Highlights d Ungulates moved to track forage in landscapes with wavelike spring green-up d Patterns of green-up explained where migratory behavior occurred in many ecosystems d At the species level, migrants and residents received equivalent foraging benefits d Movement tactics represent behavioral adaptations to specific landscapes

The most common framework under which ungulate migration is studied predicts that it is driven by spatio–temporal variation in plant phenology, yet other hypotheses may explain differences within and between species. To disentangle more complex patterns than those based on single species/ single populations, we quantified migration variability using two sympatric ungulate species differing in their foraging strategy, mating system and physiological constraints due to body size. We related observed variation to a set of hypotheses. We used GPS‐collar data from 537 individuals in 10 roe Capreolus capreolus and 12 red deer Cervus elaphus populations spanning environmental gradients across Europe to assess variation in migration propensity, distance and timing. Using time‐to‐event models, we explored how the probability of migration varied in relation to sex, landscape (e.g. topography, forest cover) and temporally‐varying environmental factors (e.g. plant green‐up, snow cover). Migration propensity varied across study areas. Red deer were, on average, three times more migratory than roe deer (56% versus 18%). This relationship was mainly driven by red deer males which were twice as migratory as females (82% versus 38%). The probability of roe deer migration was similar between sexes. Roe deer (both sexes) migrated earliest in spring. While territorial male roe deer migrated last in autumn, male and female red deer migrated around the same time in autumn, likely due to their polygynous mating system. Plant productivity determined the onset of spring migration in both species, but if plant productivity on winter ranges was sufficiently high, roe deer were less likely to leave. In autumn, migration coincided with reduced plant productivity for both species. This relationship was stronger for red deer. Our results confirm that ungulate migration is influenced by plant phenology, but in a novel way, that these effects appear to be modulated by species‐specific traits, especially mating strategies.

Humans, as super predators, can have strong effects on wildlife behaviour, including profound modifications of diel activity patterns. Subsequent to the return of large carnivores to human‐modified ecosystems, many prey species have adjusted their spatial behaviour to the contrasting landscapes of fear generated by both their natural predators and anthropogenic pressures. The effects of predation risk on temporal shifts in diel activity of prey, however, remain largely unexplored in human‐dominated landscapes. We investigated the influence of the density of lynx Lynx lynx, a nocturnal predator, on the diel activity patterns of their main prey, the roe deer Capreolus capreolus, across a gradient of human disturbance and hunting at the European scale. Based on 11 million activity records from 431 individually GPS‐monitored roe deer in 12 populations within the EURODEER network (http://eurodeer.org), we investigated how lynx predation risk in combination with both lethal and non‐lethal human activities affected the diurnality of deer. We demonstrated marked plasticity in roe deer diel activity patterns in response to spatio‐temporal variations in risk, mostly due to human activities. In particular, roe deer decreased their level of diurnality by a factor of 1.37 when the background level of general human disturbance was high. Hunting exacerbated this effect, as during the hunting season deer switched most of their activity to night‐time and, to a lesser extent, to dawn, although this pattern varied noticeably in relation to lynx density. Indeed, in the presence of lynx, their main natural predator, roe deer were relatively more diurnal. Overall, our results revealed a strong influence of human activities and the presence of lynx on diel shifts in roe deer activity. In the context of the recovery of large carnivores across Europe, we provide important insights about the effects of predators on the behavioural responses of their prey in human‐dominated ecosystems. Modifications in the temporal partitioning of ungulate activity as a response to human activities may facilitate human–wildlife coexistence, but likely also have knock‐on effects for predator–prey interactions, with cascading effects on ecosystem functioning.

Metabarcoding is a promising DNA-based method for identifying airborne pollen from environmental samples with advantages over microscopic methods. This method requires several preparatory steps of the samples, with the extraction protocol being of fundamental importance to obtain an optimal DNA yield. Currently, there is no consensus in sample preparation and DNA extraction, especially for gravimetric pollen samplers. Therefore, the aim of this study was to develop protocols to process environmental samples for pollen DNA extraction and further metabarcoding analysis, and to assess the efficacy of these protocols for the taxonomic assignment of airborne pollen, collected by gravimetric (Tauber trap) and volumetric samplers (Burkard spore trap). Protocols were tested across an increasing complexity of samples, from single-species pure pollen to environmental samples. A short fragment (about 150 base pair) of chloroplast DNA was amplified by universal primers for plants (trnL). After PCR amplification, amplicons were Sanger-sequenced and taxonomic assignment was accomplished by comparison to a custom-made reference database including chloroplast DNA sequences of 46 plant families, including most of the anemophilous taxa occurring in the study area (Trentino, Italy, Eastern Italian Alps). Using as a benchmark the classical morphological pollen analysis, it emerged that DNA metabarcoding is applicable efficiently across a complexity of samples, provided that sample preparation, DNA extraction and amplification protocols are specifically optimized.

