Coupling inter-patch movement models and landscape graph to assess functional connectivity

Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila

Most real-world behaviors - such as odor-guided locomotion - are performed with incomplete information. Activity in olfactory receptor neuron (ORN) classes provides information about odor identity but not the location of its source. In this study, we investigate the sensorimotor transformation that relates ORN activation to locomotion changes in Drosophila by optogenetically activating different combinations of ORN classes and measuring the resulting changes in locomotion. Three features describe this sensorimotor transformation: First, locomotion depends on both the instantaneous firing frequency (f) and its change (df); the two together serve as a short-term memory that allows the fly to adapt its motor program to sensory context automatically. Second, the mapping between (f, df) and locomotor parameters such as speed or curvature is distinct for each pattern of activated ORNs. Finally, the sensorimotor mapping changes with time after odor exposure, allowing information integration over a longer timescale.

How Do Landscape Structure, Management and Habitat Quality Drive the Colonization of Habitat Patches by the Dryad Butterfly (Lepidoptera: Satyrinae) in Fragmented Grassland?

Most studies dealing with species distribution patterns on fragmented landscapes focus on the characteristics of habitat patches that influence local occurrence and abundance, but they tend to neglect the question of what drives colonization of previously unoccupied patches. In a study of the dryad butterfly, we combined classical approaches derived from metapopulation theory and landscape ecology to investigate the factors driving colonization from a recent refugium. In three consecutive transect surveys, we recorded the presence and numbers of imagos in 27 patches of xerothermic grassland and 26 patches of wet meadow. Among the predictors affecting the occurrence and abundance of the dryad, we considered environmental variables reflecting (i) habitat patch quality (e.g., goldenrod cover, shrub density, vegetation height); (ii) factors associated with habitat spatial structure (patch size, patch isolation and fragmentation); and (iii) features of patch surroundings (100-m buffers around patches) that potentially pose barriers or provide corridors. Patch colonization by the dryad was strongly limited by the distance from the species refugium in the region; there was a slight positive effect of shrub density in this respect. Butterfly abundance increased in smaller and more fragmented habitat patches; it was negatively impacted by invasive goldenrod cover, and positively influenced by the density of watercourses in patch surroundings. Nectar plant availability was positively related to species abundance in xerothermic grassland, while in wet meadow the effect was the reverse. We conclude that dryad colonization of our study area is very recent, since the most important factor limiting colonization was distance from the refugium, while the habitat quality of target patches had less relevance. In order to preserve the species, conservation managers should focus on enhancing the quality of large patches and should also direct their efforts on smaller and more fragmented ones, including those with relatively low resource availability, because such habitat fragments have an important role to play for specialist species.

Predicting local and non-local effects of resources on animal space use using a mechanistic step selection model

Predicting space use patterns of animals from their interactions with the environment is fundamental for understanding the effect of habitat changes on ecosystem functioning. Recent attempts to address this problem have sought to unify resource selection analysis, where animal space use is derived from available habitat quality, and mechanistic movement models, where detailed movement processes of an animal are used to predict its emergent utilization distribution. Such models bias the animal's movement towards patches that are easily available and resource-rich, and the result is a predicted probability density at a given position being a function of the habitat quality at that position. However, in reality, the probability that an animal will use a patch of the terrain tends to be a function of the resource quality in both that patch and the surrounding habitat.We propose a mechanistic model where this non-local effect of resources naturally emerges from the local movement processes, by taking into account the relative utility of both the habitat where the animal currently resides and that of where it is moving. We give statistical techniques to parametrize the model from location data and demonstrate application of these techniques to GPS location data of caribou (Rangifer tarandus) in Newfoundland.Steady-state animal probability distributions arising from the model have complex patterns that cannot be expressed simply as a function of the local quality of the habitat. In particular, large areas of good habitat are used more intensively than smaller patches of equal quality habitat, whereas isolated patches are used less frequently. Both of these are real aspects of animal space use missing from previous mechanistic resource selection models.Whilst we focus on habitats in this study, our modelling framework can be readily used with any environmental covariates and therefore represents a unification of mechanistic modelling and step selection approaches to understanding animal space use.