Summary
The integration of conservation into production forest management is crucial to achieve desired biodiversity goals at the EU level. Retention forestry, which was introduced as a tool to mitigate the negative impact of transformation and homogenization of forests, is now common practice in Central European forests. The design of efficient retention strategies hinges on ecological knowledge, yet research-based evidence for its effectiveness is lacking. In particular, responses of large terrestrial mammals to variable retention harvesting are unknown. I will address this knowledge gap by using a combination of advanced techniques and statistical methods to investigate how the large mammal community changes in response to varying levels of retention forestry in multiple-use forests, and assess the interplay between retention forestry and the surrounding landscape. I will (a) quantify mammal species richness, species-specific abundance and β-diversity across a gradient of retention forestry and landscape forest cover, and (b) determine a threshold of retention at which significant responses occur. I expect that retention will enhance mammal diversity, but not below a certain threshold or below a certain amount of forest cover. I will use the Black Forest in Southwestern Germany as a model system for multiple-use forests in Central Europe, and conduct camera-trapping in 135 plots embedded in patches of mixed-montane forests which differ along 2 gradients of retention and landscape fragmentation. I will use multispecies hierarchical modeling in a Bayesian framework to quantify the effects of retention forestry on mammal species at different spatial grains. This multidisciplinary research combines spatial ecology, with landscape and forest ecology and will integrate for the first time ecological study of large mammals and retention forestry in Central European landscapes.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/894290 |
| Start date: | 01-01-2021 |
| End date: | 31-12-2022 |
| Total budget - Public funding: | 162 806,40 Euro - 162 806,00 Euro |
Cordis data
Original description
The integration of conservation into production forest management is crucial to achieve desired biodiversity goals at the EU level. Retention forestry, which was introduced as a tool to mitigate the negative impact of transformation and homogenization of forests, is now common practice in Central European forests. The design of efficient retention strategies hinges on ecological knowledge, yet research-based evidence for its effectiveness is lacking. In particular, responses of large terrestrial mammals to variable retention harvesting are unknown. I will address this knowledge gap by using a combination of advanced techniques and statistical methods to investigate how the large mammal community changes in response to varying levels of retention forestry in multiple-use forests, and assess the interplay between retention forestry and the surrounding landscape. I will (a) quantify mammal species richness, species-specific abundance and β-diversity across a gradient of retention forestry and landscape forest cover, and (b) determine a threshold of retention at which significant responses occur. I expect that retention will enhance mammal diversity, but not below a certain threshold or below a certain amount of forest cover. I will use the Black Forest in Southwestern Germany as a model system for multiple-use forests in Central Europe, and conduct camera-trapping in 135 plots embedded in patches of mixed-montane forests which differ along 2 gradients of retention and landscape fragmentation. I will use multispecies hierarchical modeling in a Bayesian framework to quantify the effects of retention forestry on mammal species at different spatial grains. This multidisciplinary research combines spatial ecology, with landscape and forest ecology and will integrate for the first time ecological study of large mammals and retention forestry in Central European landscapes.Status
CLOSEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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