The conservation of large carnivores is a formidable challenge for biodiversity conservation. Using a data set on the past and current status of brown bears (Ursus arctos), Eurasian lynx (Lynx lynx), gray wolves (Canis lupus), and wolverines (Gulo gulo) in European countries, we show that roughly one-third of mainland Europe hosts at least one large carnivore species, with stable or increasing abundance in most cases in 21st-century records. The reasons for this overall conservation success include protective legislation, supportive public opinion, and a variety of practices making coexistence between large carnivores and people possible. The European situation reveals that large carnivores and people can share the same landscape.

In the Brenta area of northern Italy, a brown bear Ursus arctos population is rapidly going extinct. Restocking of the population is planned. In order to study the genetics of this highly vulnerable population with a minimum of stress to the animals we have developed a PCR-based method that allows the study of mitochondrial and nuclear gene sequences from droppings collected in the field. This method is generally applicable to animals in the wild. Using excremental as well as hair samples, we show that the Brenta population is monomorphic for one mitochondrial lineage and that female as well as male bears exist in the area. In addition, 70 samples from other parts of Europe were studied. As others have previously reported, the mitochondrial gene pool of European bears is divided into two major clades, one with a western and the other with an eastern distribution. Whereas populations generally belong to either one or the other mitochondrial clade, the Romanian population contains both clades. The bears in the Brenta belong to the western clade. The implications for the management of brown bears in the Brenta and elsewhere in Europe are discussed.

We construct and explore a general modeling framework that allows for a systematic investigation of the impact of changes in landscape structure on population dynamics. The essential parts of the framework are a landscape generator with independent control over landscape composition and physiognomy, an individualbased spatially explicit population model that simulates population dynamics within heterogeneous landscapes, and scale-dependent landscape indices that depict the essential aspects of landscape that interact with dispersal and demographic processes. Landscape maps are represented by a grid of 50#50 cells and consist of good-quality, poorquality, or uninhabitable matrix habitat cells. The population model was shaped in accordance to the biology of European brown bears (Ursus arctos), and demographic parameters were adjusted to yield a source-sink configuration. Results obtained with the spatially explicit model do not confirm results of earlier nonspatial source-sink models where addition of sink habitat resulted in a decrease of total population size because of dilution of high-quality habitat. Our landscape indices, which describe scaledependent correlation between and within habitat types, were able to explain variations in variables of population dynamics (mean number of females with sink home ranges, mean number of females with source home ranges, and mean dispersal distance) caused by different landscape structure. When landscape structure changed, changes in these variables generally followed the corresponding change of an appropriate landscape index in a linear way. Our general approach incorporates source-sink dynamics as well as metapopulation dynamics, and the population model can easily be modified for other species groups. Submitted December 12, 1998; Accepted July 14, 1999 abstract: We construct and explore a general modeling framework that allows for a systematic investigation of the impact of changes in landscape structure on population dynamics. The essential parts of the framework are a landscape generator with independent control over landscape composition and physiognomy, an individual-based spatially explicit population model that simulates population dynamics within heterogeneous landscapes, and scale-dependent landscape indices that depict the essential aspects of landscape that interact with dispersal and demographic processes. Landscape maps are represented by a grid of cells and consist of good-quality, poor-50 # 50 quality, or uninhabitable matrix habitat cells. The population model was shaped in accordance to the biology of European brown bears (Ursus arctos), and demographic parameters were adjusted to yield a source-sink configuration. Results obtained with the spatially explicit model do not confirm results of earlier nonspatial source-sink models where addition of sink habitat resulted in a decrease of total population size because of dilution of high-quality habitat. Our landscape indices, which describe scale-dependent correlation between and within habitat t...

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Summary1. After an absence of almost 100 years, the Eurasian lynx Lynx lynx is slowly recovering in Germany along the German-Czech border. Additionally, many reintroduction schemes have been discussed, albeit controversially, for various locations. We present a habitat suitability model for lynx in Germany as a basis for further management and conservation efforts aimed at recolonization and population development. 2. We developed a statistical habitat model using logistic regression to quantify the factors that describe lynx home ranges in a fragmented landscape. As no data were available for lynx distribution in Germany, we used data from the Swiss Jura Mountains for model development and validated the habitat model with telemetry data from the Czech Republic and Slovenia. We derived several variables describing land use and fragmentation, also introducing variables that described the connectivity of forested and non-forested semi-natural areas on a larger scale than the map resolution. 3. We obtained a model with only one significant variable that described the connectivity of forested and non-forested semi-natural areas on a scale of about 80 km 2 . This result is biologically meaningful, reflecting the absence of intensive human land use on the scale of an average female lynx home range. Model testing at a cut-off level of P > 0·5 correctly classified more than 80% of the Czech and Slovenian telemetry location data of resident lynx. Application of the model to Germany showed that the most suitable habitats for lynx were large-forested low mountain ranges and the large forests in east Germany. 4. Our approach illustrates how information on habitat fragmentation on a large scale can be linked with local data to the potential benefit of lynx conservation in central Europe. Spatially explicit models like ours can form the basis for further assessing the population viability of species of conservation concern in suitable patches.

