Biology subjects

Neyens, T.

Publications and source records attributed to Neyens, T..

4 recordsLinked to original sources

bioRxiv2026

Cladoceran diversity build-up in newly created pondscapes

This study aimed to identify the most important drivers of cladoceran species richness build-up and species accumulation patterns in newly created ponds that collectively form entirely new pondscapes (networks of closely situated ponds in a landscape). A total of 26 newly created ponds across two newly established pondscapes were surveyed repeatedly (n=11) for key environmental pond variables and cladoceran community characteristics during the first three years after the pondscapes creation. The study ponds vary in surface area and maximum depth and cover a wide range of hydroperiods, from permanent to temporary systems with only a short hydroperiod. In total, 16 cladoceran species colonized the newly created ponds within the first three years of the pondscapes existence. Consistent with previous research, Daphnia obtusa was the first species to colonize ponds in both pondscapes. Macrophyte establishment was the most important local factor influencing the accumulation of cladoceran species over time, with vegetated ponds leading to faster species accumulation, likely because of the close association of chydorid species, Simocephalus vetulus and Ceriodaphnia spp with macrophytes. Our observations highlight the role of the establishment of macrophytes for cladoceran species richness build-up during early pond succession and offer valuable insights for designing resilient pondscapes that support rapid cladoceran species accumulation. Statements and DeclarationsThe authors have no conflicts of interest to declare.

ecology↗

bioRxiv2025

Temporal disaggregation through interval-integrated B-splines for the integrated analysis of trapping counts in ecology

O_LIPassive trapping techniques such as pitfall and malaise traps probably constitute the most widely used methods for standardised surveys of invertebrate populations worldwide. These methods typically yield aggregated count data over multi-day trapping periods, often spanning several weeks, during which species activity (i.e. phenology) can vary. The analysis of trapping data collected over temporally misaligned sampling intervals is challenging, hampering the integrated analysis of historically available trapping datasets. C_LIO_LIWe introduce a temporal disaggregation approach using interval-integrated B-splines to analyse data collected over misaligned sampling intervals while accounting for phenological influences. We present computationally efficient Taylor series approximations for integrating exponentiated B-splines over sampling intervals. We further tailor our approach to typical trapping datasets by providing several extensions, including joint species distribution modelling. C_LIO_LIThrough simulations and cross-validation, we demonstrate that our approach of temporal disaggregation outperforms naive approaches and provides improved inference on phenology and other parameters of interest, such as inter-annual trends. The first-order Taylor approximation, which can be fit using regular software routines, properly accounts for heterogeneity in sampling duration and timing, while the second-order Taylor approximation and the exact model additionally allow for improved estimation of phenological patterns. C_LIO_LIBy applying this model to a large pitfall trapping dataset, spanning almost 50 years and over 10,000 trapping events in the Belgian province of Limburg, we illustrate how this approach can be used to reveal phenological, spatiotemporal and co-distributional patterns for 331 spider species. C_LIO_LIThe interval-integrated B-splines approach we present provides a convenient way to infer phenology and other ecological parameters from temporally aggregated count data obtained over misaligned sampling intervals, facilitating the integrated analysis of heterogeneously collected datasets to infer biodiversity trends. C_LI

ecology↗

bioRxiv2022

Simulation-based assessment of the performance of hierarchical abundance estimators for camera trap surveys

The need for knowledge about abundance to guide conservation and management strategies in combination with low detectability of many species has led to a widespread use in ecology and management of a range of hierarchical models (HMs) for abundance. These models also appear like good candidates for inference about local abundance in nature reserves studied by camera traps. However, the best choice among these models is unclear, particularly how they perform in the face of several complicating features of realistic populations that include: (i) movements relative to sites, (ii) multiple detections of unmarked individuals within a single survey, and (iii) low probabilities of detection. We conducted a simulation-based comparison of three HMs (Royle-Nichols, binomial N-mixture and Poisson N-mixture model) in the context of small populations of elusive animals in a single study area, where animals cannot be distinguished individually and hence double counting occurs. We generated count data by simulating camera traps monitoring individuals moving according to a Gaussian random walk. Under the simulated scenarios none of the three HMs yielded accurate abundance estimates. Moreover, the performance of each HM depended on the interpretation of abundance. By pooling abundance estimates for trend estimation, each models performance markedly improves. Overall, the Royle-Nichols and Poisson N-mixture models outperform a binomial N-mixture model. This emphasizes the importance of choosing the appropriate HM for the data problem.

ecology↗

bioRxiv2021

Managing African Swine Fever: Assessing the Potential of Camera Traps in Monitoring Wild Boar Occupancy Trends in Infected and Noninfected Zones, Using Spatio-temporal Statistical Models

The recent spreading of African swine fever (ASF) over the Eurasian continent has been acknowledged as a serious economic threat for the pork industry. Consequently, an extensive body of research focuses on the epidemiology and control of ASF. Nevertheless, little information is available on the combined effect of ASF and ASF-related control measures on wild boar (Sus scrofa) population abundances. This is crucial information given the role of the remaining wild boar that act as an important reservoir of the disease. Given the high potential of camera traps as a non-invasive method for ungulate trend estimation, we assess the effectiveness of ASF control measures using a camera trap network. In this study, we focus on a major ASF outbreak in 2018-2020 in the South of Belgium. This outbreak elicited a strong management response, both in terms of fencing off a large infected zone as well as an intensive culling regime. We apply a Bayesian multi-season site-occupancy model to wild boar detection-nondetection data. Our results show that (1) occupancy rates at the onset of our monitoring period reflect the ASF infection status; (2) ASF-induced mortality and culling efforts jointly lead to decreased occupancy over time; and (3) the estimated mean total extinction rate ranges between 22.44% and 91.35%, depending on the ASF infection status. Together, these results confirm the effectiveness of ASF-control measures implemented in Wallonia (Belgium), which has regained its disease-free status in December 2020, as well as the usefulness of a camera trap network to monitor these effects.

ecology↗