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Federico Ossi

Publications and source records attributed to Federico Ossi.

3 recordsLinked to original sources

Interacting effects of human presence and landscape modification on birds and mammals

Sustainable human–wildlife coexistence requires a mechanistic understanding of the many ways that humans affect animals. However, progress is hampered by the lack of accessible data measuring the dynamic presence of people. Here, we leverage mobile-device data to disentangle how human presence and landscape modification differentially influence the use of geographic and environmental space for 37 mammal and bird species across the United States. Human presence affected more than 65% of species, with substantial variation across species. For ~60% of species that responded to human activities, the effects were interdependent—animals tended to react more strongly to human presence in less modified habitats. Our results demonstrate that human presence and landscape modification have complex combined effects on wildlife, which need to be considered for effective management.

Science

A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data

Background Social network analysis of animal societies allows scientists to test hypotheses about social evolution, behaviour, and dynamic processes. However, the accuracy of estimated metrics depends on data characteristics like sample proportion, sample size, and frequency. A protocol is urgently needed to assess for bias and robustness of social network metrics estimated for the animal populations especially when a limited number of individuals are monitored. Methods We used GPS telemetry datasets of five ungulate species to combine known social network approaches with novel ones into a comprehensive five-step protocol. To quantify the bias and uncertainty in the network metrics obtained from a partial population, we presented novel statistical methods which are particularly suited for autocorrelated data, such as telemetry relocations. The protocol was validated using a sixth species, the fallow deer, with a known population size where ⇠ 85% of the individuals have been directly monitored. Results Through the protocol, we demonstrated how pre-network data permu tations allow researchers to assess non-random aspects of interactions within a population. The protocol assesses bias in global network metrics, obtains confidence intervals, and quantifies uncertainty of global and node-level network metrics based on the number of nodes in the network. We found that global network metrics like density remained robust even with a lowered sample size, while local network metrics like eigenvector centrality were unreliable for four of the species. The fallow deer network showed low uncertainty and bias even at lower sampling proportions, indicating the importance of a thoroughly sampled population while demonstrating the accuracy of our evaluation methods for smaller samples. Conclusions The protocol allows researchers to analyse GPS-based radio telemetry or other data to determine the reliability of social network metrics. The estimates enable the statistical comparison of networks under di↵erent conditions, such as analysing daily and seasonal changes in the density of a network. The methods can also guide methodological decisions in animal social network research, such as sampling design and allow more accurate ecological inferences from the available data. The R package aniSNA enables researchers to implement this workflow on their dataset, generating reliable inferences and guiding methodological decisions

Article

Wherever I may roam—Human activity alters movements of red deer (Cervus elaphus) and elk (Cervus canadensis) across two continents

Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer ( Cervus elaphus ) and 14 elk ( Cervus canadensis ) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.

Idaho, Montana, Wyoming