Search

Changing environmental conditions and land use are threatening biodiversity on a large scale, making successful conservation and restoration essential for maintaining biodiversity. Planning of such efforts profits from information about where conditions are suitable for biotopes, to evaluate how likely successful conservation or restoration is at these sites. This study uses the distribution model Maxent to identify varying levels of conservation and restoration potential for 29 different biotopes in the central European region of Bavaria, Germany, by comparing the environmentally suitable areas identified by models with the current distribution of each biotope. We identified a conservation potential when a biotope occurred under suitable environmental conditions and a restoration potential when suitable environmental conditions were present at a site where the biotope was not observed. We found that 69.57% of biotope observations occurred under suitable environmental conditions representing a large conservation potential. Also, 22 biotopes showed more restoration potential than their current distribution and both conservation and restoration potential showed a similar geographical distribution. The approach used in this study can provide valuable insights for conservation and restoration decision-making by suggesting priority areas for the conservation and restoration of multiple biotopes. Further, it could be applied in other regions globally and by incorporating future climate projections it could identify particularly resilient locations for biotope conservation or restoration. [ABSTRACT FROM AUTHOR]

Aim: Environmental conditions define the suitability of an area for biotopes, and any area can be suitable for several biotopes. However, most previous studies modelled the distribution of single biotopes ignoring the potential co‐occurrence of biotopes in one area, which limits the usefulness of such models for conservation and restoration planning. In this study, we described the potential biotope composition of an area in response to environmental conditions. Location: Bavaria, Federal State of Germany. Methods: Based on the Bavarian biotope mapping data, we modelled the distribution of 29 terrestrial biotopes based on six climate variables and six chemical and four physical soil properties using the species distribution modelling algorithm Maxent. Results: For most biotopes, we found that climate variables were more important than soil variables for the biotope distribution and that the area of the predicted biotope distribution was larger than the observed distribution. The potential biotope composition illustrated that while 8% of the area in Bavaria was not sufficiently suitable for any analysed biotope, 92% of the modelled area in Bavaria was suitable for at least one biotope, 84% for two and 77% for at least three biotopes. The difference in suitability between the most suitable biotopes in composition was minor. Further, over one‐quarter of the modelled area was suitable for 6–8 different biotopes. Main Conclusions: Our study showed that considering a composition of potentially suitable biotopes in a raster cell, instead of only the most suitable biotope, provides valuable information to identify conservation priorities and restoration opportunities. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has led to temporary changes in human–animal interactions due to changes in human activities. Here, we report on a surge in hedgehog observations during the first COVID‐19 lockdown in Germany in 2020, on the citizen science Web portal "Igel in Bayern" (Hedgehogs in Bavaria) in Germany. This increase in comparison with previous years was attributed to an increase in the number of people reporting hedgehog observations, rather than an increase in the number of hedgehog observations made by each observer. Additionally, in contrast to other studies on the effects of a COVID‐19 lockdown on observations recorded by citizen science projects, the share of observations made in more urbanized areas during the lockdown time was not higher than the change observed in less urbanized areas. This is possibly a result of the differences in COVID‐19 measures between Germany and other countries where preceding studies were carried out, in particular the lack of measures limiting traveling outdoor activities for citizens. [ABSTRACT FROM AUTHOR]