Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-23T18:43:23.807Z Has data issue: false hasContentIssue false
  • English
  • Français

Cryptic and cumulative impacts on the wintering habitat of the endangered black-faced spoonbill (Platalea minor) risk its long-term viability

Published online by Cambridge University Press:  27 June 2017

EVAN J. PICKETT ,
MELANIE CHAN ,
WENDA CHENG ,
JOHN ALLCOCK ,
SIMBA CHAN ,
JUNHUA HU ,
KISUP LEE ,
BENA SMITH ,
SHUANG XING  and
YAT-TUNG YU
...Show all authors
EVAN J. PICKETT
Affiliation:
School of Biological Sciences, The University of Hong Kong, Hong Kong, China
MELANIE CHAN
Affiliation:
School of Biological Sciences, The University of Hong Kong, Hong Kong, China
WENDA CHENG
Affiliation:
School of Biological Sciences, The University of Hong Kong, Hong Kong, China
JOHN ALLCOCK
Affiliation:
The Hong Kong Birdwatching Society, Lai Chi Kok, Kowloon, Hong Kong, China
SIMBA CHAN
Affiliation:
BirdLife International Asia Regional Office, Tokyo, Japan
JUNHUA HU
Affiliation:
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China
KISUP LEE
Affiliation:
Waterbird Network Korea, Seoul 03147, Korea
BENA SMITH
Affiliation:
Wildfowl & Wetlands Trust, Slimbridge, Gloucestershire GL2 7BT, UK
SHUANG XING
Affiliation:
School of Biological Sciences, The University of Hong Kong, Hong Kong, China
YAT-TUNG YU
Affiliation:
The Hong Kong Birdwatching Society, Lai Chi Kok, Kowloon, Hong Kong, China
TIMOTHY C. BONEBRAKE*
Affiliation:
School of Biological Sciences, The University of Hong Kong, Hong Kong, China
*
*Correspondence: Dr Timothy C. Bonebrake email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

The East Asian–Australasian flyway contains some of the most threatened habitats in the world, with at least 155 waterbird species reliant on the tidal habitats it comprises. The black-faced spoonbill (Platalea minor) is an iconic endangered species distributed across the coast of East Asia. Its population suffered a severe decline into the 1990s, but extensive monitoring and conservation interventions have aided a substantial recovery of the species. We used a population viability analysis based on data collected over the past two decades in conjunction with species distribution models to project spatially explicit models of population change for the next 35 years. Over nearly all scenarios of habitat loss and climate change, the global spoonbill population was projected to increase in the short-term due to low population numbers likely well below current population carrying capacities. However, climate change and habitat loss together threaten the recovery of the spoonbill population such that, by 2050, population declines are apparent as a consequence of these cumulative impacts. These threats are also cryptic and represent a challenge to the conservation of species recovering from anthropogenic impacts; observed population increases can hide large reductions in habitat suitability that threaten the long-term viability of species.

Keywords

climate changeendangered speciesglobal warmingmigrationtidal wetlandswaterbirds
Type
Non-Thematic Papers
Information
Environmental Conservation , Volume 45 , Issue 2: Thematic section. Humans and Island Environments , June 2018 , pp. 147 - 154
Copyright
Copyright © Foundation for Environmental Conservation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Supplementary material can be found online at http://dx.doi.org/10.1017/S0376892917000340

