Spatial behavior in rehabilitated orangutans in Sumatra: Where do they go?

Wildlife restoration is one of the key components of conservation strategies, and this includes the rehabilitation and release of animals confiscated from wildlife traffickers. When primates are re-introduced, most individuals need a pre-release training to acquire the skills needed to survive in the wild. Pre-release training may either negatively or positively affect primate post-release behavior and survival. Post-release behavior, however, has rarely been monitored even though it is the only means to assess the survival of released individuals. Here, we present a thorough analysis of data from a 3-year radio tracking study on 32 orangutans (Pongo abelii) released in Sumatra after their rehabilitation. We investigated whether and how the age at release, the duration of the pre-release rehabilitation and training, and the release location affected the post-release individual spatial behavior. Orangutans released at older age exhibited post-release habitat selection patterns that were more comparable to that shown by wild conspecifics, i.e., they chose areas closer to rivers and at lower elevations (150-250 meters a.s.l.) where previous research had documented greater food availability. In contrast, individuals released at younger age showed a stronger spatial dependency on the rehabilitation station and exhibited disrupted habitat selection patterns; although after several months after the release all individuals tended to decrease their spatial reliance on the rehabilitation facility. This study indicates that the rehabilitation of individuals for a longer period and their release further from the rehabilitation station have facilitated the subsequent development of more natural spatial behavior, i.e. driven by food availability rather than by the dependence on care-giving human facility. Our study provides indications on how to improve the rehabilitation and release of confiscated orangutans, highlighting the importance of the age at release, the length of the rehabilitation program, and the location of the release site.

How many wolves (Canis lupus) fit into Germany? The role of assumptions in predictive rule-based habitat models for habitat generalists.

Due to legislative protection, many species, including large carnivores, are currently recolonizing Europe. To address the impending human-wildlife conflicts in advance, predictive habitat models can be used to determine potentially suitable habitat and areas likely to be recolonized. As field data are often limited, quantitative rule based models or the extrapolation of results from other studies are often the techniques of choice. Using the wolf (Canis lupus) in Germany as a model for habitat generalists, we developed a habitat model based on the location and extent of twelve existing wolf home ranges in Eastern Germany, current knowledge on wolf biology, different habitat modeling techniques and various input data to analyze ten different input parameter sets and address the following questions: (1) How do a priori assumptions and different input data or habitat modeling techniques affect the abundance and distribution of potentially suitable wolf habitat and the number of wolf packs in Germany? (2) In a synthesis across input parameter sets, what areas are predicted to be most suitable? (3) Are existing wolf pack home ranges in Eastern Germany consistent with current knowledge on wolf biology and habitat relationships? Our results indicate that depending on which assumptions on habitat relationships are applied in the model and which modeling techniques are chosen, the amount of potentially suitable habitat estimated varies greatly. Depending on a priori assumptions, Germany could accommodate between 154 and 1769 wolf packs. The locations of the existing wolf pack home ranges in Eastern Germany indicate that wolves are able to adapt to areas densely populated by humans, but are limited to areas with low road densities. Our analysis suggests that predictive habitat maps in general, should be interpreted with caution and illustrates the risk for habitat modelers to concentrate on only one selection of habitat factors or modeling technique.