Detection probabilities for sessile organisms

Estimation of population sizes and species ranges are central to population and conservation biology. It is widely appreciated that imperfect detection of mobile animals must be accounted for when estimating population size from presence-absence data. Sessile organisms also are imperfectly detected, but correction for detection probability in estimating their population sizes is rare. We illustrate challenges of detection probability and population estimation of sessile organisms using censuses of red wood ant (Formica rufa-group) nests as a case study. These ants, widespread in the northern hemisphere, can make large (up to 2-m tall), highly visible nests. Using data from a mapping campaign by eight observers with varying experience of sixteen 3600-m2 plots in the Black Forest region of southwest Germany, we compared three different statistical approaches (a nest-level data-augmentation patch-occupancy model with event-specific covariates; a plot-level Bayesian and maximum likelihood model; non-parametric Chao-type estimators) for quantifying detection probability of sessile organisms. Detection probabilities by individual observers of red wood ant nests ranged from 0.31 – 0.64 for small nests, depending on observer experience and nest size (detection rates were approximately 0.17 higher for large nests), but not on habitat characteristics (forest type, local vegetation). Robust estimation of population density of sessile organisms – even highly apparent ones such as red wood ant nests – thus requires estimation of detection probability, just as it does when estimating population density of rare or cryptic species. Our models additionally provide approaches to calculate the number of observers needed for a required level of accuracy. Estimating detection probability is vital not only when censuses are conducted by experts, but also when citizenscientists are engaged in mapping and monitoring of both common and rare species.Organismic and Evolutionary Biolog

Ecological Monitoring with Spy Satellite Images—The Case of Red Wood Ants in Romania

Dynamics of habitat conditions drive important changes in distribution and abundance of animal species making monitoring an important but also a challenging task when data from the past are scarce. We compared the distribution of ant mounds in the 1960s with recent inventories (2018), looking at changes in canopy cover over time, in a managed forest. Both historical and recent sources of information were used. Habitat suitability at present was determined using a Normalized Difference Vegetation Index (NDVI) image as a proxy for stand canopy cover. The NDVI product was obtained using Google Earth Engine and Sentinel 2 repository. For past conditions (no spectral information available), presence of edges and more open canopies was assessed on a Corona spy-satellite image and based on information from old forest management plans. A threshold distance of 30 m was used to assess location of ant nests compared to favorable habitats. Both old and new information sources showed that ants prefer intermediate canopy cover conditions in their vicinity. Nests remained clustered because of the heterogeneous habitat conditions, but spatial distribution has changed due to canopy alteration along time. The analysis on the NDVI was effective for 82% of cases (i.e., nests occurred within 30 m from favorable habitats). For all the remaining nests (18%), the Google Earth high resolution satellite image revealed in their vicinity the presence of small canopy gaps (undetected by the NDVI). These results show that historical satellite images are very useful for explaining the long-term dynamics of ant colonies. In addition, the use of modern remote sensing techniques provides a reliable and expedite method in determining the presence of favorable small-scale habitat, offering a very useful tool for ecological monitoring across large landscapes and in very different areas, especially in the context of ecosystem dynamics driven and exacerbated by climate change

Climate Warming and Past and Present Distribution of the Processionary Moths (Thaumetopoea spp.) in Europe, Asia Minor and North Africa

International audiencePine processionary moth, Thaumetopea pityocampa, is a model insect indicator of global warming, the northwards and upwards range expansion of this Mediterranean species being directly associated with the recent warming up. The knowledge about the drivers of moth expansion is synthesized. A first standardized mapping of the northern expansion edge, from Western Europe to Turkey, is presented, then detailed for 20 countries of Europe, Asia Minor and North Africa, including future trends. Additional data about the responses of the other Thaumetopoea species are given. Finally, the chapter points out the importance of the man-mediated introductions in the expansion process