自然保护区空间特征和地块最优化选择方法

自然保护区是保护物种和生态系统的有效方式,用于建立自然保护区的资源却是稀缺的,这就提出这样的问题：1)自然保护区在空间上应具有什么特征才是有效的;2)如何从许多备选地块中选择一部分组成自然保护区对稀缺资源进行最优化分配。为促进物种生存繁衍,在地块选择时应考虑保护区空间特征。这篇文章综述了该领域最近的研究进展,重点介绍了结合各种空间特征的保护区地块最优化选择模型。介绍了4个主要的空间特征：1)连续,2)间隔和距离,3)边界和集约,4)面积以及核心区和缓冲区。以前用启发式算法求解这些问题,但研究已显示该法不能保证资源的最优化分配。空间特征也可用线性整数规划模拟,用最优化软件求得最优解。目前的线性整数规划模型和软件还不能有效解决大型的保护区地块选择问题,计算效率易成为实际应用的瓶颈。文章概括了我国目前自然保护区设计领域的研究状况和面临的问题,最后讨论了该领域新的研究方向。     

Spatially-Correlated Risk in Nature Reserve Site Selection

Establishing nature reserves protects species from land cover conversion and the resulting loss of habitat. Even within a reserve, however, many factors such as fires and defoliating insects still threaten habitat and the survival of species. To address the risk to species survival after reserve establishment, reserve networks can be created that allow some redundancy of species coverage to maximize the expected number of species that survive in the presence of threats. In some regions, however, the threats to species within a reserve may be spatially correlated. As examples, fires, diseases, and pest infestations can spread from a starting point and threaten neighboring parcels’ habitats, in addition to damage caused at the initial location. This paper develops a reserve site selection optimization framework that compares the optimal reserve networks in cases where risks do and do not reflect spatial correlation. By exploring the impact of spatially-correlated risk on reserve networks on a stylized landscape and on an Oregon landscape, this analysis demonstrates an appropriate and feasible method for incorporating such post-reserve establishment risks in the reserve site selection literature as an additional tool to be further developed for future conservation planning.     

Spatial heterogeneity in habitat selection: Nest site selection by greater prairie-chickens

Ecological relationships of animals and their environments are known to vary spatially and temporally across scales. However, common approaches for evaluating resource selection by animals assume that the processes of habitat selection are stationary across space. The assumption that habitat selection is spatially homogeneous may lead to biased inference and ineffective management. We present the first application of geographically weighted logistic regression to habitat selection by a wildlife species. As a case study, we examined nest site selection by greater prairie-chickens at 3 sites with different ecological conditions in Kansas to assess whether the relative importance of habitat features varied across space. We found that 1) nest sites were associated with habitat conditions at multiple spatial scales, 2) habitat associations across spatial scales were correlated, and 3) the influence of habitat conditions on nest site selection was spatially explicit. Post hoc analyses revealed that much of the spatial variability in habitat selection processes was explained at a regional scale. Moreover, habitat features at local spatial scales were more strongly associated with nest site selection in unfragmented grasslands managed intensively for cattle production than they were in fragmented grasslands within a matrix of farmland. Female prairie-chickens exhibited spatial variability in nest site selection at multiple spatial scales, suggesting plasticity in habitat selection behavior. Our results highlight the importance of accounting for spatial heterogeneity when evaluating the ecological effects of habitat components. © 2013 The Wildlife Society.     

Connectivity, Probabilities and Persistence: Comparing Reserve Selection Strategies

Reserve selection methods are often based on information on species’ occurrence. This can be presence–absence data, or probabilities of occurrence estimated with species distribution models. However, the effect of the choice of distribution model on the outcome of a reserve selection method has been ignored. Here we test a range of species distribution models with three different reserve selection methods. The distribution models had different combinations of variables related to habitat quality and connectivity (which incorporates the effect of spatial habitat configuration on species occurrence). The reserve selection methods included (i) a minimum set approach without spatial considerations; (ii) a clustering reserve selection method; and (iii) a dynamic approach where probabilities of occurrence are re-evaluated according to the spatial pattern of selected sites. The sets of selected reserves were assessed by re-computing species probability of occurrence in reserves using the best probability model and assuming loss of non-selected habitat. The results show that particular choices of distribution model and selection method may lead to reserves that overestimate the achieved target; in other words, species may seem to be represented but the reserve network may actually not be able to support them in the long-term. Instead, the use of models that incorporated connectivity as a variable resulted in the selection of aggregated reserves with higher potential for species long-term persistence. As reserve design aims at the long-term protection of species, it is important to be aware of the uncertainties related to model and method choice and their implications.     

