Evidence map›Paper›PMID 35381018›Full record

ArticlePloS one2022

Predicting wildlife corridors for multiple species in an East African ungulate community.

Jason Riggio, Katie Foreman, Ethan Freedman, Becky Gottlieb, David Hendler, Danielle Radomille, Ryan Rodriguez, Thomas Yamashita, John Kioko, Christian Kiffner

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Jason RiggioDepartment of Wildlife, Fish and Conservation Biology, Museum of Wildlife and Fish Biology, University of California, Davis, California, United States of America.ORCID 0000-0002-4988-3794
Katie ForemanDepartment of Environmental Studies, Franklin and Marshall College, Lancaster, Pennsylvania, United States of America.
Ethan FreedmanDepartment of Biology, Tufts University, Medford, Maryland, United States of America.
Becky GottliebThe School for Field Studies, Center for Wildlife Management Studies, Karatu, Tanzania.
David HendlerBard College, Annandale-on-Hudson, New York, United States of America.
Danielle RadomilleDepartment of Geography and the Environment, Villanova University, Villanova, Pennsylvania, United States of America.ORCID 0000-0003-0040-2782
Ryan RodriguezDepartment of Natural Resources, Cornell University, Ithaca, New York, United States of America.
Thomas YamashitaCaesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, Texas, United States of America.
John KiokoThe School for Field Studies, Center for Wildlife Management Studies, Karatu, Tanzania.
Christian KiffnerThe School for Field Studies, Center for Wildlife Management Studies, Karatu, Tanzania.ORCID 0000-0002-7475-9023

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wildlife corridors are typically designed for single species, yet holistic conservation approaches require corridors suitable for multiple species. Modelling habitat linkages for wildlife is based on several modelling steps (each involving multiple choices), and in the case of multi-species corridors, an approach to optimize single species corridors to few or a single functional corridor for multiple species. To model robust corridors for multiple species and simultaneously evaluate the impact of methodological choices, we develop a multi-method approach to delineate corridors that effectively capture movement of multiple wildlife species, while limiting the area required. Using wildlife presence data collected along ground-based line transects between Lake Manyara and Tarangire National Parks, Tanzania, we assessed species-habitat association in both ensemble and stacked species distribution frameworks and used these to estimate linearly and non-linearly scaled landscape resistances for seven ungulate species. We evaluated habitat suitability and least-cost and circuit theory-based connectivity models for each species individually and generated a multi-species corridor. Our results revealed that species-habitat relationships and subsequent corridors differed across species, but the pattern of predicted landscape connectivity across the study area was similar for all seven species regardless of method (circuit theory or least-cost) and scaling of the habitat suitability-based cost surface (linear or non-linear). Stacked species distribution models were highly correlated with the seven species for all model outputs (r = 0.79 to 0.97), while having the greatest overlap with the individual species least-cost corridors (linear model: 61.6%; non-linear model: 60.2%). Zebra was the best single-species proxy for landscape connectivity. Overall, we show that multi-species corridors based on stacked species distribution models achieve relatively low cumulative costs for savanna ungulates as compared to their respective single-species corridors. Given the challenges and costs involved in acquiring data and parameterizing corridor models for multiple species, zebra may act as a suitable proxy species for ungulate corridor conservation in this system.

Indexed as

Conservation of Natural ResourcesEcosystemAnimalsAnimals, Wild

Identifiers

PMID35381018
PMCPMC8982851

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.