It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct estimates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate model calibration procedures can access additional sources of information, compensating the lack of direct parameter estimates. Our objective is to show how model calibration using population-level data can facilitate the construction of SEPMs that produce reliable predictions for conservation even when direct parameter estimates are inadequate. We constructed a spatially explicit and individual-based population model for the dynamics of brown bears (Ursus arctos) after a reintroduction program in Austria. To calibrate the model we developed a procedure that compared the simulated population dynamics with distinct features of the known population dynamics (=patterns). This procedure detected model parameterizations that did not reproduce the known dynamics. Global sensitivity analysis of the uncalibrated model revealed high uncertainty in most model predictions due to large parameter uncertainties (coefficients of variation CV ≈ 0.8). However, the calibrated model yielded predictions with considerably reduced uncertainty (CV ≈ 0.2). A pattern or a combination of various patterns that embed information on the entire model dynamics can reduce the uncertainty in model predictions, and the application of different patterns with high information content yields the same model predictions. In contrast, a pattern that does not embed information on the entire population dynamics (e.g., bear observations taken from sub-areas of the study area) does not reduce uncertainty in model predictions. Because population-level data for defining (multiple) patterns are often available, our approach could be applied widely.

Conservation biologists often must make management decisions based on little empirical information. In Germany, biologists are concerned that the recovery and reintroduction of Eurasian lynx (Lynx lynx) may fail because the remaining suitable habitat may be insufficient to sustain a viable population. However, no comprehensive study addressing this concern has been made that not only considers distribution of suitable habitat, but also connectivity to other populations. The aims of this study were (1) to quantify the amount and location of potentially suitable lynx habitat in Germany, (2) to estimate the connectivity between patches of suitable habitat, and (3) to evaluate lynx conservation programs. Habitat preferences of lynx were described in a rule‐based model based on the availability of forest cover (defined by patch size) and the spatial structure of the habitat. Rules were implemented in a geographic information system to predict locations of suitable habitat. Optimal connections among patches were modeled using a cost‐path analysis based on habitat‐specific probabilities of lynx crossing patches. Results indicated wide variation in the size of patches of suitable habitat, with 10 areas each sufficiently large to sustain >20 resident lynxes. Overall, a total of 380 lynxes could be sustained by the 10 areas. Uncertainty analyses of model parameters and assumptions revealed little variation in predicted habitat, primarily because results were constrained by the actual distribution of forest habitat. Our analyses suggest that lynx reintroduction programs should emphasize large, connected areas and consider broad‐scale habitat connectivity in the landscape. Our approach also demonstrates how biologically plausible rules can be applied in conservation to identify areas in which success is most likely, even when few empirical data are available.

In most of Europe, true wilderness areas do not exist and brown bears Ursus arctos generally have to cope with human disturbance and infrastructure. The few studies in Europe that have investigated brown bear activity have demonstrated a predominantly nocturnal and ‘shy’ behaviour in bears. There is still quite a debate on whether the shy, nocturnal bears of Europe are the result of centuries of persecution by men (genetically fixed trait) or whether hunting and the high disturbance potential in the multi‐use landscapes are the driving force (individually learnt trait). We analysed the activity pattern of 16 individual bears monitored for 3372 h between May and October 1982–1998 in the Dinaric Mountains of Slovenia and Croatia. The data were collected via time sampling and basically analysed using two approaches: a general linear model with seasonal component to delineate the most important variables influencing the activity pattern and level and cluster analysis to group bears according to their 24‐h activity pattern. Time of day and age were the most important variables predicting activity. Although individual variation in the activity pattern was high among individual bears, in general, yearlings were more diurnal and had a less distinct difference between day‐ and night‐time activity levels than adult bears. Subadults were somewhat intermediate to adults and yearlings. We believe that nocturnal behaviour is most likely driven through negative experiences with humans, giving space for much individual variation. More research is needed to prove the causal relationship of nocturnal behaviour and the degree of disturbance that an individual bear is exposed to.