水深度处理生物滤层中菌群的时空分布特征

以生物滤柱为反应器,对污水进行深度处理。试验表明,生物滤层中的菌群由于生化特性的不同,启动阶段异养菌要比自养菌的生长提前一周左右。生物滤柱异养菌、自养菌的形成对稳定运行非常关键,启动阶段较高的COD容积负荷不利于亚硝化、硝化细菌的产生。异养菌在竞争中占有优势,主要生长在滤柱的进水端和悬浮生物膜中。进水有机物浓度较低,造成亚硝化细菌的分布同异养菌分布基本一致。硝化细菌由于较弱的竞争能力,主要生长在滤柱的出水端和吸附生物膜中。底物浓度的改变使生物膜中的菌群对有机物、溶解氧以及生存空间的竞争也发生变化,最终导致其分布也随之改变。     

The Importance of Being Spatial (and Reserved): Assessing Northern Spotted Owl Habitat Relationships with Hierarchical Bayesian Models

Abstract:  Regional conservation planning increasingly draws on habitat suitability models to support decisions regarding land allocation and management. Nevertheless, statistical techniques commonly used for developing such models may give misleading results because they fail to account for 3 factors common in data sets of species distribution: spatial autocorrelation, the large number of sites where the species is absent (zero inflation), and uneven survey effort. We used spatial autoregressive models fit with Bayesian Markov Chain Monte Carlo techniques to assess the relationship between older coniferous forest and the abundance of Northern Spotted Owl nest and activity sites throughout the species' range. The spatial random-effect term incorporated in the autoregressive models successfully accounted for zero inflation and reduced the effect of survey bias on estimates of species–habitat associations. Our results support the hypothesis that the relationship between owl distribution and older forest varies with latitude. A quadratic relationship between owl abundance and older forest was evident in the southern portion of the range, and a pseudothreshold relationship was evident in the northern portion of the range. Our results suggest that proposed changes to the network of owl habitat reserves would reduce the proportion of the population protected by up to one-third, and that proposed guidelines for forest management within reserves underestimate the proportion of older forest associated with maximum owl abundance and inappropriately generalize threshold relationships among subregions. Bayesian spatial models can greatly enhance the utility of habitat analysis for conservation planning because they add the statistical flexibility necessary for analyzing regional survey data while retaining the interpretability of simpler models.     

Habitat Mosaic, Wildlife Availability, and Hunting in the Tropical Forest of Calakmul, Mexico

Abstract: Habitat loss and subsistence hunting are two of the main activities that affect wildlife in frontier areas. We compared subsistence hunting patterns in four villages with different ethnic composition and degree of habitat disturbance in the vicinity of Calakmul Biosphere Reserve, Campeche, Mexico. We also compared differences between some of these villages in harvest composition and prey availability to determine hunting preferences. We used a Landsat TM satellite image to analyze the degree of disturbance around the villages. We conducted periodic surveys of subsistence hunting and prey availability. Wildlife availability was assessed monthly on nine transects (3000 m) established in the vicinity of three villages. The relative amount of disturbed habitat was smaller in an indigenous Maya village ( IV ) and larger in a mestizo village ( MV ). The two mixed-composition villages ( MCVs) had intermediate levels of disturbance. Ten species, four large and six small, of birds and mammals accounted for 97% of the hunting records. Hunting was more intense in IV and less intense in MCV1. The three village types had different hunting preferences. The habitat-mosaic composition in the vicinity of the villages influenced prey availability and subsistence-hunting preferences. Changes in the habitat mosaic were caused by the size of the holding and by ethnic composition. In spite of longer settlement time, the habitat mosaic in the vicinity of IV was less transformed than that of the other sites. Their larger holding size and greater diversity of economic activities may explain why the Mayas at IV have transformed the landscape less than the other groups and can hunt more and larger prey.     

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.     

Transferability of Species Distribution Models: a Functional Habitat Approach for Two Regionally Threatened Butterflies

Abstract:  Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak ( Callophrys rubi ) and the grayling ( Hipparchia semele ), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable—although to different degrees—among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.     

Source-Sink Models and the Problem of Habitat Degradation: General Models and Applications to the Yellowstone Grizzly

I used source-sink population models to explore the consequences of habitat degradation for populations living on good and degraded habitats linked by movement. In particular, I modeled the conversion of land from good habitat quality supporting positive population growth to a degraded condition in which there was population decline. I found that with high rates of movement between good and bad quality areas populations require relatively large amounts of good habitat to remain stable. However, low movement rates resulted in greater sensitivity of population growth to habitat loss. Even small amounts of habitat degradation could result in rapid changes in overall population growth rates depending upon the rates of population increase and decline in the two habitat types. I also developed and simulated an age-structured model for grizzly bears ( Ursus arctos horribilis ) existing in good and degraded habitats and fit this model to data from the Yellowstone grizzly population. I used this model to predict the ability to detect crucial amounts of habitat degradation from census data and found that when degradation is slow (e.g., 1% conversion of good to poor habitat per year), more than a decade may pass between crucial amounts of degradation—beyond which populations begin long-term decline—and its detection, even if census data were unrealistically good. Thus these simple models indicate that, at least in some circumstances, habitat degradation can have rapid and severe impacts on population dynamics and traditional monitoring programs may not be adequate to detect the consequences of degradation.     

Hierarchical Bayesian Spatial Models for Multispecies Conservation Planning and Monitoring

Abstract: Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence–absence data derived from regional monitoring programs to develop models with both landscape and site‐level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence–absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad‐scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km² hexagons), can increase the relevance of habitat models to multispecies conservation planning.