The spatial scaling of habitat selection by African elephants

1. Understanding and accurately predicting the spatial patterns of habitat use by organisms is important for ecological research, biodiversity conservation and ecosystem management. However, this understanding is complicated by the effects of spatial scale, because the scale of analysis affects the quantification of species-environment relationships. 2. We therefore assessed the influence of environmental context (i.e. the characteristics of the landscape surrounding a site), varied over a large range of scales (i.e. ambit radii around focal sites), on the analysis and prediction of habitat selection by African elephants in Kruger National Park, South Africa. 3. We focused on the spatial scaling of the elephants' response to their main resources, forage and water, and found that the quantification of habitat selection strongly depended on the scales at which environmental context was considered. Moreover, the inclusion of environmental context at characteristic scales (i.e. those at which habitat selectivity was maximized) increased the predictive capacity of habitat suitability models. 4. The elephants responded to their environment in a scale-dependent and perhaps hierarchical manner, with forage characteristics driving habitat selection at coarse spatial scales, and surface water at fine spatial scales. 5. Furthermore, the elephants exhibited sexual habitat segregation, mainly in relation to vegetation characteristics. Male elephants preferred areas with high tree cover and low herbaceous biomass, whereas this pattern was reversed for female elephants. 6. We show that the spatial distribution of elephants can be better understood and predicted when scale-dependent species-environment relationships are explicitly considered. This demonstrates the importance of considering the influence of spatial scale on the analysis of spatial patterning in ecological phenomena.     

Incorporating spatial criteria in optimum reserve network selection

Considering the spatial location of sites that are to be selected for inclusion in a protected reserve network may be necessary to facilitate dispersal and long-term persistence of species in the selected sites. This paper presents an integer programming (IP) approach to the reserve network selection problem where spatial considerations based on intersite distances are taken into account when selecting reserve sites. The objective is to reduce the fragmentation of preserved sites and design a compact reserve network. Two IP formulations are developed which minimize the sum of pairwise distances and the maximum intersite distance between all sites in the reserve network, respectively, while representing all species under consideration. This approach is applied to a pond invertebrate dataset consisting of 131 sites containing 256 species in Oxfordshire, UK. The results show that significant reductions in reserve fragmentation can be achieved, compared with spatially unrestricted optimum reserve selection, at the expense of a small loss in reserve efficiency.     

Nest site selection of a primary hole‐nesting passerine reveals means to developing sustainable forestry

Anthropogenic habitat loss and fragmentation affect populations worldwide. For example, many bird populations of boreal forests have declined due to intensive forestry. To target conservation actions for such species, determining the key factors that affect their habitat selection is essential. Remote sensing methods provide highly potential means to measure habitat variables over large areas. We aim at identifying the key‐features of habitats by utilizing remote sensing data. As a case example, we study the nest site selection of a primary hole‐nesting passerine, the willow tit Poecile montanus, in a managed forest landscape. Using presence–absence data, we determine the most important habitat characteristics of the nest sites for three spatial scales by generalized linear mixed effect models. Our results highlight the importance of the availability of nesting sites – standing decaying deciduous trees – in the nest site selection of P. montanus. It seems to prefer moist habitats with high densities of deciduous trees and to avoid open areas, but does not require mature or intact habitats. Most of the nest site selection seems to occur within small scales. In this case, remote sensing data alone was insufficient for producing reliable models, but adding information of an ecologically important feature from direct field surveys greatly improved model performances. For the conservation and maintenance of dead wood dependent species, changes in forestry practices are necessary to keep the key characteristics of the habitat. Most importantly, continuous availability of standing decaying wood should be secured.     

