Advertisement

Chinese Geographical Science

, Volume 29, Issue 6, pp 962–973 | Cite as

Using MaxEnt Model to Guide Marsh Conservation in the Nenjiang River Basin, Northeast China

  • Zhiliang Wang
  • Bai ZhangEmail author
  • Xuezhen Zhang
  • Hongxu Tian
Article
  • 4 Downloads

Abstract

Incorporating private and working lands into protected area networks could mitigate the isolation state of protected areas (PAs) and improve the efficiency of conservation. But how to select patches of land for conservation is still a troublesome issue. In this study, the MaxEnt model and irreplaceability index were applied to guide marsh conservation in the Nenjiang River Basin, Northeast China. According to the high accuracy of the MaxEnt model predictions (i.e., the average AUC value = 0.933), the Wuyuer River and Zhalong marshes in the downstream reaches of Wuyuer River are the optimal habitat for the Red-crowned crane and migratory waterfowls. There are 22 marsh patches selected by the patch irreplaceability index for conservation, of which 12 patches had been included in the current network of protected areas. The other 10 patches of marsh (amounting to 1096 km2) far from human disturbances with high NDVI (up to 0.8) and close distance to water (less than 100 m), which are excluded from the existing network of PAs, should be implemented conservation easement programs to improve the protection efficiency of conservation. Specifically, the marshes at Taha, Tangchi, and Lamadian should be given priority for conservation and restoration to reintroduce migratory waterfowls, as this would lessen the current isolation state of the Zhalong National Nature Reserve.

Keywords

MaxEnt model irreplaceability index marsh conservation Red-crowned crane (Grus japonensisNenjiang River Basin 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

This paper was supported by the RS and GIS Research Center of the Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, who kindly provided us with some data and experimental instruments.