References

Akçakaya, HR, Root, W (2005) RAMAS GIS 5: Linking Spatial Data with Population Viability Analysis. Setauket, NY, USA: Applied Biomathematics.Google Scholar
Amano, T, Székely, T, Koyama, K, Amano, H, Sutherland, WJ (2010) A framework for monitoring the status of populations: an example from wader populations in the East Asian–Australasian flyway. Biological Conservation 143: 2238–2247.Google Scholar
An, SQ, Li, HB, Guan, BH, Zhou, C, Wang, Z, Deng, Z, Zhi, Y et al. (2007) China's natural wetlands: past problems, current status, and future challenges. AMBIO 36: 335–342.Google Scholar
Beissinger, SR, Westphal, MI (1998) On the use of demographic models of population viability in endangered species management. J Wildlife Management 62: 821–841.Google Scholar
Bonebrake, TC, Syphard, AD, Fraklin, J, Anderson, KE, Akçakaya, HR, Mizerek, T, Winchell, C, Regan, HM (2014) Fire management, managed relocation, and land conservation options for long-lived obligate seedling plants under global changes in climate, urbanization, and fire regime. Conservation Biology 28: 1057–1067.Google Scholar
Chan, S, Fang, WH, Lee, KS, Yamada, Y, Yu, YT (2010) International Single Species Action Plan for the Conservation of the Black-faced Spoonbill (Platalea minor). Tokyo, Japan: BirdLife International Asia Division.Google Scholar
Cho, DO, Olsen, SB (2003) The status and prospects for coastal management in Korea. Coastal Management 31: 99– 119.Google Scholar
Chong, JR, Pak, UI, Rim, CY, Kim, TS (1996) Breeding biology of black-faced spoonbill Platalea minor. Strix 14: 1–10.Google Scholar
Dufresne, JL, Foujols, MA, Denvil, S, Caubel, A, Marti, O, Aumont, O, Mignot, J (2013) Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Climate Dynamics 40: 2123–2165.Google Scholar
ESRI (2011) ArcGIS Desktop: Release 10. Redlands, CA, USA: Environmental Systems Research Institute.Google Scholar
Fraixedas, S, Lehikoinen, A, Lindén, A (2015) Impacts of climate and land‐use change on wintering bird populations in Finland. Journal of Avian Biology 46: 63–72.Google Scholar
Franklin, J, Regan, HM, Syphard, AD (2014) Linking spatially explicit species distribution and population models to plan for the persistence of plant species under global change. Environmental Conservation 41: 97–109.Google Scholar
Global Land Cover (2003) 2000 Database. European Commission, Joint Research Centre. URL http://forobs.jrc.ec.europa.eu/products/glc2000/glc2000.phpGoogle Scholar
Heard, MJ, Smith, KF, Ripp, KJ, Berger, M, Chen, J, Dittmeier, J, Goter, M et al. (2013) The threat of disease increases as species move toward extinction. Conservation Biology 27: 1378– 1388.Google Scholar
Hijmans, RJ, Cameron, SE, Parra, JL, Jones, PG, Jarvis, A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965–1978.Google Scholar
Hu, J, Hu, H, Jiang, Z (2010) The impacts of climate change on the wintering distribution of an endangered migratory bird. Oecologia 164: 555–565.Google Scholar
Hua, N, Tan, K, Chen, Y, Ma, Z (2015) Key research issues concerning the conservation of migratory shorebirds in the Yellow Sea region. Bird Conservation International 25: 38–52.Google Scholar
Hunter, EA, Nibbelink, NP, Alexander, CR, Barrett, K, Mengak, LF, Guy, RK, Moore, CT, Cooper, RJ (2015) Coastal vertebrate exposure to predicted habitat changes due to sea level rise. Environmental Management 56: 1528–1537.Google Scholar
Islam, MS, Tanaka, M (2004) Impacts of pollution on coastal and marine ecosystems including coastal and marine fisheries and approach for management: a review and synthesis. Marine Pollution Bulletin 48: 624–648.CrossRefGoogle Scholar
Iwamura, T, Fuller, RA, Possingham, HP (2014) Optimal management of a multispecies shorebird flyway under sea-level rise. Conservation Biology 28: 1710–1720.Google Scholar
Iwamura, T, Possingham, HP, Chadès, I, Minton, C, Murray, NJ, Rogers, DI, Treml, EA, Fuller, RA (2013) Migratory connectivity magnifies the consequences of habitat loss from sea-level rise for shorebird populations. Proceedings. Biological Sciences 280: 20130325.Google Scholar
Lehikoinen, A, Jaatinen, K, Vähätalo, AV, Clausen, P, Crowe, O, Deceuninck, B, Hearn, R et al. (2013) Rapid climate driven shifts in wintering distributions of three common waterbird species. Global Change Biology 19: 2071–2081.Google Scholar