So close and yet so different: The importance of considering temporal dynamics to understand habitat selection

Habitat selection of animals is influenced by spatial heterogeneity as well as temporal environmental dynamics. In addition, human activities potentially have severe influences on the habitat selection of animals, often resulting in more nocturnal behavior. We investigated seasonal and circadian habitat selection patterns of red deer (Cervus elaphus) on a military training area in Bavaria (Germany). Individual deer ranged on two neighboring, but non-overlapping sites differing in landscape composition and human activity. Using GPS telemetry data, we visually investigated selection patterns and then fitted step-selection functions to assess multiple approaches to account for temporal (i.e., diel and seasonal) effects and for the impact of habitat conditions on selection. We first showed that the way in which time of day is considered in step-selection functions is essential for obtaining ecologically meaningful results, and that the usual ways of including time (i.e., either based on clock-time or based on night vs. day categories) can lead to incomplete or misleading conclusions. Furthermore, we found that individuals followed either circadian or seasonal habitat selection patterns, depending on the site they inhabited. This can be explained by differences in disturbance between the two sites. Except in winter, individuals selected for open habitats during the night irrespective of human activity level, but only individuals from the more disturbed site selected for covered habitats during the day. Our results highlight the importance of carefully considering the appropriate temporal scale for habitat selection analyses. Our findings also indicate that red deer are not a crepuscular or nocturnal species per se, as is often observed in human-dominated landscapes. Instead, our results imply that nocturnality in red deer is an effect of adaption to human activities.     

Habitat loss and connectivity of reserve networks in probability approaches to reserve design

Quantitative methods for the design of reserve networks often select over‐dispersed reserves, and consequently a number of species extinctions can be expected in such reserves, especially if unprotected surrounding habitat is lost. A novel approach that deals with this problem is presented by considering factors such as habitat quality and spatial configuration of reserves during the selection process. Species‐specific effects of habitat loss and fragmentation, together with habitat composition, are taken into account when computing species probabilities of local occurrence. Sites are then chosen to represent all species with a given target probability. The method is applied to a dataset of butterflies and moths from the Creuddyn Peninsula, North Wales, UK, which includes species with various responses to habitat quality and configuration. The results show that the resulting level of reserve clustering will depend on the number of species for which the spatial configuration plays an important role (at the scale under consideration), and on the pattern and amount of habitat loss that is expected to follow around the reserves. The method represents a step towards taking better into account species persistence when selecting reserve networks in a changing world.     

Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Designing connected nature reserve networks using a graph theory approach

Habitat fragmentation has been cited as one of the critical reasons for biodiversity loss. Establishing connected nature reserve networks is an effective way to reduce habit fragmentation. However, the resources devoted to nature reserves have always been scarce. Therefore it is important to allocate our scarce resources in an optimal way. The optimal design of a reserve network which is effective both ecologically and economically has become an important research topic in the reserve design literature. The problem of optimal selection of a subset from a larger group of potential habitat sites is solved using either heuristic or formal optimization methods. The heuristic methods, although flexible and computationally fast, can not guarantee the solution is optimal therefore may lead to scarce resources being used in an ineffective way. The formal optimization methods, on the other hand, guarantees the solution is optimal, but it has been argued that it would be difficult to model site selection process using optimization models, especially when spatial attributes of the reserve have to be taken into account. This paper presents a linear integer programming model for the design of a minimal connected reserve network using a graph theory approach. A connected tree is determined corresponding to a connected reserve. Computational performance of the model is tested using datasets randomly generated by the software GAMS. Results show that the model can solve a connected reserve design problem which includes 100 potential sites and 30 species in a reasonable period of time. As an empirical application, the model is applied to the protection of endangered and threatened bird species in the Cache River basin area in Illinois, US. Two connected reserve networks are determined for 13 bird species.     

