Locating wildlife crossings for multispecies connectivity across linear infrastructures

Mimet, Anne; Clauzel, Céline; Foltête, Jean-Christophe

doi:10.1007/s10980-016-0373-y

Cited by 73 publications

(64 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…network metrics; Bastille‐Rousseau, Douglas‐Hamilton, Blake, Northrup, & Wittemyer, ; Wittemyer, Keating, Vollrath, & Douglas‐Hamilton, ) could provide more refined identification of crossing locations in prioritization schemes. Likewise, approaches assessing connectivity for multiple species may be preferable where community or multispecies conservation goals are paramount (Mimet, Clauzel, & Foltête, ). We focus on a single species in this study, given the lack of comparable data from other species.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing the positioning of wildlife crossing structures using GPS telemetry

Bastille‐Rousseau

Wall

Douglas‐Hamilton

et al. 2018

Journal of Applied Ecology

View full text Add to dashboard Cite

Development of transportation corridors has accelerated globally, with infrastructure projects being implemented across remote ecosystems, particularly in the tropics. Such developments can have negative impacts on wildlife and their ecosystems. The importance of wildlife crossing structures to mitigate adverse effects of such features is widely recognized, but the siting of and investment in crossing structures is contentious. Data on animal movement provide valuable, highly specific information for such processes, but can present analytical challenges and remain underutilized in planning mitigation efforts. We develop two algorithms based on Integer Linear Programming to prioritize crossing points based on frequency of use or breadth of coverage among tracked individuals. These scenarios represent metrics likely to guide the planning of crossing structures, where the former may relate to the objective of minimizing vehicle‐animal collisions and the latter on maintaining ecosystem connectivity. We exemplify the algorithms through application on a tracking dataset from over 150 African elephants living near the proposed Lamu Port‐South Sudan‐Ethiopia‐Transport corridor. We explore the influence of sampling bias on outcomes and discuss considerations to guide the application process. Given the generally open, unfenced nature of this ecosystem, recorded movements occurred throughout the system and a third of the corridor length in the ecosystem was intersected by recorded elephant movements. The selection of crossing structure locations and their impacts on elephants varied whether we used a subsample of elephant representative of local population density or total sample of monitored individuals. The two algorithms also selected for different crossing structure locations. Synthesis and applications. Our work shows some of the challenges of using Global Positioning System telemetry in deciding where to put crossing structures and demonstrates the need to identify the type of constraints in the system and desired crossing structure characteristics a priori. We recommend managers carefully evaluate the presence of potential biases in their data. High‐resolution data combined with objective prioritization methods allow reasoned planning actions, but are often lacking during critical infrastructure planning stages. Given the limited budget already allocated to mitigation measures in most proposed developments, the tools developed and applied here can facilitate effective spatial planning.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Likewise, approaches assessing connectivity for multiple species may be preferable where community or multispecies conservation goals are paramount (Mimet, Clauzel, & Foltête, 2016). We focus on a single species in this study, given the lack of comparable data from other species.…”

Section: Frairmentioning

confidence: 99%

Optimizing the positioning of wildlife crossing structures using GPS telemetry

Bastille‐Rousseau

Wall

Douglas‐Hamilton

et al. 2018

Journal of Applied Ecology

View full text Add to dashboard Cite

show abstract

“…Graph theory has seen extensive development and growing applications in ecology and conservation (Urban et al 2009, Beier et al 2011, Galpern et al 2011, Rayfield et al 2011, including habitat creation, restoration, and reserve design (Kininmonth et al 2011, Clauzel et al 2015, Mimet et al 2016. Only recently has a more formal methodological framework for using graph theory for land-use planning been proposed (Foltête et al 2014).…”

