Towards a unified framework for connectivity that disentangles movement and mortality in space and time

Bridging the gap between movement data and connectivity analysis using the Time-Explicit Habitat Selection (TEHS) model

BACKGROUND

Understanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes.

METHODS

We propose a new model, called the Time-Explicit Habitat Selection (TEHS) model, that can be directly used for connectivity analysis. The TEHS model decomposes the movement process in a principled approach into a time and a selection component, providing complementary information regarding space use by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil.

RESULTS

The time model revealed that the fastest movements tended to occur between 8 p.m. and 5 a.m., suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We also found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, using the spatial absorbing Markov chain framework, we show that the TEHS model results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch due to avoidance of certain habitats.

CONCLUSIONS

The proposed approach can be used to characterize how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. Additionally, this framework can help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit connectivity results.

Foray movements are common and vary with natal habitat for a highly mobile bird

Understanding dispersal is central to interpreting the effects of climate change, habitat loss and habitat fragmentation, and species invasions. Prior to dispersal, animals may gather information about the surrounding landscape via forays, or systematic, short-duration looping movements away from and back to the original location. Despite theory emphasizing that forays can be beneficial for dispersing organisms and that such behaviors are predicted to be common, relatively little is known about forays in wild populations. Theory predicts that individuals that use forays may delay dispersal and such behaviors should increase survival, yet empirical tests of these predictions remain scarce. We tested these predictions in a natural system using the critically endangered snail kite (Rostrhaumus sociabilis), a wetland-dependent raptor. We GPS tracked 104 snail kites from fledging through emigration from the natal site across their breeding range to understand the demographic consequences of movement. We found that forays were common (82.7% of individuals tracked), and natal habitat played an important role in the initiation, execution, and outcome of foray behavior. The effect of foraying on survival was indirect, where forayers emigrated later than non-forayers, and individuals that emigrated later had the highest survival. Poor hydrological conditions in the natal environment were especially important for eliciting forays. Finally, females responded more strongly to natal hydrology than males, making more forays and significantly longer, more distant trips. These results emphasize the fundamental role of natal habitat for determining behavioral patterns, strengthen links between individual movement decisions and their demographic consequences, and provide an important behavioral focal point for interpreting movement tracks that would not otherwise be captured by conventional movement models.

Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture-recapture models

BACKGROUND

Improved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning.

METHODS

We used mark-recapture data collected from 924 genetic detections of 598 American black bears (Ursus americanus) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces.

RESULTS

Model results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100 km2 (95% CI 12.52-20.6) for females and 9.27 bears/100 km2 (95% CI 7.70-11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear (Ursus arctos) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity.

CONCLUSIONS

Density-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.

Estimating survival in continuous space from mark-dead-recovery data - Towards a continuous version of the multinomial dead recovery model

Understanding spatially varying survival is crucial for understanding the ecology and evolution of migratory animals, which may ultimately help to conserve such species. We develop an approach to estimate an annual survival probability function varying continuously in geographic space, if the recovery probability is constant over space. This estimate is based on a density function over continuous geographic space and the discrete age at death obtained from dead recovery data. From the same density function, we obtain an estimate for animal distribution in space corrected for survival, i.e., migratory connectivity. This is possible, when migratory connectivity can be separated from recovery probability. In this article, we present the method how spatially and continuously varying survival and the migratory connectivity corrected for survival can be obtained, if a constant recovery probability can be assumed reasonably. The model is a stepping stone in developing a model allowing for disentangling spatially heterogeneous survival and migratory connectivity corrected for survival from a spatially heterogeneous recovery probability. We implement the method using kernel density estimates in the R-package CONSURE. Any other density estimation technique can be used as an alternative. In a simulation study, the estimators are unbiased but show edge effects in survival and migratory connectivity. Applying the method to a real-world data set of European robins Erithacus rubecula results in biologically reasonable continuous heat-maps for survival and migratory connectivity.