Population Dynamics and Spatial Distribution of Coral Reef Fishes: Comparison Between Continuous and Isolated Habitats

Recent studies have shown that there are high degrees of spatial and temporal stability in coral reef fish assemblage structures in a continuous habitat, in contrast to results of observations in isolated habitats. In order to determine the reason for the difference in temporal stability of fish assemblage structures in a continuous habitat site and an isolated habitat site, population dynamics and spatial distributions of coral reef fishes (six species of pomacentrids and two species of apogonids) in the two habitat site were investigated over a 2-year period in an Okinawan coral reef. The population densities of pomacentrid and apogonid species increased in juvenile settlement periods at both sites, but the magnitude of seasonal fluctuation in population density was significantly greater at the isolated habitat site, indicating that the rate of juvenile settlement and mortality rate in the isolated habitat were greater than those in the continuous habitat. The magnitude of aggregation of fishes, which affects density-dependent biological interactions that modify population density such as competition and predation, was also significantly greater at the isolated habitat site, especially in the juvenile settlement season. Most of the fishes at the isolated habitat site exhibited more generalized patterns of microhabitat selection because of less coral coverage and diversity. The seasonal stability in the species composition of fishes was greater at the continuous habitat site than that at the isolated habitat. Our findings suggest that the relative importance of various ecological factors responsible for regulation of the population density of coral reef fishes (e.g., competition, predation, microhabitat selection and post-settlement movement) in a continuous habitat site and the isolated habitat site are different.     

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Animals select habitats that will ultimately optimize their fitness through access to favorable resources, such as food, mates, and breeding sites. However, access to these resources may be limited by bottom‐up effects, such as availability, and top‐down effects, such as risk avoidance and competition, including that with humans. Competition between wildlife and people over resources, specifically over space, has played a significant role in the worldwide decrease in large carnivores. The goal of this study was to determine the habitat selection of cheetahs (Acinonyx jubatus) in a human‐wildlife landscape at multiple spatial scales. Cheetahs are a wide‐ranging, large carnivore, whose significant decline is largely attributed to habitat loss and fragmentation. It is believed that 77% of the global cheetah population ranges outside protected areas, yet little is known about cheetahs’ resource use in areas where they co‐occur with people. The selection, or avoidance, of three anthropogenic variables (human footprint density, distance to main roads and wildlife areas) and five environmental variables (open habitat, semiclosed habitat, edge density, patch density and slope), at multiple spatial scales, was determined by analyzing collar data from six cheetahs. Cheetahs selected variables at different scales; anthropogenic variables were selected at broader scales (720–1440 m) than environmental variables (90–180 m), suggesting that anthropogenic pressures affect habitat selection at a home‐range level, whilst environmental variables influence site‐level habitat selection. Cheetah presence was best explained by human presence, wildlife areas, semiclosed habitat, edge density and slope. Cheetahs showed avoidance for humans and steep slopes and selected for wildlife areas and areas with high proportions of semiclosed habitat and edge density. Understanding a species’ resource requirements, and how these might be affected by humans, is crucial for conservation. Using a multiscale approach, we provide new insights into the habitat selection of a large carnivore living in a human‐wildlife landscape.     

Untangling Natural Seascape Variation from Marine Reserve Effects Using a Landscape Approach

Distinguishing management effects from the inherent variability in a system is a key consideration in assessing reserve efficacy. Here, we demonstrate how seascape heterogeneity, defined as the spatial configuration and composition of coral reef habitats, can mask our ability to discern reserve effects. We then test the application of a landscape approach, utilizing advances in benthic habitat mapping and GIS techniques, to quantify this heterogeneity and alleviate the confounding influence during reserve assessment. Seascape metrics were quantified at multiple spatial scales using a combination of spatial image analysis and in situ surveys at 87 patch reef sites in Glover''s Reef Lagoon, Belize, within and outside a marine reserve enforced since 1998. Patch reef sites were then clustered into classes sharing similar seascape attributes using metrics that correlated significantly to observed variations in both fish and coral communities. When the efficacy of the marine reserve was assessed without including landscape attributes, no reserve effects were detected in the diversity and abundance of fish and coral communities, despite 10 years of management protection. However, grouping sites based on landscape attributes revealed significant reserve effects between site classes. Fish had higher total biomass (1.5×) and commercially important biomass (1.75×) inside the reserve and coral cover was 1.8 times greater inside the reserve, though direction and degree of response varied by seascape class. Our findings show that the application of a landscape classification approach vastly improves our ability to evaluate the efficacy of marine reserves by controlling for confounding effects of seascape heterogeneity and suggests that landscape heterogeneity should be considered in future reserve design.     

