Predation risk is a major driver of the distribution of prey animals, which typically show strong responses to cues for predator presence. An unresolved question is whether naïve individuals respond to mimicked cues, and whether such cues can be used to deter prey. We investigated whether playback of wolf sounds induces fear responses in naïve ungulates in a human-dominated landscape from which wolves have been eradicated since 1879. We conducted a playback experiment in mixed-coniferous and broadleaved forest that harboured three cervid and one suid species. At 36 locations, we played wolf sounds, sounds of local sheep or no sounds, consecutively, in random order, and recorded visit rate and group size, using camera traps. Visit rates of cervids and wild boar showed a clear initial reduction to playback of both wolf and sheep sounds, but the type of response differed between sound, forest type and species. For naïve wild boar in particular, responses to predator cues depended on forest type. Effects on visit rate disappeared within 21 days. Group sizes in all the species were not affected by the sound treatment. Our findings suggest that the responses of naïve ungulates to wolf sound seem to be species specific, depend on forest type and wear off in time, indicating habituation. Before we can successfully deter ungulates using predator sound, we should further investigate how different forest types affect the perception of naïve ungulates to these sounds, as responses to predator sound may depend on habitat characteristics.
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There is consensus that plant species richness enhances plant productivity within natural grasslands, but the underlying drivers remain debated. Recently, differential accumulation of soil‐borne fungal pathogens across the plant diversity gradient has been proposed as a cause of this pattern. However, the below‐ground environment has generally been treated as a ‘black box’ in biodiversity experiments, leaving these fungi unidentified. Using next generation sequencing and pathogenicity assays, we analysed the community composition of root‐associated fungi from a biodiversity experiment to examine if evidence exists for host specificity and negative density dependence in the interplay between soil‐borne fungi, plant diversity and productivity. Plant species were colonised by distinct (pathogenic) fungal communities and isolated fungal species showed negative, species‐specific effects on plant growth. Moreover, 57% of the pathogenic fungal operational taxonomic units (OTUs) recorded in plant monocultures were not detected in eight plant species plots, suggesting a loss of pathogenic OTUs with plant diversity. Our work provides strong evidence for host specificity and negative density‐dependent effects of root‐associated fungi on plant species in grasslands. Our work substantiates the hypothesis that fungal root pathogens are an important driver of biodiversity‐ecosystem functioning relationships.
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The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted—modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits.These results provide not only a holistic pan-Amazonian picture of tree death but largescale evidence for the overarching importance of the growth–survival trade-off in driving tropical tree mortality.
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Wildlife crime is an important driver of biodiversity loss and disrupts the social and economic activities of local communities. During the last decade, poaching of charismatic megafauna, such as elephant and rhino, has increased strongly, driving these species to the brink of extinction. Early detection of poachers will strengthen the necessary law enforcement of park rangers in their battle against poaching. Internationally, innovative, high tech solutions are sought after to prevent poaching, such as wireless sensor networks where animals function as sensors. Movement of individuals of widely abundant, non-threatened wildlife species, for example, can be remotely monitored ‘real time’ using GPS-sensors. Deviations in movement of these species can be used to indicate the presence of poachers and prevent poaching. However, the discriminative power of the present movement sensor networks is limited. Recent advancements in biosensors led to the development of instruments that can remotely measure animal behaviour and physiology. These biosensors contribute to the sensitivity and specificity of such early warning system. Moreover, miniaturization and low cost production of sensors have increased the possibilities to measure multiple animals in a herd at the same time. Incorporating data about within-herd spatial position, group size and group composition will improve the successful detection of poachers. Our objective is to develop a wireless network of multiple sensors for sensing alarm responses of ungulate herds to prevent poaching of rhinos and elephants.
