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The WEN group has many projects going on in the tropics, which are usually too far for the duration of the BSc Afstudeerproject. However, there are often many desk-based studies available with previously collected data. General themes are wildlife conservation, sustainable land use and remote sensing, such as modeling data from camera traps or bioacoustics.

The National Park Utrechtse Heuvelrug (NPUH) consists of ca. 20,000 ha contiguous and diverse forest and heathland on sandy soils. The area is situated in the province of Utrecht (the Netherlands). Typically NPUH is fragmented by national, provincial and local roads and railways that are fenced to prevent animal collisions. This created compartments in which management goals differ and animal migration is limited. To reconnect the fragments, fauna overpasses have been built since 1988 under the multi-year programme of defragmentation (meerjarenplan ontsnippering, MJPO), a government-funded programme. The general aim of the project is to understand how medium-sized to large-sized mammals use the network of fauna overpasses. More specifically questions such as, how fauna management or recreation disturbance influences the use of the fauna overpasses, where obstacles lie in the optimal connectivity of the fragments and how managers can overcome these on a regional or local scale. To measure the use of the fauna overpasses by mammals, we use a standardised wildlife camera trapping method consisting of a pair of camera traps per fauna overpasses. Depending on the timing of the project, students can help in setting up the project or help in data-collection and data-analysis. It is also possible to study human or policy related questions, which are equally important in understanding the effectivity of the network.  

To assess wildlife densities many different methods are used (see other project). One of these methods is the Random Encounter Model (Rowcliffe, 2008). To calculate speed from camera traps it is important to correctly estimate the detection zone of a camera trap. This project aims to understand and compare metrics derived from camera trapping data.  

Sub-projects:  

   Detection zone estimation (Hofmeester v.s. REM)
   Speed estimation 

Approximately 1 out of every 3 European forest species are dependent on deadwood. Because of a history of young forest and deadwood habitat depletion till the end of last century, the Dutch deadwood-fauna is severely degraded. Forest managers are doing efforts of deadwood enrichment (creation and leaving deadwood) to stimulate this biodiversity, but the exact response of the species community is unknown, especially in a degraded and fragmented Dutch landscape. A range of treatments (felling, uprooting, damaging etc.) and timing (summer, winter, spring, fall) are used in a standardised ecological experiment to explore:  

   to find out how fragmentation shapes skewed communities and impact deadwood decomposition  
   how timing of deadwood creation shapes saproxylic beetle communities
   the use of saproxylic (deadwood inhabiting) beetles as indicators or ‘barometers’ of deadwood habitat quality

Method: For this topic, you need fieldwork, lab-work (identification and sorting of insect specimen) and data-analysis. There are also opportunities for molecular techniques, if interested. Depending on the research topic you use a variety of these methods.  Period: all year round. September- April or November till end of summer.  

Required background

   Basic knowledge of European/Dutch arthropod fauna (at least being able to order level, preferably experience with identification of arthropods to family level). Previous experience with identification keys and insect identification is convenient but not mandatory, but you should be willing to learn is.
   Experience with fieldwork and problem-solving in rough forest environments
   Capable of doing some labour-intensive fieldwork on long days. The fieldwork is done in during the year, mostly in summer and spring, and requires walking and carrying traps or samples through rough terrain, in various weather conditions.  
   A basic knowledge of R and data-analysis 

Aim: Quantify how mammal community composition varies across Europe along gradients of human pressure, and test how climate change, land-use change, and fragmentation interact to reshape these communities. We will also assess whether, and how, species’ daily activity patterns shift under these stressors.

This project has three components:

1. compiling and harmonising camera-trap datasets from open sources (e.g., Wildlife Insights; GBIF camera-trap records);
2. building an analysis-ready database, including metadata checks, deduplication, mammal-only filtering, and quality control (e.g., removing baited or unusually elevated cameras); and
3. compiling species-trait data for European mammals (e.g., PanTHERIA, EltonTraits), standardising names, and preparing a clean trait dataset for target species.

Along the way, you’ll gain experience with heterogeneous data formats, dataset integration, literature review, and good data-management practice.