最优化设计连续的自然保护区

生境破碎是导致生物多样性损失的重要原因之一,避免生境破碎的一个有效方式是建立连续的自然保护区使物种可在保护区内自由移动。不加选择地把大片土地都转为保护区是实现连续的一个途径,但资源是有限的,应当以最优的方式分配。如何最优化设计生态上和经济上都有效的保护区成为生物保护领域一个重要议题。从一组备选地块中选择一部分组成自然保护区,这样的问题主要有两种解法:启发式方法和最优化方法。启发式方法虽然灵活且运算速度快但不能保证最优解因而可能导致稀缺资源的浪费,最优化方法保证得到的解是最优的但建模和运算存在困难。建立一个线性整数规划模型用于设计一个最小的连续保护区,用Dantzig剪切法消除循环确保形成一个连续的树,对应一个连续的保护区,检验了模型的计算效率。结果显示,模型可在合理时间内解决一个包含100个备选地块和30个物种的连续保护区设计问题,计算效率显著优于同类目的的其它方法。以美国伊利诺伊州Cache河流域11种濒危鸟类的保护区设计为例说明了该方法的应用,设计了两种情况下连续的保护区。讨论了模型的局限和数据问题。     

Planning for reserve adequacy in dynamic landscapes; maximizing future representation of vegetation communities under flood disturbance in the Pantanal wetland

Aim Using a probabilistic modelling framework, we aimed to incorporate landscape spatiotemporal dynamics into reserve design. We employed a spatially explicit stochastic model, which integrates both hydrological and biological processes, to simulate the wetland’s biological succession. Location Pantanal wetland (with 140,000 km²) between Brazil, Bolivia and Paraguay. Methods We used the reserve design software Marxan to optimize the current and future representation (up to 50 years) of 20% of five plant communities with maximum reliability (i.e. smallest uncertainty). The Kappa statistic was used to compare selection frequencies of individual sites through a set of planning timeframes (5, 17, 25 and 50 years) and the likely pattern of biological succession over these periods. Results Solutions based on static vegetation distributions were significantly dissimilar from solutions based on the expected modelled changes resulting from the flood disturbance and succession dynamics. Increasing the required reliability of biodiversity outcomes resulted in more expensive reserve solutions. We demonstrated the flexibility of probabilistic decision‐making methods to illuminate the trade‐offs between reliability and efficiency of site selection. Main conclusions Considering the importance of habitat heterogeneity to the principles and practice of systematic conservation planning, it is notable that landscape dynamics have not been a central theme in conservation planning. In the case of the Pantanal hydrosere, acknowledging and planning for temporal dynamics required an ability to model succession and define acceptable levels of outcome reliability, but ultimately improved the long‐term Adequacy of resulting reserve networks.     

Habitat Selection by Prairie Dogs in a Disturbed Landscape at the Edge of Their Geographic Range

ABSTRACT Although habitat attributes of black-tailed prairie dog (Cynomys ludovicianus) colonies have been described for central and northern portions of the species' geographic range, little is known about these associations at the southern edge of this species' distribution. Because high-quality habitats are expected to be scarcer at the edge of the species' geographic range, different patterns of habitat selection might emerge in these populations. We analyzed habitat selection by black-tailed prairie dogs in a human-disturbed mosaic of desert grasslands and shrublands in northwestern Chihuahua, Mexico. We contrasted 151 used and 133 unused habitat units producing 11 case-control logistic regression models to explain site occupancy by prairie dogs with different combinations of environmental variables. Prairie dogs from Chihuahua occupy sites similar in most respects to sites in more northern regions, although these prairie dogs appear to be more tolerant of increased shrub density and reduced herbage cover. We found that site occupancy was best modeled by positive effects of soil moisture level, cover of forbs, cover of unpalatable vegetation, cover of bare ground, and amount of prairie-dog colony area within 1 km and by the inverse of altitude, shrub density, herbage height, and amount of hostile habitat within 1 km. The 2 most significant variables were herbage height and shrub density, which might reflect the prominent role that visibility plays in habitat selection by prairie dogs. In contrast, we found weak evidence that human features have significant impacts on site occupancy by prairie dogs. Our results support the prediction that environmental conditions of sites used by prairie dogs in edge regions partially differ from those observed in more northern latitudes. We suggest that reserve managers focus conservation efforts on areas with short vegetation, low density of shrubs, and high herbage cover, conditions that could be promoted by controlled burns, herbage mowing, and mechanical removal of shrubs.     