MacKinnon, J, Verkuil, YI, Murray, N (2012) IUCN Situation Analysis on East and Southeast Asian Intertidal Habitats, with Particular Reference to the Yellow Sea (Including the Bohai Sea). Occasional Paper of the IUCN Species Survival Commission No. 47. Gland, Switzerland: IUCN.Google Scholar
Murray, NJ, Clemens, RS, Phinn, SR, Possingham, HP, Fuller, RA (2014) Tracking the rapid loss of tidal wetlands in the Yellow Sea. Frontiers in Ecology and Environment 12: 267–272.CrossRefGoogle Scholar
Murray, NJ, Ma, Z, Fuller, RA (2015) Tidal flats of the Yellow Sea: a review of ecosystem status and anthropogenic threats. Austral Ecology 40: 472–481.CrossRefGoogle Scholar
Newton, I (1998) Population Limitation in Birds. San Diego, CA, USA: Academic Press.Google Scholar
Pavón‐Jordán, D, Fox, AD, Clausen, P, Dagys, M, Beceuninck, B, Devos, K, Hearn, RD et al. (2015) Climate‐driven changes in winter abundance of a migratory waterbird in relation to EU protected areas. Diversity and Distributions 21: 571–582.CrossRefGoogle Scholar
Pearce-Higgins, JW, Yalden, DW, Whittingham, MJ (2005) Warmer springs advance the breeding phenology of golden plovers Pluvialis apricaria and their prey (Tipulidae). Oecologia 143: 470–476.Google Scholar
Phillips, SJ, Dudik, M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31: 161–175.Google Scholar
Rueda-Cediel, P, Anderson, KE, Regan, TJ, Franklin, J, Regan, HM (2015) Combined influences of model choice, data quality, and data quantity when estimating population trends. PLoS ONE 10: e0132255.Google Scholar
Stocker, TF, Qin, D, Plattner, GK, Tignor, M, Allen, SK, Boschung, J, Nauels, A et al. (2013) IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, and New York, NY, USA: Cambridge University Press.Google Scholar
Syphard, AD, Regan, HM, Franklin, J, Swab, RM, Bonebrake, TC (2013) Does functional type vulnerability to multiple threats depend on spatial context in Mediterranean‐climate regions? Diversity and Distributions 19: 1263–1274.CrossRefGoogle Scholar
Thorne, KM, Mattsson, BJ, Takekawa, J, Cummings, J, Crouse, D, Block, G, Bloom, V et al. (2015) Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change. Ecology and Society 20: 30.Google Scholar
Ueng, Y-T, Perng, J-J, Wang, J-P, Weng, J-H, Hou, P-CL (2006.) Diet of the black-faced spoonbill wintering at Chiku Wetland in Southwestern Taiwan. Waterbirds 29: 185–190.Google Scholar
Ueng, Y-T, Wang, J-P, Hou, P-CL (2007) Predicting population trends of the black-faced Spoonbill (Platalea minor). Wilson Journal of Ornithology 119: 246–252.Google Scholar
Ueta, M, Melville, DS, Wang, Y, Ozaki, K, Kanai, Y, Leader, PJ, Wang, C-C, Kuo, C-Y (2002) Discovery of the breeding sites and migration routes of black-faced spoonbills Platalea minor. IBIS 144: 340–343.CrossRefGoogle Scholar
USGS (2009) HYDRO1 K elevation derivative database. URL http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/gtopo30/hydro.Google Scholar
Virkkala, R (2016) Long-term decline of southern boreal forest birds: consequence of habitat alteration or climate change? Biodiversity Conservation 25: 151–167.Google Scholar
Yeung, CL, Yao, CT, Hsu, YC, Wang, JP, Li, SH (2006) Assessment of the historical population size of an endangered bird, the black-faced spoonbill (Platalea minor) by analysis of the mitochondrial DNA diversity. Animal Conservation 9: 1– 10.CrossRefGoogle Scholar
Yu, H (1994) China's coastal ocean uses: conflicts and impacts. Ocean Coastal Management 25: 161–178.CrossRefGoogle Scholar
Yu, YT, Fong, HHN, Tse, IWI (2015) International Black-faced Spoonbill Census 2015. Hong Kong, China: Black-faced Spoonbill Research Group, The Hong Kong Bird Watching Society.Google Scholar
Yukimoto, S, Adachi, Y, Hosaka, M, Sakami, T, Yoshimura, H, Hirabara, M, Tanaka, TY et al. (2012) A new global climate model of the Meteorological Research Institute: MRI-CGCM3 – model description and basic performance. Journal of the Meterological Society of Japan 90A: 26–64.Google Scholar
Supplementary material: File

Pickett supplementary material S1

Appendix

Download Pickett supplementary material S1(File)
File 183 KB
Supplementary material: File

Pickett supplementary material S2

Supplementary Figure

Download Pickett supplementary material S2(File)
File 392.2 KB
Supplementary material: File

Pickett supplementary material S3

Supplementary Table

Download Pickett supplementary material S3(File)
File 12.4 KB