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1. Understanding the Importance of Dynamic Landscape Connectivity

   https://doi.org/10.3390/land9090303  

   Zeller, K.A.; Lewison, R.; Fletcher, R.J.; Tulbure, M.G.; Jennings, M.K. (August 2020, Land)

   null (Ed.)

   Landscape connectivity is increasingly promoted as a conservation tool to combat the negative effects of habitat loss, fragmentation, and climate change. Given its importance as a key conservation strategy, connectivity science is a rapidly growing discipline. However, most landscape connectivity models consider connectivity for only a single snapshot in time, despite the widespread recognition that landscapes and ecological processes are dynamic. In this paper, we discuss the emergence of dynamic connectivity and the importance of including dynamism in connectivity models and assessments. We outline dynamic processes for both structural and functional connectivity at multiple spatiotemporal scales and provide examples of modeling approaches at each of these scales. We highlight the unique challenges that accompany the adoption of dynamic connectivity for conservation management and planning in the context of traditional conservation prioritization approaches. With the increased availability of time series and species movement data, computational capacity, and an expanding number of empirical examples in the literature, incorporating dynamic processes into connectivity models is more feasible than ever. Here, we articulate how dynamism is an intrinsic component of connectivity and integral to the future of connectivity science. 

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2. danceON and softWEAR: Education-level creative coding and programmable wearables

   https://doi.org/10.1145/3537972.3538015  

   Bergner, Yoav; Payne, William; McDermott, Kathleen; Desportes, Kayla (June 2022, International Conference on Movement and Computing)

   Our research collaborative has been exploring movement computing educational technology experiences. That is, we have been building tools that simultaneously support both movement and computing learning objectives at entry-level. We will demo two products in development. danceON is a domain-specific language and a web app that allows users to create interactive graphics overlaid on video from pre-recorded or live (webcam) sources. soft- WEAR is a solderless and breadboardless ecosystem using sensors, LEDs, and the Adafruit Trinket M0. It is designed to support a workflow from ideation, prototyping, and iteration to a durable, wearable final project embedded into clothing or accessories. 

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3. Validating network connectivity with observed movement in experimental landscapes undergoing habitat destruction

   https://doi.org/10.1111/1365-2664.13624  

   Poli, Caroline; Hightower, Jessica; Fletcher, Jr., Robert J.; Kaplan, ed., Ian (April 2020, Journal of Applied Ecology)

   Abstract Maintaining the ability of organisms to move between suitable patches of habitat despite ongoing habitat loss is essential to conserving biodiversity. Quantifying connectivity has therefore become a central focus of conservation planning. A large number of metrics have been developed to estimate potential connectivity based on habitat configuration, matrix structure and information on organismal movement, and it is often assumed that metrics explain actual connectivity. Yet, validation of metrics is rare, particularly across entire landscapes undergoing habitat loss—a crucial problem that connectivity conservation aims to mitigate.We leveraged a landscape‐scale habitat loss and fragmentation experiment to assess the performance of commonly used patch‐ and landscape‐scale connectivity metrics against observed movement data, test whether incorporating information about the matrix improves connectivity metrics and examine the performance of metrics across a gradient of habitat loss. We tested whether 38 connectivity metrics predict movement at the patch (i.e. patch immigration rates) and landscape (i.e., total movements) scale for a pest insect, the cactus bugChelinidea vittiger, across 15 replicate landscapes.Metrics varied widely in their ability to explain actual connectivity. At the patch scale, dPCflux, which describes the contribution of a patch to movement across the landscape independent of patch size, best explained immigration rates. At the landscape scale, total movements were best explained by a mesoscale metric that captures that distance between clusters of patches (i.e. modules). Incorporating the matrix did not necessarily improve the ability of metrics to predict actual connectivity. Across the habitat loss gradient, dPCfluxwas sensitive to habitat amount.Synthesis and applications. Our study provides a much‐needed evaluation of network connectivity metrics at the patch and landscape scales, emphasizing that accurate quantification of connectivity requires the incorporation, not only of habitat amount but also habitat configuration and information on dispersal capability of species. We suggest that variation in habitat may often be more critical for interpreting network connectivity than the matrix, and advise that connectivity metrics may be sensitive to habitat loss and should therefore be applied with caution to highly fragmented landscapes. Finally, we recommend that applications integrate mesoscale configuration of habitat into connectivity strategies. 

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4. Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species

   https://doi.org/10.1111/cobi.14114  

   Barbour, Nicole; Shillinger, George_L; Gurarie, Eliezer; Hoover, Aimee_L; Gaspar, Philippe; Temple‐Boyer, Julien; Candela, Tony; Fagan, William_F; Bailey, Helen (July 2023, Conservation Biology)

   Abstract Conservation of migratory species exhibiting wide‐ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial–temporal products. For the deep‐diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal–vertical movement model results with spatial–temporal kernel density estimates and threat data (gear‐specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004–2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space‐use estimates to create maps of relative risk of turtle–fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high‐risk interactions with turtles in a residential, deep‐diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) (https://www.upwell.org/sptw), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high‐risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial–temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors. 

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5. Mapping the connectivity–conflict interface to inform conservation

   https://doi.org/10.1073/pnas.2211482119  

   Vasudev, Divya; Fletcher, Robert J.; Srinivas, Nishanth; Marx, Andrew J.; Goswami, Varun R. (January 2023, Proceedings of the National Academy of Sciences)

   Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephantElephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes. 

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