Assessing Habitat Use by Snapper (Chrysophrys auratus) from Baited Underwater Video Data in a Coastal Marine Park

Baited Underwater Video (BUV) systems have become increasingly popular for assessing marine biodiversity. These systems provide video footage from which biologists can identify the individual fish species present. Here we explore the relevance of spatial dependence and marine park boundaries while estimating the distribution and habitat associations of the commercially and recreationally important snapper species Chrysophrys auratus in Moreton Bay Marine Park during a period when new Marine National Parks zoned as no-take or “green” areas (i.e., areas with no legal fishing) were introduced. BUV studies typically enforce a minimum distance among BUV sites, and then assume that observations from different sites are independent conditional on the measured covariates. In this study, we additionally incorporated the spatial dependence among BUV sites into the modelling framework. This modelling approach allowed us to test whether or not the incorporation of highly correlated environmental covariates or the geographic placement of BUV sites produced spatial dependence, which if unaccounted for could lead to model bias. We fitted Bayesian logistic models with and without spatial random effects to determine if the Marine National Park boundaries and available environmental covariates had an effect on snapper presence and habitat preference. Adding the spatial dependence component had little effect on the resulting model parameter estimates that emphasized positive association for particular coastal habitat types by snapper. Strong positive relationships between the presence of snapper and rock habitat, particularly rocky substrate composed of indurated freshwater sediments known as coffee rock, and kelp habitat reinforce the consideration of habitat availability in marine reserve design and the design of any associated monitoring programs.     

The Use of Geographic Information Systems, Remote Sensing, and Suitability Modeling to Identify Conifer Restoration Sites with High Biological Potential for Anadromous Fish at the Cedar River Municipal Watershed in Western Washington, U.S.A.

We developed a methodology integrating several forms of remotely sensed data into a Geographic Information Systems (GIS) model that identifies suitable sites for riparian conifer restoration at the Cedar River Municipal Watershed in western Washington, U.S.A. The model integrates vegetative and geomorphic variables with information on the habitat preferences of anadromous fishes to identify riparian stands where conifer restoration would have the greatest biological benefit for salmon recovery. The high-resolution raster datasets used in our analysis were capable of characterizing the biophysical attributes of riparian areas at finer spatial scales than was previously possible. This model is intended to serve as a screening tool to identify candidate sites for riparian area restoration. The assessment approach described in this study can be applied not only to model salmonid habitat at the watershed scale but also to assess landscape patterns relevant to a wide range of restoration goals. This methodological framework offers several advantages over other approaches to restoration site selection and planning. First, the fine-scale spatial resolution of the GIS datasets (pixels ≤5 m) used in the model provides a more accurate representation of the habitat conditions than has been possible with coarser-scale data (pixels ≥5 m). Therefore, the accuracy of site identification is greatly improved. Second, the quantitative nature of the model exercises greater objectivity than some other landscape-scale planning approaches. This regional planning tool could be replicated in other watersheds with comparable datasets and could be applied to identify habitat restoration sites for other species or guilds of species by simply altering the model criteria to match the habitat needs of the target organisms.     

Differences in Characteristics of Reserve Network Selection Using Population Data Versus Habitat Surrogates

The use of species data versus environmental surrogates used in lieu of species data in systematic reserve site selection is still highly debated. We analyse in a case study whether and how the results of reserve network selection are affected by the use of species data versus habitat surrogates (habitat models) for qualitative (presence/absence) and quantitative (population size/habitat quality) information. In a model region, the post-mining landscape south of Leipzig/Germany, we used iterative algorithms to select a network for 29 animal target species from a basic set of 127 sites. The network results differ markedly for the two information types: depending on the representation goal, 18–45% of the selected sites chosen in response to one information type do not appear in the results for the other type. Given the availability of quantitative and hence deeper information, evaluation rules can be used to filter out the best habitats and the largest populations. In our model study, 0–40% less suitable areas were selected when instead of quantitative details only qualitative data were used. In view of various advantages and limitations of the two information types, we propose improving the methodological approach to the selection of networks for animal species by combining different information types.