The successional dynamics of forests—from canopy openings to regeneration, maturation, and decay—influence the amount and heterogeneity of resources available for forest‐dwelling organisms. Conservation has largely focused only on selected stages of forest succession (e.g., late‐seral stages). However, to develop comprehensive conservation strategies and to understand the impact of forest management on biodiversity, a quantitative understanding of how different trophic groups vary over the course of succession is needed. We classified mixed mountain forests in Central Europe into nine successional stages using airborne LiDAR. We analysed α‐ and β‐diversity of six trophic groups encompassing approximately 3,000 species from three kingdoms. We quantified the effect of successional stage on the number of species with and without controlling for species abundances and tested whether the data fit the more‐individuals hypothesis or the habitat heterogeneity hypothesis. Furthermore, we analysed the similarity of assemblages along successional development. The abundance of producers, first‐order consumers, and saprotrophic species showed a U‐shaped response to forest succession. The number of species of producer and consumer groups generally followed this U‐shaped pattern. In contrast to our expectation, the number of saprotrophic species did not change along succession. When we controlled for the effect of abundance, the number of producer and saproxylic beetle species increased linearly with forest succession, whereas the U‐shaped response of the number of consumer species persisted. The analysis of assemblages indicated a large contribution of succession‐mediated β‐diversity to regional γ‐diversity. Synthesis and applications. Depending on the species group, our data supported both the more‐individuals hypothesis and the habitat heterogeneity hypothesis. Our results highlight the strong influence of forest succession on biodiversity and underline the importance of controlling for successional dynamics when assessing biodiversity change in response to external drivers such as climate change. The successional stages with highest diversity (early and late successional stages) are currently strongly underrepresented in the forests of Central Europe. We thus recommend that conservation strategies aim at a more balanced representation of all successional stages.

Drastic declines in insect populations are a vital concern worldwide. Despite widespread insect monitoring, the significant gaps in the literature must be addressed. Future monitoring techniques must be systematic and global. Advanced technologies and computer solutions are needed. We provide here a review of relevant works to show the high potential for solving the aforementioned problems. Major historical and modern methods of insect monitoring are considered. All major radar solutions are carefully reviewed. Insect monitoring with radar is a well established technique, but it is still a fast-growing topic. The paper provides an updated classification of insect radar sets. Three main groups of insect radar solutions are distinguished: scanning, vertical-looking, and harmonic. Pulsed radar sets are utilized for all three groups, while frequency-modulated continuous-wave (FMCW) systems are applied only for vertical-looking and harmonic insect radar solutions. This work proves the high potential of radar entomology based on the growing research interest, along with the emerging novel setups, compact devices, and data processing approaches. The review exposes promising insect monitoring solutions using compact radar instruments. The proposed compact and resource-effective setups can be very beneficial for systematic insect monitoring.

The high diversity of insects has limited the volume of long‐term community data with a high taxonomic resolution and considerable geographic replications, especially in forests. Therefore, trends and causes of changes are poorly understood. Here we analyse trends in species richness, abundance and biomass of nocturnal macro moths in three quantitative data sets collected over four decades in forests in southern Germany. Two local data sets, one from coppiced oak forests and one from high oak forests included 125K and 48K specimens from 559 and 532 species, respectively. A third regional data set, representing all forest types in the temperate zone of central Europe comprised 735K specimens from 848 species. Generalized additive mixed models revealed temporal declines in species richness (−38%), abundance (−53%) and biomass (−57%) at the regional scale. These were more pronounced in plant host specialists and in dark coloured species. In contrast, the local coppiced oak forests showed an increase, in species richness (+62%), while the high oak forests showed no clear trends. Left and right censoring as well as cross validation confirmed the robustness of the analyses, which led to four conclusions. First, the decline in insects appears in hyper diverse insect groups in forests and affects species richness, abundance and biomass. Second, the pronounced decline in host specialists suggests habitat loss as an important driver of the observed decline. Third, the more severe decline in dark species might be an indication of global warming as a potential driver. Fourth, the trends in coppiced oak forests indicate that maintaining complex and diverse forest ecosystems through active management may be a promising conservation strategy in order to counteract negative trends in biodiversity, alongside rewilding approaches.

Movement ecology of small wild animals is often reliant on radio‐tracking methods due to the size and weight restrictions of available transmitters. In manual radio telemetry, large errors in spatial position and infrequent relocations prevent the effective analysis of small‐scale movement patterns and dynamic aspects of habitat selection. Automatic radio‐tracking systems present a potential solution for overcoming these drawbacks. However, existing systems use customized electronics and commercial software or exclusively record presence/absence data instead of triangulating the position of tagged individuals. We present a low‐cost automatic radio‐tracking system built from consumer electronic devices that can locate the position of radio transmitters under field conditions. We provide information on the hardware components, describe mobile and stationary set‐up options, and offer open‐source software solutions. We describe the workflow from hardware setup and antenna calibration, to recording and processing the data and present a proof of concept for forest‐dwelling bats using a mixed forest as study area. With an average bearing error of 6.8° and a linear error of 21 m within a distance ranging from 65 m to 190 m, the accuracy of our system exceeds that of both traditional methods as well as manual telemetry. This affordable and easy‐to‐use automatic radio‐tracking system complements existing tools in movement ecology research by combining the advantages of lightweight and cost‐efficient radio telemetry with an automatic tracking set‐up.

Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing.