Seabirds pecking polystyrene items in offshore Adriatic Sea waters - Giovanni Bearzi; Silvia Bonizzoni; Federico Fanesi; Simone Tenan; Corrado Battisti (Environmental Science and Pollution Research, 2023)

First spatially-explicit density estimate for a snow leopard population in the Altai Mountains - Valentina Oberosler; Simone Tenan; Claudio Groff; Miha Krofel; Claudio Augugliaro; Bayaraa Munkhtsog; Francesco Rovero (Biodiversity and Conservation, 2022)

Effects of anthropogenic disturbance on primate density at the landscape scale - Nathalie Cavada; Simone Tenan; Claudia Barelli; Francesco Rovero (Conservation Biology, 2019)
Accurate estimations of the abundance of threatened animal populations are required for assessment of species’ status and vulnerability and conservation planning. However, density estimation is usually difficult and resource demanding, so researchers often collect data at local scales. However, anthropogenic pressures most often have landscape‐level effects, for example, through habitat loss and fragmentation. We applied hierarchical distance sampling (HDS) to transect count data to determine the effect of habitat and anthropogenic factors on the density of 3 arboreal primate species inhabiting 5 distinct tropical forests across a landscape of 19,000 km 2 in the Udzungwa Mountains of Tanzania. We developed a novel, multiregion extension of HDS that allowed us to model density and detectability jointly across forests without losing site‐specific information. For all species, the effect of anthropogenic disturbance on density was overwhelmingly negative among metapopulations: −0.63 Angolan colobus (Colobus angolensis palliatus) (95% Bayesian CI −1.03 to −0.27), −0.54 Udzungwa red colobus (Procolobus gordonorum) (−0.89 to −0.22), and −0.33 Sykes' monkey (Cercopithecus mitis monoides) (−0.63 to −0.07). Some responses to habitat factors were shared, notably the negative effect of elevation and the positive effect of climber coverage. These results are important for conservation science and practice because: the among‐populations negative responses to anthropogenic disturbance provides a foundation for development of conservation plans that hold at the landscape scale, which is a comprehensive and cost‐efficient approach; the among‐species consistency in responses suggests conservation measures may be generalized at the guild level, which is especially relevant given the functional importance of primates in tropical rainforests; and the greater primate densities in areas at low elevation, which are closer to human settlements, point to specific management recommendations, such as the creation of buffer zones and prioritization of areas for protection.

Assessing the effect of density on population growth when modeling individual encounter data - Simone Tenan; Giacomo Tavecchia; Daniel Oro; Roger Pradel (Ecology, 2019)
The relative role of density‐dependent and density‐independent variation in vital rates and population size remains largely unsolved. Despite its importance to the theory and application of population ecology, and to conservation biology, quantifying the role and strength of density dependence is particularly challenging. We present a hierarchical formulation of the temporal symmetry approach, also known as the Pradel model, that permits estimation of the strength of density dependence from capture–mark–reencounter data. A measure of relative population size is built in the model and serves to detect density dependence directly on population growth rate. The model is also extended to account for temporal random variability in demographic rates, allowing estimation of the temporal variance of population growth rate unexplained by density dependence. We thus present a model‐based approach that enable to test and quantify the effect of density‐dependent and density‐independent factors affecting population fluctuations in a single modeling framework. More generally, we use this modeling framework along with simulated and empirical data to show the value of including density dependence when modeling individual encounter data without the need for auxiliary data.

Climate‐driven vital rates do not always mean climate‐driven population - Giacomo Tavecchia; Simone Tenan; Roger Pradel; José‐Manuel Igual; Meritxell Genovart; Daniel Oro (Global Change Biology, 2016)
Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate‐driven trajectories even when local vital rates are climate dependent. We illustrated this using individual‐based data on a trans‐equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large‐scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate‐driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate‐dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate‐driven projections.

Evaluating mortality rates with a novel integrated framework for nonmonogamous species - Simone Tenan; Aaron Iemma; Natalia Bragalanti; Paolo Pedrini; Marta De Barba; Ettore Randi; Claudio Groff; Meritxell Genovart (Conservation Biology, 2016)
The conservation of wildlife requires management based on quantitative evidence, and especially for large carnivores, unraveling cause‐specific mortalities and understanding their impact on population dynamics is crucial. Acquiring this knowledge is challenging because it is difficult to obtain robust long‐term data sets on endangered populations and, usually, data are collected through diverse sampling strategies. Integrated population models (IPMs) offer a way to integrate data generated through different processes. However, IPMs are female‐based models that cannot account for mate availability, and this feature limits their applicability to monogamous species only. We extended classical IPMs to a two‐sex framework that allows investigation of population dynamics and quantification of cause‐specific mortality rates in nonmonogamous species. We illustrated our approach by simultaneously modeling different types of data from a reintroduced, unhunted brown bear ( Ursus arctos ) population living in an area with a dense human population. In a population mainly driven by adult survival, we estimated that on average 11% of cubs and 61% of adults died from human‐related causes. Although the population is currently not at risk, adult survival and thus population dynamics are driven by anthropogenic mortality. Given the recent increase of human‐bear conflicts in the area, removal of individuals for management purposes and through poaching may increase, reversing the positive population growth rate. Our approach can be generalized to other species affected by cause‐specific mortality and will be useful to inform conservation decisions for other nonmonogamous species, such as most large carnivores, for which data are scarce and diverse and thus data integration is highly desirable.