A5009209964- Species Distribution and Climate Change
- Wildlife Ecology and Conservation
- Primate Behavior and Ecology
- Environmental DNA in Biodiversity Studies
- Ecology and Vegetation Dynamics Studies
- Remote Sensing and LiDAR Applications
- Wildlife-Road Interactions and Conservation
- Fire effects on ecosystems
- Remote Sensing in Agriculture
- Forest ecology and management
- Bacteriophages and microbial interactions
- Microbial infections and disease research
- Identification and Quantification in Food
- AI in cancer detection
- Animal Ecology and Behavior Studies
- Conservation, Biodiversity, and Resource Management
- Cell Image Analysis Techniques
- Bat Biology and Ecology Studies
- Human-Animal Interaction Studies
Leibniz Institute for Zoo and Wildlife Research
2018-2025
Technische Universität Berlin
2022-2025
Mississippi State University
2017-2019
Global Wildlife Conservation
2019
Abstract Invertebrate‐derived DNA ( iDNA ), in combination with high throughput sequencing, has been proposed as a cost‐efficient and powerful tool to survey vertebrate species. Previous studies, however, have only provided evidence that vertebrates can be detected using , but not taken the next step of placing these detection events within statistical framework allows for robust biodiversity assessments. Here, we compare concurrent camera‐trap surveys. Leeches were repeatedly collected...
Abstract Habitat degradation and hunting have caused the widespread loss of larger vertebrate species (defaunation) from tropical biodiversity hotspots. However, these defaunation drivers impact in different ways and, therefore, require conservation interventions. We conducted landscape-scale camera-trap surveys across six study sites Southeast Asia to assess how moderate intensive, indiscriminate differentially terrestrial mammals birds. found that functional extinction rates were higher...
Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents unique opportunity broad-scale collaborative species monitoring due its largely non-discriminatory nature, which creates considerable volumes data on relatively wide range This has potential shed light ecology rare, cryptic understudied taxa, with...
Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of region. Vertebrate populations are declining globally due land-use change and hunting, latter frequently referred as "defaunation." This is especially true in Asia where there extensive high human densities. Robust monitoring requires that large volumes vertebrate population data be made available for use by scientific applied communities....
Borneo Malaysia Poachingprojected the distribution of Sunda pangolins in Sabah.Additionally, we assessed accessibility their forest habitats to humans understand potential threats.Our model indicated that, as 2015, approximately half Sabah's land area (39,530 km 2 ) is suitable for pangolins, with 43% protected forests, 38% production and 19% outside these areas.Alarmingly, our data suggest that nearly all (91%) are relatively easily accessible poachers.Our findings provide a state-level...
Abstract While habitat loss and hunting remain the major drivers of biodiversity declines, sublethal disturbances, such as human presence, recreation, noise also impact wildlife. In response, wildlife often adjust their spatiotemporal behaviors. This study assesses how terrestrial responds to disturbances associated with sustainable logging activities. Using camera traps, we conducted a 2‐year continuous survey two compartments within an active, sustainably logged forest reserve in central...
Abstract Environmental DNA (eDNA) and invertebrate‐derived (iDNA) are used to survey biodiversity non‐invasively mitigate difficulties in obtaining wildlife samples, particularly remote areas or for rare species. Recently, eDNA/iDNA were monitor known pathogens; however, most pathogens unknown often evolutionarily divergent. To detect identify novel mammalian viruses from eDNA/iDNA, we a curated set of RNA oligonucleotides as viral baits hybridization capture system coupled with...
Abstract Even with intensive sampling effort, data often remain sparse when estimating population density of elusive species such as the Sunda clouded leopard Neofelis diardi . An inadequate number recaptures can make it difficult to account for heterogeneity in detection parameters. We used from large-scale camera-trapping surveys three forest reserves Sabah, Malaysian Borneo, (1) examine whether a high-density camera-trap network increases females, which tend be more detect, thus improving...
Maximizing detection probability is a common goal for occupancy studies using camera traps data collection.Placing additional cameras at survey station may improve precision of and estimates.However, these benefits are situational potentially influenced by species' physical characteristics behavior.We estimated null probabilities 20 mammalian species with >10 detections multiple sites from one-and two-camera sets 63 stations set in commercial forest reserve Sabah, Malaysian Borneo during...
Abstract Convolutional neural networks (CNNs) and deep learning are powerful robust tools for ecological applications, particularly suited image data. Image segmentation (the classification of all pixels in images) is one such application can, example, be used to assess forest structural metrics. While CNN‐based methods applications have been suggested, widespread adoption research has slow, likely due technical difficulties implementation CNNs lack toolboxes ecologists. Here, we present R...
Invertebrate-derived DNA (iDNA), in combination with high throughput sequencing, has been proposed as a cost-efficient and powerful tool to survey vertebrate species. Previous studies, however, have only provided evidence that vertebrates can be detected using iDNA, but not taken the next step of placing these detection events within statistical framework allows for robust biodiversity assessments. Here, we compare concurrent iDNA camera-trap surveys. Leeches were repeatedly collected close...
ABSTRACT Environmental DNA (eDNA) and invertebrate-derived (iDNA) have been used to survey biodiversity non-invasively mitigate difficulties of obtaining wildlife samples, particularly in remote areas or for rare species. Recently, eDNA/iDNA applied monitor known pathogens, however, most pathogens are unknown often evolutionarily divergent. To detect identify novel mammalian viruses from sources, we a curated set RNA oligonucleotides as viral baits hybridization capture system coupled with...
To offset the declining timber supply by shifting towards more sustainable forestry practices, industrial tree plantations are expanding in tropical production forests. The conversion of natural forests to plantation is generally associated with loss biodiversity and shifts generalist disturbance tolerant communities, but effects mixed-landuse landscapes integrating remain little understood. Using camera traps, we surveyed medium-to-large bodied terrestrial wildlife community across two...
Abstract Forest degradation and hunting are two major drivers of species declines in tropical forests, often associated with forest production activities infrastructure. To assess how the medium‐to‐large bodied terrestrial vertebrate community varied across these main gradients anthropogenic impact, we conducted a camera‐trap survey three reserves central Sabah, Malaysian Borneo, each different past current logging regimes. We analyzed data from 32‐species using Bayesian occupancy model,...
ABSTRACT Understanding environmental factors that influence forest health, as well the occurrence and abundance of wildlife, is a central topic in forestry ecology. However, manual processing field habitat data time-consuming months are often needed to progress from collection interpretation. Computer-assisted tools, such deep-learning applications can significantly shortening time process while maintaining high level accuracy. Here, we propose Habitat-Net: novel method based on...
Abstract Convolutional neural networks (CNNs) and deep learning are powerful robust tools for ecological applications. CNNs can perform very well in various tasks, especially visual tasks image data. Image segmentation (the classification of all pixels images) is one such task example be used to assess forest vertical horizontal structure. While methods have been suggested, widespread adoption research has slow, likely due technical difficulties implementation lack toolboxes ecologists....