Section: Sobolmentioning

confidence: 99%

Using spatial demographic network models to optimize habitat management decisions

et al. 2017

View full text Add to dashboard Cite

Conservation and management activities are always constrained by finite resources. Therefore, decisions such as which sites to protect, whether existing habitat should be restored or whether new habitat should be created, and where on the landscape management efforts should be focused present difficult challenges. An overarching goal of many conservation or management plans is the long‐term persistence of populations, which is often dependent on functional connectivity and the maintenance of metapopulation dynamics. Graph theory and network approaches are frequently used tools for modeling functional connections between populations and between habitats. Less often, graph models are used to guide conservation or management decisions. We used spatial networks derived for an amphibian population to determine optimal locations to create new habitat, prioritize existing habitat for restoration, and determine the habitat most critical for maintaining connectivity within the existing metapopulation within Fort Leonard Wood, Missouri, USA, 2012–2014. Using data collected at 206 breeding ponds over 3 years, we constructed demographic networks representing the functional connectivity between ponds by dispersing ringed salamanders (Ambystoma annulatum). We incorporated uncertainty in key model parameters through Monte Carlo simulation, and used a graph‐theoretical parameterization of the metapopulation mean lifetime model to assess how changes in network structure affect persistence of the network. We conducted addition and removal experiments within our Monte Carlo simulations to rank and prioritize locations for pond creation, ponds for restoration, and ponds for preservation. Salamanders bred in 106 ponds in ≥1 year; 2.4% of ponds functioned predominantly as sources and 51% of occupied ponds functioned predominantly as sinks. The importance of a pond to the network was correlated with the number of emigrants dispersing from a pond, the number of ponds reached by these dispersers, and the frequency a pond functioned as a source. Creating new ponds at optimal locations increased the persistence of the network an average of 15.4% compared to randomly selected locations, whereas selective restoration of currently unoccupied ponds resulted in an average increase of 31.4% in network persistence, as compared to randomly selected unoccupied ponds. Through Monte Carlo simulation, we constructed biologically informed demographic connectivity networks for use as a spatial conservation or management planning tool. Although our approach was implemented with an amphibian and a breeding pond network, it is generalizable to any species occupying discrete habitat patches. © 2017 The Wildlife Society.

show abstract

“…Functional connectivity is the behavioral response to the landscape elements [7]. It can be analyzed by a species' movement behavior in the landscape by testing dispersal success, search time and cell immigration, and comparing movement frequencies and weighing distances between points [8,9]. Previous researches have addressed the definition and application of landscape connectivity especially structural connectivity [7,10].…”

Section: Introductionmentioning

confidence: 99%

Assessing Structural Connectivity of Urban Green Spaces in Metropolitan Hong Kong

et al. 2017

View full text Add to dashboard Cite

Connectivity is a vital element in landscape structure because of its importance in species-landscape interactions. Connectivity analysis of green spaces in urban landscapes, especially in high-density cities such as Hong Kong, differs from that of habitats in natural or rural landscapes. Using the human being as the target species, we formulated with GIS techniques a resistance weight, a structural connectivity index and an ecological barrier effect index to assess connectivity of green spaces. Two factors were included in the modeling, namely the resistance of different land uses related to human activities, and the distance between different urban green spaces. We analyzed the relationships between the connectivity index of green spaces and green cover, elevation, building density and population density. Our results indicate that low connectivity usually occurs in both old and new town centers with high building density and low green cover, and in areas occupied by land uses with a high resistance weight. However, urban density may not necessarily have a negative influence on the structural connectivity of green spaces. Green cover also may not necessarily have positive impact on connectivity if the green spaces have a poor spatial pattern. Adding more green stepping stones, large green spaces and green corridors to form greenways and shortening the distance between urban green spaces can offer a spatial-planning strategy to increase the green space connectivity in Hong Kong. The study provides insights to optimize connectivity of green spaces to improve the urban living environment in high-density metropolises.

show abstract

Locating wildlife crossings for multispecies connectivity across linear infrastructures

Cited by 73 publications

References 67 publications

Optimizing the positioning of wildlife crossing structures using GPS telemetry

Optimizing the positioning of wildlife crossing structures using GPS telemetry

Using spatial demographic network models to optimize habitat management decisions

Assessing Structural Connectivity of Urban Green Spaces in Metropolitan Hong Kong

Contact Info

Product

Resources

About