Estimating resistance surfaces using gradient forest and allelic frequencies

Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the gradient forest approach to produce a resistance surface. Used in community ecology, gradient forest is an extension of random forest, and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resistance Gradient Forest (resGF) performance was compared to other published methods (maximum likelihood population effects model, random forest-based least-cost transect analysis and species distribution model). In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the gradient forest approach performed similarly to the other random forest-based approach using least-cost transect analysis but outperformed MLPE-based methods. Additionally, two worked examples are provided using two previously published data sets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and inform long-term biodiversity conservation strategies.

First insights in terrestrial mammals monitoring in the Candelaria and Machay Reserves in the Ecuadorian Tropical Andes

Habitat disturbance leads to biodiversity decline and modifications in the landscape structure and composition, affecting both dispersal movements and ecological processes at different temporal and spatial scales. The Ecuadorian Tropical Andes harbour suitable habitats for the distribution of a wide variety of species; however, there is a lack of studies focused on mammal diversity and its association with the habitat attributes in the central-eastern slopes. Here, we reported the diversity of terrestrial mammals recorded between 2019 and 2021 in a camera-trap monitoring study in the Candelaria and Machay reserves in the upper basin of the Pastaza River, Ecuador. We performed site-occupancy probability analysis to assess the influence of spatial variables in the species' occurrence and also, based on natural marks, we reported preliminary findings in Andean bear individual identification. We detected 22 species of terrestrial mammals. Alpha diversity was similar between reserves with slightly higher species richness in Machay. Evenness indices showed unequal species distribution, with the Andean bear and domestic dogs exhibiting greater dominance. In addition, species composition was dissimilar between reserves, where the species turnover mostly explained the beta diversity. We observed that Andean bear and puma detections increased according to the natural vegetation cover. Conversely, domestic dogs were frequently detected in cells with an increasing proportion of pastures and crops. Additionally, we identified 26 Andean bears and six individuals recaptured during our study. Our results caution about the disturbance derived from human activities since we recorded unprecedented detections of domestic dogs in wild habitats. Nonetheless, it highlights the importance of private conservation areas (e.g. Candelaria, Machay and others) for supporting the occurrence and dispersal of terrestrial mammal species between larger areas in the upper basin of the Pastaza River.

Predicting areas important for ecological connectivity throughout Canada

Governments around the world have acknowledged that urgent action is needed to conserve and restore ecological connectivity to help reverse the decline of biodiversity. In this study we tested the hypothesis that functional connectivity for multiple species can be estimated across Canada using a single, upstream connectivity model. We developed a movement cost layer with cost values assigned using expert opinion to anthropogenic land cover features and natural features based on their known and assumed effects on the movement of terrestrial, non-volant fauna. We used Circuitscape to conduct an omnidirectional connectivity analysis for terrestrial landscapes, in which the potential contribution of all landscape elements to connectivity were considered and where source and destination nodes were independent of land tenure. Our resulting map of mean current density provided a seamless estimate of movement probability at a 300 m resolution across Canada. We tested predictions in our map using a variety of independently collected wildlife data. We found that GPS data for individual caribou, wolves, moose, and elk that traveled longer distances in western Canada were all significantly correlated with areas of high current densities. The frequency of moose roadkill in New Brunswick was also positively associated with current density, but our map was not able to predict areas of high road mortality for herpetofauna in southern Ontario. The results demonstrate that an upstream modelling approach can be used to characterize functional connectivity for multiple species across a large study area. Our national connectivity map can help governments in Canada prioritize land management decisions to conserve and restore connectivity at both national and regional scales.

Estimation in the multinomial reencounter model - Where do migrating animals go and how do they survive in their destination area?

Spatial variation in survival has individual fitness consequences and influences population dynamics. Which space animals use during the annual cycle determines how they are affected by this spatial variability. Therefore, knowing spatial patterns of survival and space use is crucial to understand demography of migrating animals. Extracting information on survival and space use from observation data, in particular dead recovery data, requires explicitly identifying the observation process. We build a fully stochastic model for animals marked in populations of origin, which were found dead in spatially discrete destination areas. The model acts on the population level and includes parameters for use of space, survival and recovery probability. It is based on the division coefficient and the multinomial reencounter model. We use a likelihood-based approach, derive Restricted Maximum Likelihood-like estimates for all parameters and prove their existence and uniqueness. In a simulation study we demonstrate the performance of the model by using Bayesian estimators derived by the Markov chain Monte Carlo method. We obtain unbiased estimates for survival and recovery probability if the sample size is large enough. Moreover, we apply the model to real-world data of European robins Erithacus rubecula ringed at a stopover site. We obtain annual survival estimates for different spatially discrete non-breeding areas. Additionally, we can reproduce already known patterns of use of space for this species.

