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1. Entomological studies often aim to estimate species distribution, community composition, or species-richness patterns. False absences can, however, bias these estimates and should consequently not be overlooked in insect studies. Multi-species occupancy models (MSOMs) afford a flexible solution to cover the main topics in ecological entomology while dealing with detectability issues. 2. We sampled Orthoptera communities at 81 mountain grasslands sites in France, using three sampling techniques: sighting, listening, and sweep netting. Five plots were sampled per site. This sampling design allowed MSOMs to be used to estimate richness, occupancy, and detection probabilities while accounting for the effect of covariates. We also used MSOMs to evaluate the efficiency of the survey design and to assess the effects of sampling optimisation. 3. The estimates obtained for altitudinal distribution were reliable, with known species distributions confirming the relevance of MSOMs to model the effects of covariates on Orthoptera communities. The species-specific detection probability was often less than one and varied with the detection technique used and the grass height, confirming the need to deal with detection issues in orthopteran studies. 4. We estimated an inventory completeness superior to 0.80 for 93% of the sites, and an overall detection probability superior to 0.95 for 52% of the species, suggesting the sampling design was suitable for studying occupancy in Orthoptera communities. We also found that the sweep netting step may be omitted or the number of plots reduced without affecting species detectability or inventory completeness. Those recommendations may help to optimise future sampling strategies.
Aim Optimum shifts in species–environment relationships are intensively studied in a wide range of ecological topics, including climate change and species invasion. Numerous statistical methods are used to study optimum shifts, but, to our knowledge, none explicitly estimate it. We extended an existing model to explicitly estimate optimum shifts for multiple species having symmetrical response curves. We called this new Bayesian hierarchical model the Explicit Hierarchical Model of Optimum Shifts (EHMOS). Location All locations. Taxon All taxa. Methods In a simulation study, we compared the accuracy of EHMOS to a mean comparison method and a Bayesian generalized linear mixed model (GLMM). Specifically, we tested if the accuracy of the methods was sensitive to (1) sampling design, (2) species optimum position and (3) species ecological specialization. In addition, we compared the three methods using a real dataset of investigated optimum shifts in 24 Orthopteran species between two time periods along an elevation gradient. Results Of all the simulated scenarios, EHMOS was the most accurate method. GLMM was the most sensitive method to species optimum position, providing unreliable estimates in the presence of marginal species, that is, species with an optimum close to a sampling boundary. The mean comparison method was also sensitive to species optimum position and ecological specialization, especially in an unbalanced sampling design, with high negative bias and low interval coverage compared to EHMOS. The case study results obtained with EHMOS were consistent with what is expected considering ongoing climate change, with mostly upward shifts, which further improved confidence in the accuracy of the EHMOS method. Main Conclusions Explicit Hierarchical Model of Optimum Shifts could be used for a wide range of topics and extended to produce new insights, especially in climate change studies. Explicit estimation of optimum shifts notably allows investigation of ecological assumptions that could explain interspecific variability of these shifts.
La Directive Habitats-Faune-Flore (DHFF) prévoit un suivi dans le temps de l’état de conservation des espèces d’intérêt communautaire. En France, cette surveillance reste peu développée pour les invertébrés. Des protocoles nationaux sont proposés pour sept espèces de coléoptères saproxyliques rares ou à caractère « parapluie » : Stephanopachys linearis (Kugelann, 1792) et Stephanopachys substriatus (Paykull, 1800) (Bostrichidae), Cerambyx cerdo Linnaeus, 1758 et Rosalia alpina (Linnaeus, 1758) (Cerambycidae), Osmoderma eremita (Scopoli, 1763) (Trichiinae), Limoniscus violaceus (P.W.J. Müller,1821) (Elateridae) et Rhysodes sulcatus (Fabricius, 1787) (Rhysodinae). La DHFF définit quatre paramètres d’état de conservation : l’aire de répartition, la taille des populations, l’habitat d’espèce et les perspectives futures. À partir de la littérature sur l’écologie et la conservation de ces espèces et de l’expertise des auteurs sur les populations françaises, la réflexion a porté sur des protocoles économiquement et techniquement réalistes pour effectuer une veille à large échelle. Pour ces espèces rares et discrètes, les mesures directes des tailles de populations ne paraissent pas opérationnelles. Il est proposé de confirmer l’occupation des sites (voire de détecter de nouvelles localités) et de suivre les micro-habitats clés de chacune de ces espèces. Ce focus sur l’habitat d’espèce doit permettre de faire le lien avec les pressions et les mesures de gestion. Un recours à la modélisation et aux observatoires participatifs est envisagé pour préciser la distribution de certaines espèces. Il est préconisé de mobiliser des statistiques de l’inventaire forestier national en les affinant à l’échelle de la distribution de chaque espèce. Un tableau résume les propositions pour chaque espèce : paramètres visés, plan et unités d’échantillonnage, techniques et matériel, périodes favorables, possibilité d’impliquer les gestionnaires, périodicité des relevés, types d’indicateurs, éléments de coûts et perspectives de recherche.Ces propositions sont discutées en termes de moyens nécessaires et au regard des rares protocoles disponibles dans les pays concernés par ces espèces, notamment en Italie.
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