Fishing behaviours and fisher effect in decision‐making processes when facing depredation by marine predators - Anaïs Janc; Christophe Guinet; David Pinaud; Gaëtan Richard; Pascal Monestiez; Paul Tixier (Fisheries Management and Ecology, 2021)
Fishers aim to optimise cost–benefit ratios of their behaviour when exploiting resources. Avoidance of interactions with marine predators (i.e. their feeding on catches in fishing gear, known as depredation) has recently become an important component of their decisions. How fishers minimise these interactions whilst maximising fishing success is poorly understood. This issue is addressed in a sub‐Antarctic, long‐line fishery confronted with extensive depredation by sperm whales Physeter macrocephalu s and killer whales Orcinus orca by examining a 15‐year data set. Whereas a broad range of behaviours was identified from spatio‐temporal and operational descriptors, none combined high fishing success with low frequency of interactions. With experience, fishers favoured exploitation of productive patches with high frequencies of interactions over avoidance behaviours. Such decisions, although potentially optimal in the short term, are likely to intensify pressures on fish stocks and impact depredating whales. Therefore, the present study provides additional evidence to inform management decisions pertaining to the coexistence between fisheries and marine predators.

Combining multiple visual surveys to model the habitat of deep‐diving cetaceans at the basin scale - Auriane Virgili; Matthieu Authier; Oliver Boisseau; Ana Cañadas; Diane Claridge; Tim Cole; Peter Corkeron; Ghislain Dorémus; Léa David; Nathalie Di‐Méglio; Charlotte Dunn; Tim E. Dunn; et al. (Global Ecology and Biogeography, 2019)
Aim Deep‐diving cetaceans are oceanic species exposed to multiple anthropogenic pressures including high intensity underwater noise, and knowledge of their distribution is crucial to manage their conservation. Due to intrinsic low densities, wide distribution ranges and limited presence at the sea surface, these species are rarely sighted. Pooling data from multiple visual surveys sharing a common line‐transect methodology can increase sightings but requires accounting for heterogeneity in protocols and platforms. Location North Atlantic Ocean and Mediterranean Sea. Time period 1998 to 2015. Major taxa Ziphiidae; Physeteriidae; Kogiidae. Methods About 1,240,000 km of pooled effort provided 630 sightings of ziphiids, 836 of physeteriids and 106 of kogiids. For each taxon, we built a hierarchical model to estimate the effective strip width depending on observation conditions and survey types. We then modelled relative densities in a generalized additive modelling framework. Geographical predictions were limited to interpolations identified with a gap analysis of environmental space coverage. Results Deeper areas of the North Atlantic gyre were mostly environmental extrapolation in the predictions, thereby highlighting gaps in sampling across the different surveys. For the three species groups, the highest relative densities were predicted along continental slopes, particularly in the western North Atlantic Ocean where the Gulf Stream creates dynamic frontal zones and eddies. Main conclusions Pooling a large number of surveys provided the first basin‐wide models of distribution for deep‐diving cetaceans, including several data‐deficient taxa, across the North Atlantic Ocean and the Mediterranean Sea. These models can help the conservation of elusive and poorly known marine megafauna.