A Validation Procedure for Ecological Corridor Locations

Connectivity conservation analysis is based on a wide range of approaches designed to pinpoint key ecological corridors in order to maintain multispecies flows. However, the lack of validation procedures with accessible data prevents one from evaluating the accuracy of ecological corridor locations. We propose a new validation procedure to evaluate the accuracy of ecological corridor locations in landscape connectivity approaches. The ability of the procedure to properly rank the accuracy of different landscape connectivity approaches was illustrated in a study case. Maxent model and circuit theory were used to locate ecological corridors for forest bird species, following three approaches based on land cover, umbrella species and multispecies presence data. The validation procedure was used to compare the three approaches. Our validation procedure ranked the three approaches as expected, considering that accuracy in locating ecological corridors is related to the biological realism of calibration data. The corridors modelled were more accurate with species presence data (umbrella and multispecies approaches) compared to land cover proxy (habitat-based approach). These results confirm the quality of the validation procedure. Our validation procedure can be used to: (1) evaluate the accuracy of the location of ecological corridors; (2) select the best approach to locate ecological corridors, and (3) validate the underlying assumptions of landscape connectivity approaches (e.g., dispersal and matrix resistance values).

Do all roads lead to resistance? State road density is the main impediment to gene flow in a flagship species inhabiting a severely fragmented anthropogenic landscape

AIM

Connectivity conservation is ideally based on empirical information on how landscape heterogeneity influences species-specific movement and gene flow. Here, we present the first large-scale evaluation of landscape impacts on genetic connectivity in the European wildcat (Felis silvestris), a flagship and umbrella species for connectivity conservation across Europe.

LOCATION

The study was carried out in the core area of the distributional range of wildcats in Germany, covering about 186,000 km2 of a densely populated and highly fragmented landscape.

METHODS

We used data of 975 wildcats genotyped at 14 microsatellites and an individual-based landscape genetic framework to assess the importance of twelve landscape variables for explaining observed genetic connectivity. For this, we optimized landscape resistance surfaces for all variables and compared their relative impacts using multiple regression on distance matrices and commonality analysis.

RESULTS

Genetic connectivity was best explained by a synergistic combination of six landscape variables and isolation by distance. Of these variables, road density had by far the strongest individual impact followed by synergistic effects of agricultural lands and settlements. Subsequent analyses involving different road types revealed that the strong effect of road density was largely due to state roads, while highways and federal roads had a much smaller, and county roads only a negligible impact.

MAIN CONCLUSIONS

Our results highlight that landscape-wide genetic connectivity in wildcats across Germany is strongly shaped by the density of roads and in particular state roads, with higher densities providing larger resistance to successful dispersal. These findings have important implications for conservation planning, as measures to mitigate fragmentation effects of roads (e.g., over- or underpasses) often focus on large, federally managed transportation infrastructures. While these major roads exert local barrier effects, other road types can be more influential on overall connectivity, as they are more abundant and more widespread across the landscape.

Land cover, individual's age and spatial sorting shape landscape resistance in the invasive frog Xenopus laevis

