Habitat evaluation of wild Amur tiger (Panthera tigris altaica) and conservation priority setting in north-eastern China

Luan, Xiaofeng; Qu, Yanyan; Li, Diqiang; Liu, Shirong; Wang, Xiulei; Wu, Bo; Zhu, Chi

doi:10.1016/j.jenvman.2010.08.001

Cited by 55 publications

(30 citation statements)

References 26 publications

(28 reference statements)

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“…Habitat suitability modeling (HSM) techniques have been central to refining species distribution maps [36], [37], identifying movement pathways [38], [39] and prioritizing areas for habitat restoration or species reintroduction [38], [40]. Maximum entropy, or Maxent, identifies habitat using only presence locations [41], [42], which is compatible with our GPS data associated with pronghorn movements.…”

Section: Methodsmentioning

confidence: 75%

“…Graphs, composed of habitat patches and habitat links (corridors) connecting the patches, may be used to illustrate the movement of populations and facilitate landscape connectivity analyses [52]. Currently there are two popular methods for implementing graph theory in corridor identification: least-cost modeling (LCM) [53], [40] and circuit theory [54]. In LCM, the path of least resistance between two points across a cost surface is identified [53].…”

Section: Methodsmentioning

confidence: 99%

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Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

2012

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Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.

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Section: Methodsmentioning

confidence: 75%

Section: Methodsmentioning

confidence: 99%

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

2012

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“…Broad‐leaved mixed forests appear in the Lesser Khingan Mountains, Changbai Mountains, and Wanda Mountains and are dominated by L . gmelinii , Pinus koraiensis , Quercus mongolica , Tilia amurensis , and Betula platyphylla (Deng et al., ; Xiaofeng et al., ; Yang & Xu, ). These complex ecological systems support many wildlife species, including the black‐billed capercaillie ( T. urogalloides ), black grouse ( Lyrurus tetrix ), and hazel grouse ( Bonasa bonasia ) (He et al., ; Yin et al., ; Zhang et al., ; Zhu & Liu, ).…”

Section: Methodsmentioning

confidence: 99%

Long‐term ecological data for conservation: Range change in the black‐billed capercaillie (Tetrao urogalloides) in northeast China (1970s–2070s)

Yang

Zhang

Chen

et al. 2018

Ecology and Evolution

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Long‐term ecological data can be an effective tool to help ecologists integrate future projections with historical contexts and provide unique insights into the long‐term dynamics of endangered species. However, hampered by data limitations, including incomplete and spatially biased data, relatively few studies have used multidecadal datasets or have examined changes in biogeography from a historical perspective. The black‐billed capercaillie (Tetrao urogalloides) is a large capercaillie (classified as Least Concern [LC] on the IUCN red list) that has undergone a dramatic decline in population during the late 20th century and is considered endangered. Its conservation status is pessimistic, and the species requires immediate protection. Therefore, we supplemented a historical dataset to identify changes in this bird's range and population in northeast China over the long term. The study area spanned Heilongjiang Province, Jilin Province, and the northeast corner of Inner Mongolia in northeast China. We integrated an ecological niche model (BIOMOD2) with long‐term ecological data on this species to estimate the magnitude of change in distribution over time. Our results revealed a 35.25% reduction in the current distribution of this species compared to their potential distribution in the 1970s. This decline is expected to continue under climate change. For example, the future range loss was estimated to be 38.79 ± 0.22% (8.64–90.19%), and the actual state could be worse, because the baseline range of the model was greater than the real range in the 2000s, showing a 12.39% overestimation. To overcome this poor outlook, a conservation strategy should be established in sensitive areas, including the southwestern Greater Khingan Mountains and northern Lesser Khingan Mountains. Actions that should be considered include field investigations, establishing a monitor network, designing ecological corridors, and cooperating with local inhabitants, governments, and conservation biologists to improve the conservation of the black‐billed capercaillie.

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“…The AHP is a method used for calculating the weights of parameter factors by qualitative and quantitative comparison of their relative im portance (Saaty 1977, Saaty & Vargas 1991. In many sustainable habitat management models, AHP is widely used to create a methodology framework and reduce uncertainty (Store & Kangas 2001, Luan et al 2011, Chen et al 2013). For example, using AHP, Shen et al (2008) identified the relative importance of habitat factors to determine the range of giant panda activity in the Minshan Mountains, China.…”

Section: Weights Of Parameter Factorsmentioning

confidence: 99%

Assessing the carrying capacity of Perinereis aibuhitensis in a Chinese estuarine wetland using a GIS-based habitat suitability index model

Liu¹,

Wang²,

Zhao³

et al. 2017

Aquacult. Environ. Interact.

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Habitat evaluation of wild Amur tiger (Panthera tigris altaica) and conservation priority setting in north-eastern China

Cited by 55 publications

References 26 publications

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

Long‐term ecological data for conservation: Range change in the black‐billed capercaillie (Tetrao urogalloides) in northeast China (1970s–2070s)

Assessing the carrying capacity of Perinereis aibuhitensis in a Chinese estuarine wetland using a GIS-based habitat suitability index model

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