Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia

Gantulga Bayandonoi; Koustubh Sharma; Justine Shanti Alexander; Purevjav Lkhagvajav; Ian Durbach; Chimeddorj Buyanaa; Bariushaa Munkhtsog; Munkhtogtokh Ochirjav; Sergelen Erdenebaatar; Bilguun Batkhuyag; Nyamzav Battulga; Choidogjamts Byambasuren; Bayarsaikhan Uudus; Shar Setev; Lkhagvasuren Davaa; Khurel-Erdene Agchbayar; Naranbaatar Galsandorj; Darryl MacKenzie

doi:10.1111/ddi.13412

Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia

Gantulga Bayandonoi, Koustubh Sharma, Justine Shanti Alexander, Purevjav Lkhagvajav, Ian Durbach, Chimeddorj Buyanaa, Bariushaa Munkhtsog, Munkhtogtokh Ochirjav, Sergelen Erdenebaatar, Bilguun Batkhuyag, Nyamzav Battulga, Choidogjamts Byambasuren, Bayarsaikhan Uudus, Shar Setev, Lkhagvasuren Davaa, Khurel-Erdene Agchbayar, Naranbaatar Galsandorj, Darryl MacKenzie

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

20 Downloads (Pure)

Abstract

Aim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km² in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection.

Location We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km² of Mongolia's potential snow leopard range.

Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country.

Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses.

Main conclusions This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that 0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.

Original language	English
Number of pages	13
Journal	Diversity and Distributions
Volume	Early View
Early online date	23 Sept 2021
DOIs	https://doi.org/10.1111/ddi.13412
Publication status	E-pub ahead of print - 23 Sept 2021

Keywords

Imperfect detection
Large carnivores
Mongolia
Occupancy
Predictive modelling
Sign surveys
Snow leopard
Species distribution

Access to Document

10.1111/ddi.13412Licence: CC BY

Bayandonoi_2021_DD_Mapping-the-ghost_CC
Copyright © 2021 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Final published version, 1.39 MBLicence: CC BY

Data for "Mapping the ghost: Estimating probabilistic snow leopard distribution across Mongolia"
Ochirjav, M. (Contributor), Borchers, D. (Contributor), Uudus, B. (Contributor), Munkhtsog, B. (Contributor), Bayandonoi, G. (Contributor), Erdenebaatar, S. (Contributor), Battulga, N. (Contributor), MacKenzie, D. (Contributor), Sharma, K. (Contributor), Davaa, L. (Contributor), Lkhagvajav, P. (Contributor), Galsandorj, N. (Contributor), Durbach, I. (Contributor), Byambasuren, C. (Contributor), Alexander, J. S. (Contributor), Setev, S. (Contributor), Buyanaa, C. (Contributor), Agchbayar, K.-E. (Contributor) & Batkhuyag, B. (Contributor), Zenodo, 25 Aug 2021
DOI: 10.5281/zenodo.5257572
Dataset

Cite this

Bayandonoi, G., Sharma, K., Shanti Alexander, J., Lkhagvajav, P., Durbach, I., Buyanaa, C., Munkhtsog, B., Ochirjav, M., Erdenebaatar, S., Batkhuyag, B., Battulga, N., Byambasuren, C., Uudus, B., Setev, S., Davaa, L., Agchbayar, K.-E., Galsandorj, N., & MacKenzie, D. (2021). Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia. Diversity and Distributions, Early View. Advance online publication. https://doi.org/10.1111/ddi.13412

@article{5335a81536cc4054a0325a0cdc0b2208,

title = "Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia",

abstract = "Aim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection. Location We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km2 of Mongolia's potential snow leopard range. Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country. Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses. Main conclusions This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that 0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.",

keywords = "Imperfect detection, Large carnivores, Mongolia, Occupancy, Predictive modelling, Sign surveys, Snow leopard, Species distribution",

author = "Gantulga Bayandonoi and Koustubh Sharma and {Shanti Alexander}, Justine and Purevjav Lkhagvajav and Ian Durbach and Chimeddorj Buyanaa and Bariushaa Munkhtsog and Munkhtogtokh Ochirjav and Sergelen Erdenebaatar and Bilguun Batkhuyag and Nyamzav Battulga and Choidogjamts Byambasuren and Bayarsaikhan Uudus and Shar Setev and Lkhagvasuren Davaa and Khurel-Erdene Agchbayar and Naranbaatar Galsandorj and Darryl MacKenzie",

note = "We are grateful to Global Environment Facility, United Nations Development Program and Snow Leopard Trust for supporting the Global Snow Leopard and Ecosystem Protection Program and development of tools and methods for Population Assessment of the World's Snow leopards (PAWS).",

year = "2021",

month = sep,

day = "23",

doi = "10.1111/ddi.13412",

language = "English",

volume = "Early View",

journal = "Diversity and Distributions",

issn = "1366-9516",

publisher = "Wiley-Blackwell",

}

Bayandonoi, G, Sharma, K, Shanti Alexander, J, Lkhagvajav, P, Durbach, I, Buyanaa, C, Munkhtsog, B, Ochirjav, M, Erdenebaatar, S, Batkhuyag, B, Battulga, N, Byambasuren, C, Uudus, B, Setev, S, Davaa, L, Agchbayar, K-E, Galsandorj, N & MacKenzie, D 2021, 'Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia', Diversity and Distributions, vol. Early View. https://doi.org/10.1111/ddi.13412

TY - JOUR

T1 - Mapping the ghost

T2 - estimating probabilistic snow leopard distribution across Mongolia

AU - Bayandonoi, Gantulga

AU - Sharma, Koustubh

AU - Shanti Alexander, Justine

AU - Lkhagvajav, Purevjav

AU - Durbach, Ian

AU - Buyanaa, Chimeddorj

AU - Munkhtsog, Bariushaa

AU - Ochirjav, Munkhtogtokh

AU - Erdenebaatar, Sergelen

AU - Batkhuyag, Bilguun

AU - Battulga, Nyamzav

AU - Byambasuren, Choidogjamts

AU - Uudus, Bayarsaikhan

AU - Setev, Shar

AU - Davaa, Lkhagvasuren

AU - Agchbayar, Khurel-Erdene

AU - Galsandorj, Naranbaatar

AU - MacKenzie, Darryl

N1 - We are grateful to Global Environment Facility, United Nations Development Program and Snow Leopard Trust for supporting the Global Snow Leopard and Ecosystem Protection Program and development of tools and methods for Population Assessment of the World's Snow leopards (PAWS).

PY - 2021/9/23

Y1 - 2021/9/23

N2 - Aim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection. Location We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km2 of Mongolia's potential snow leopard range. Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country. Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses. Main conclusions This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that 0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.

AB - Aim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection. Location We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km2 of Mongolia's potential snow leopard range. Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country. Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses. Main conclusions This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that 0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.

KW - Imperfect detection

KW - Large carnivores

KW - Mongolia

KW - Occupancy

KW - Predictive modelling

KW - Sign surveys

KW - Snow leopard

KW - Species distribution

U2 - 10.1111/ddi.13412

DO - 10.1111/ddi.13412

M3 - Article

SN - 1366-9516

VL - Early View

JO - Diversity and Distributions

JF - Diversity and Distributions

ER -

Mapping the ghost: estimating probabilistic snow leopard distribution across Mongolia

Abstract

Keywords

Access to Document

Fingerprint

Datasets

Data for "Mapping the ghost: Estimating probabilistic snow leopard distribution across Mongolia"

Cite this