The description of functional connectivity is based on the quantification of landscape resistance, which represents species-specific movement costs across landscape features. Connectivity models use these costs to identify movement corridors at both individual and population levels and provide management recommendations for populations of conservation interest. Typically, resistance costs assigned to specific land cover types are assumed to be valid for all individuals of the population. Little attention has been paid to intraspecific variation in resistance costs due to age or dispersal syndrome, which may significantly affect model predictions. We quantified resistance costs in an expanding invasive population of the African clawed frog Xenopus laevis in Western France. In this principally aquatic amphibian, juveniles, sub-adults and adults disperse overland. The enhancement of dispersal traits via spatial sorting has been also observed at the range periphery of the population. Resistance costs, and thus connectivity, might vary as a function of life stage and position within the invaded range. We assessed multiple dimensions of functional connectivity. On various land cover types, we measured locomotion, as crossing speed, in different post-metamorphic age classes, and dehydration, sensitivity of locomotion to dehydration and substrate preference in juveniles. We also tested the effect of the position in the invaded range (core vs. periphery) on individual performances. In juveniles, general trends towards higher resistance costs on grass and lower resistance costs on bare soil and asphalt were observed, although not all experiments provided the same cost configurations. Resistance to locomotion varied between age classes, with adults and sub-adults facing lower costs than juveniles, particularly when crossing structurally complex land cover types such as grass and leaf litter. The position in the range had a minor effect on landscape resistance, and only in the dehydration experiment, where water loss in juveniles was lower at the range periphery. Depicting functional connectivity requires (a) assessing multiple dimensions of behavioural and physiological challenges faced by animals during movement; (b) considering factors, such as age and dispersal syndrome, that may affect movement at both individual and population levels. Ignoring this complexity might generate unreliable connectivity models and provide unsupported management recommendations for conservation.

Urban specialization reduces habitat connectivity by a highly mobile wading bird

BACKGROUND

Mobile animals transport nutrients and propagules across habitats, and are crucial for the functioning of food webs and for ecosystem services. Human activities such as urbanization can alter animal movement behavior, including site fidelity and resource use. Because many urban areas are adjacent to natural sites, mobile animals might connect natural and urban habitats. More generally, understanding animal movement patterns in urban areas can help predict how urban expansion will affect the roles of highly mobile animals in ecological processes.

METHODS

Here, we examined movements by a seasonally nomadic wading bird, the American white ibis (Eudocimus albus), in South Florida, USA. White ibis are colonial wading birds that forage on aquatic prey; in recent years, some ibis have shifted their behavior to forage in urban parks, where they are fed by people. We used a spatial network approach to investigate how individual movement patterns influence connectivity between urban and non-urban sites. We built a network of habitat connectivity using GPS tracking data from ibis during their non-breeding season and compared this network to simulated networks that assumed individuals moved indiscriminately with respect to habitat type.

RESULTS

We found that the observed network was less connected than the simulated networks, that urban-urban and natural-natural connections were strong, and that individuals using urban sites had the least-variable habitat use. Importantly, the few ibis that used both urban and natural habitats contributed the most to connectivity.

CONCLUSIONS

Habitat specialization in urban-acclimated wildlife could reduce the exchange of propagules and nutrients between urban and natural areas, which has consequences both for beneficial effects of connectivity such as gene flow and for detrimental effects such as the spread of contaminants or pathogens.

The allometry of movement predicts the connectivity of communities

Connectivity has long played a central role in ecological and evolutionary theory and is increasingly emphasized for conserving biodiversity. Nonetheless, connectivity assessments often focus on individual species even though understanding and preserving connectivity for entire communities is urgently needed. Here we derive and test a framework that harnesses the well-known allometric scaling of animal movement to predict community-level connectivity across protected area networks. We used a field translocation experiment involving 39 species of southern African birds to quantify movement capacity, scaled this relationship to realized dispersal distances determined from ring-and-recovery banding data, and used allometric scaling equations to quantify community-level connectivity based on multilayer network theory. The translocation experiment explained observed dispersal distances from ring-recovery data and emphasized allometric scaling of dispersal based on morphology. Our community-level networks predicted that larger-bodied species had a relatively high potential for connectivity, while small-bodied species had lower connectivity. These community networks explained substantial variation in observed bird diversity across protected areas. Our results highlight that harnessing allometric scaling can be an effective way of determining large-scale community connectivity. We argue that this trait-based framework founded on allometric scaling provides a means to predict connectivity for entire communities, which can foster empirical tests of community theory and contribute to biodiversity conservation strategies aimed at mitigating the effects of environmental change.