Digital tracking technologies have considerably increased the amount and quality of animal trajectories, enabling the study of habitat use and habitat selection at a fine spatial and temporal scale. However, current approaches do not yet explicitly account for a key aspect of habitat use, namely the sequential variation in the use of different habitat features. To overcome this limitation, we propose a tree-based approach that makes use of sequence analysis methods, derived from molecular biology, to explore and identify ecologically relevant sequential patterns in habitat use by animals. We applied this approach to ecological data consisting of simulated and real trajectories from a roe deer population (Capreolus capreolus), expressed as ordered sequences of habitat use. We show that our approach effectively captured spatio-temporal patterns of sequential habitat use by roe deer. In our case study, individual sequences were clustered according to the sequential use of the elevation gradient (first order) and of open/closed habitats (second order). We provided evidence for several behavioural processes, such as migration and daily alternating habitat use. Some unexpected patterns, such as homogeneous sequences of use of open habitat, could also be identified. Our findings advocate the importance of dealing with the sequential nature of movement data. Approaches based on sequence analysis methods are particularly useful and effective since they allow exploring temporal patterns of habitat use in a synthetic and visually captive manner. The proposed approach represents a useful and effective way to classify individual movement behaviour across populations and species. Ultimately, this method can be applied to explore the temporal scale of ecological processes based on movement

Monitoring biodiversity is of increasing importance in natural ecosystems. Metabarcoding can be used as a powerful molecular tool to complement traditional biodiversity monitoring, as total environmental DNA can be analyzed from complex samples containing DNA of different origin. The aim of this research was to demonstrate the potential of pollen DNA metabarcoding using the chloroplast trnL partial gene sequencing to characterize plant biodiversity. Collecting airborne biological particles with gravimetric Tauber traps in four Natura 2000 habitats within the Natural Park of Paneveggio Pale di San Martino (Italian Alps), at three-time intervals in 1 year, metabarcoding identified 68 taxa belonging to 32 local plant families. Metabarcoding could identify with finer taxonomic resolution almost all non-rare families found by conventional light microscopy concurrently applied. However, compared to microscopy quantitative results, Poaceae, Betulaceae, and Oleaceae were found to contribute to a lesser extent to the plant biodiversity and Pinaceae were more represented. Temporal changes detected by metabarcoding matched the features of each pollen season, as defined by aerobiological studies running in parallel, and spatial heterogeneity was revealed between sites. Our results showcase that pollen metabarcoding is a promising approach in detecting plant species composition which could provide support to continuous monitoring required in Natura 2000 habitats for biodiversity conservation.

provided evidence for important behavioral processes, such as day-night habitat alternation. By characterizing sequential habitat use patterns of animals, we may better evaluate the temporal trade-offs in animal habitat use and how they are affected by changes in landscapes.

Context Diel use of forest and open habitats by large herbivores is linked to species-specific needs of multiple and heterogeneous resources. However, forest cover layers might deviate considerably for a given landscape, potentially affecting evaluations of animals’ habitat use. Objectives We assessed inconsistency in the estimates of diel forest use by red and roe deer at GPS location and home range (HR) levels, using two geographic layers: Tree Cover Density (TCD) and Corine Land Cover (CLC). Methods We first measured the classification mismatch of red and roe deer GPS locations between TCD and CLC, also with respect to habitat units’ size. Then, we used Generalised Least Squares models to assess the proportional use of forest at day and night at the GPS location and HR levels, both with TCD and CLC. Results About 20% of the GPS locations were inconsistently classified as forest or open habitat by the two layers, particularly within smaller habitat units. Overall proportion of forest and open habitat, though, was very similar for both layers. In all populations, both deer species used forest more at day than at night and this pattern was more evident with TCD than with CLC. However, at the HR level, forest use estimates were only marginally different between the two layers. Conclusions When estimating animal habitat use, geographic layer choice requires careful evaluation with respect to ecological questions and target species. Habitat use analyses based on GPS locations are more sensitive to layer choice than those based on home ranges.