Extrapolating cetacean densities beyond surveyed regions: habitat‐based predictions in the circumtropical belt - Laura Mannocci; Pascal Monestiez; Jérôme Spitz; Vincent Ridoux (Journal of Biogeography, 2015)
Aim Our knowledge of cetacean distributions is impeded by large data‐gaps worldwide, particularly at tropical latitudes. This study aims to (1) find generic relationships between cetaceans and their habitats in a range of tropical waters, and (2) extrapolate cetacean densities in a circumtropical belt extending far beyond surveyed regions. Location Pelagic, circumtropical. Methods Aerial surveys were conducted over three regions in the tropical Atlantic (132,000 km 2 ), Indian (1.4 million km 2 ) and Pacific (1.4 million km 2 ) oceans. Three cetacean guilds were studied (Delphininae, Globicephalinae and sperm and beaked whales). For each guild, a generalized additive model was fitted using sightings recorded in all three regions and 14 candidate environmental predictors. Cetacean densities were tentatively extrapolated over a circumtropical belt, excluding waters where environmental characteristics departed from those encountered in the surveyed regions. Results Each cetacean guild exhibited a relationship with the primary production and depth of the minimum dissolved oxygen concentration. Delphininae also showed a relationship with the dominant phytoplankton group. The prediction envelopes were primarily constrained by water temperature. Circumtropical extrapolations of Delphininae and Globicephalinae were contrasted between ocean basins, with high densities predicted in the equatorial waters of the three ocean basins. The predicted densities of sperm and beaked whales were lower and more uniform across the circumtropical belt than for the other two guilds. Main conclusions Our modelling approach represents a good analytical solution to predicting cetacean population densities in poorly documented tropical waters. Future data collection should concentrate on areas where environmental characteristics were not encountered in our survey regions and where the predicted densities were the most uncertain. By highlighting cetacean hotspots far beyond waters under national jurisdiction, this study can provide guidance for the delimitation of Ecologically and Biologically Significant Marine Areas.

Spatial leave‐one‐out cross‐validation for variable selection in the presence of spatial autocorrelation - Kévin Le Rest; David Pinaud; Pascal Monestiez; Joël Chadoeuf; Vincent Bretagnolle (Global Ecology and Biogeography, 2014)
Aim Processes and variables measured in ecology are almost always spatially autocorrelated, potentially leading to the choice of overly complex models when performing variable selection. One way to solve this problem is to account for residual spatial autocorrelation ( RSA ) for each subset of variables considered and then use a classical model selection criterion such as the A kaike information criterion ( AIC ). However, this method can be laborious and it raises other concerns such as which spatial model to use or how to compare different spatial models. To improve the accuracy of variable selection in ecology, this study evaluates an alternative method based on a spatial cross‐validation procedure. Such a procedure is usually used for model evaluation but can also provide interesting outcomes for variable selection in the presence of spatial autocorrelation. Innovation We propose to use a special case of spatial cross‐validation, spatial leave‐one‐out ( SLOO ), giving a criterion equivalent to the AIC in the absence of spatial autocorrelation. SLOO only computes non‐spatial models and uses a threshold distance (equal to the range of RSA ) to keep each point left out spatially independent from the others. We first provide some simulations to evaluate how SLOO performs compared with AIC . We then assess the robustness of SLOO on a large‐scale dataset. R software codes are provided for generalized linear models. Main conclusions The AIC was relevant for variable selection in the presence of RSA if the independent variables considered were not spatially autocorrelated. It otherwise failed because highly spatially autocorrelated variables were more often selected than others. Conversely, SLOO had similar performances whether the variables were themselves spatially autocorrelated or not. It was particularly useful when the range of RSA was small, which is a common property of spatial tools. SLOO appears to be a promising solution for selecting relevant variables from most ecological spatial datasets.

Modelling dendritic ecological networks in space: an integrated network perspective - Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie‐Josée Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; et al. (Ecology Letters, 2013)
Dendritic ecological networks ( DEN s) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DEN s have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2‐D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DEN s. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DEN s. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2‐D space can be used to explore the influence of multi‐scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Prey capture attempts can be detected in Steller sea lions and other marine predators using accelerometers - Morgane Viviant; Andrew W. Trites; David A. S. Rosen; Pascal Monestiez; Christophe Guinet (Polar Biology, 2010)

The littoral fish community of the Lebanese rocky coast (eastern Mediterranean Sea) with emphasis on Red Sea immigrants - Mireille L. Harmelin-Vivien; Ghazi Bitar; Jean-Georges Harmelin; Pascal Monestiez (Biological Invasions, 2005)

Spatial interpolation of air temperature using environmental context: Application to a crop model - Pascal Monestiez; Dominique Courault; Denis Allard; Françoise Ruget (Environmental and Ecological Statistics, 2001)

Spatial interpolation of air temperature according to atmospheric circulation patterns in southeast France - Dominique Courault; Pascal Monestiez (International Journal of Climatology, 1999)