References

  1. Anderson M G, Padding P I, 2015. The North American approach to waterfowl management: synergy of hunting and habitat conservation. International Journal of Environmental Studies, 72(5): 810–829. doi:  https://doi.org/10.1080/00207233.2015.1019296 CrossRefGoogle Scholar
  2. Bastian C T, Keske C M H, Mcleod D M et al., 2017. Landowner and land trust agent preferences for conservation easements: implications for sustainable land uses and landscapes. Landscape and Urban Planning, 157: 1–13. doi:  https://doi.org/10.1016/j.landurbplan.2016.05.030 CrossRefGoogle Scholar
  3. Beatty W S, Kesler D C, Webb E B et al., 2014. The role of protected area wetlands in waterfowl habitat conservation: implications for protected area network design. Biological Conservation, 176: 144–152. doi:  https://doi.org/10.1016/j.biocon.2014.05.018 CrossRefGoogle Scholar
  4. Brugière D, Scholte P, 2013. Biodiversity gap analysis of the protected area system in poorly documented Chad. Journal for Nature Conservation, 21(5): 286–293. doi:  https://doi.org/10.1016/j.jnc.2013.02.004 CrossRefGoogle Scholar
  5. Buschke F T, Vanschoenwinkel B, 2014. Mechanisms for the inclusion of cumulative impacts in conservation decision-making are sensitive to vulnerability and irreplaceability in a stochastically simulated landscape. Journal for Nature Conservation, 22(3): 265–271. doi:  https://doi.org/10.1016/j.jnc.2014.02.002 CrossRefGoogle Scholar
  6. Calado H, Bragagnolo C, Silva S et al., 2016. Adapting environmental function analysis for management of protected areas in small islands-case of Pico Island (the Azores). Journal of Environmental Management, 171: 231–242. doi:  https://doi.org/10.1016/j.jenvman.2016.02.015 CrossRefGoogle Scholar
  7. Caro T M, O’Doherty G, 1999. On the use of surrogate species in conservation biology. Conservation Biology, 13(4): 805–814. doi:  https://doi.org/10.1046/j.1523-1739.1999.98338.x CrossRefGoogle Scholar
  8. Carwardine J, Rochester W A, Richardson K S et al., 2007. Conservation planning with irreplaceability: does the method matter? Biodiversity and Conservation, 16(1): 245–258. doi:  https://doi.org/10.1007/s10531-006-9055-4 CrossRefGoogle Scholar
  9. Dissanayake S T M, Onal H, Westervelt J D, 2011. Optimum selection of conservation reserves: extensions to multiple land use. Military Operations Research, 16(1): 65–76. doi:  https://doi.org/10.5711/1082598316165 CrossRefGoogle Scholar
  10. Elith J, Graham C H, Anderson R P et al., 2006. Novel methods improve prediction of species’ distributions from occurrence data. Eco-graphy, 29(2): 129–151. doi:  https://doi.org/10.1111/j.2006.0906-590.04596.x Google Scholar
  11. Evans-Peters G R, Dugger B D, Petrie M J, 2012. Plant community composition and waterfowl food production on Wetland Reserve Program easements compared to those on managed public lands in western Oregon and Washington. Wetlands, 32: 391–399. doi:  https://doi.org/10.1007/s13157-012-0275-y CrossRefGoogle Scholar
  12. Feng Kemin, Li Jinlu, 1985. Aerial surveys of the Red-crowned cranes and other waterfowls in China. Journal of Northeastern Forestry College, 13(1): 80–87. (in Chinese).Google Scholar
  13. Fleishman E, Yen J D, Thomson J R et al., 2018. Identifying spatially and temporally transferrable surrogate measures of species richness. Ecological Indicators, 84: 470–478. doi:  https://doi.org/10.1016/j.ecolind.2017.09.020 CrossRefGoogle Scholar
  14. Fonseca C R, Venticinque E M, 2018. Biodiversity conservation gaps in Brazil: a role for systematic conservation planning. Perspectives in Ecology and Conservation, 16(2): 61–67. doi:  https://doi.org/10.1016/j.pecon.2018.03.001 CrossRefGoogle Scholar
  15. Gardner C J, Raxworthy C J, Metcalfe K et al., 2015. Comparing methods for prioritising protected areas for investment: a case study using Madagascar’s dry forest reptiles. Plos One, 10(7): e0132803. doi:  https://doi.org/10.1371/journal.pone.0132803 CrossRefGoogle Scholar
  16. Gjerde I, Grytnes J A, Heegaard E et al., 2018. Red List updates and the robustness of sites selected for conservation of red-listed species. Global Ecology and Conservation, 16: e00454. doi:  https://doi.org/10.1016/j.gecco.2018.e00454 CrossRefGoogle Scholar
  17. He Chunguang, Sheng Lianxi, Lang Huiqing et al., 2004. Migration dynamics of Grus japonensis in recent years spring and conservation of its habitat in Xianghai Nature Reserve. Chinese Journal of Applied Ecology, 15(9): 1523–1526. (in Chinese).Google Scholar
  18. Hunter E A, Raney P A, Gibbs J P et al., 2012. Improving wetland mitigation site identification through community distribution modeling and a patch-based ranking scheme. Wetlands, 32(5): 841–850. doi:  https://doi.org/10.1007/s13157-012-0315-7 CrossRefGoogle Scholar
  19. Jaynes E T, 1957. Information theory and statistical mechanics. Physical Review, 106(4): 620–630. doi:  https://doi.org/10.1103/physrev.106.620 CrossRefGoogle Scholar
  20. Jiang Hongxing, Piao Renzhu, 2015. Census of Breeding Waterfowls in Songnen Plain of Northeast China by Ground and Aerial Surveys (2004–2008). Beijing: Science Press. (in Chinese)Google Scholar
  21. Johnson D H, 1980. The comparison of usage and availability measurements for evaluating resource preference. Ecology, 61(1): 65–71. doi:  https://doi.org/10.2307/1937156 CrossRefGoogle Scholar
  22. Jones J, 2001. Habitat selection studies in avian ecology: a critical review. Auk, 118(2): 557–562. doi:  https://doi.org/10.1642/0004-8038(2001)118[0557:HSSIAE]2.0.CO;2 CrossRefGoogle Scholar
  23. Jones K R, Plumptre A J, Watson J E M et al., 2016. Testing the effectiveness of surrogate species for conservation planning in the greater virunga landscape, Africa. Landscape and Urban Planning 145: 1–11. doi:  https://doi.org/10.1016/j.landurbplan.2015.09.006 CrossRefGoogle Scholar
  24. Kukkala A S, Moilanen A, 2013. Core concepts of spatial prioritisation in systematic conservation planning. Biological Reviews, 88(2): 443–464. doi:  https://doi.org/10.1111/brv.12008 CrossRefGoogle Scholar
  25. Li Y Z, Fluharty D L, 2017. Marine protected area networks in China: challenges and prospects. Marine Policy, 85: 8–16. doi:  https://doi.org/10.1016/j.marpol.2017.08.001 CrossRefGoogle Scholar
  26. Lu H F, Campbell D, Chen J et al., 2007. Conservation and economic viability of nature reserves: an emergy evaluation of the Yancheng Biosphere Reserve. Biological Conservation, 139(3–4): 415–438. doi:  https://doi.org/10.1016/j.biocon.2007.07.014 CrossRefGoogle Scholar
  27. Ma Yiqing, Jin Longrong, Jin Ailian et al., 1987. An aerial survey on Red-crowned cranes and other rare waders in the Wuyuer River Basin of Heilongjiang Province. Acta Zoologica Sinica, 33(2): 187–191. (in Chinese)Google Scholar
  28. Mao D H, Wang Z M, Wu J G et al., 2018. China’s wetlands loss to urban expansion. Land Degradation & Development, 29(8): 2644–2657. doi:  https://doi.org/10.1002/ldr.2939 CrossRefGoogle Scholar
  29. Margules C R, Pressey R L, 2000. Systematic conservation planning. Nature, 405(6783): 243–253. doi:  https://doi.org/10.1038/35012251 CrossRefGoogle Scholar
  30. McGarigal K, Wan H Y, Zeller K A et al., 2016. Multi-scale habitat selection modeling: a review and outlook. Landscape Ecology, 31(6): 1161–1175. doi:  https://doi.org/10.1007/s10980-016-0374-x CrossRefGoogle Scholar
  31. Memtsas D P, 2003. Multiobjective programming methods in the reserve selection problem. European Journal of Operational Research, 150(3): 640–652. doi:  https://doi.org/10.1016/S0377-2217(02)00519-2 CrossRefGoogle Scholar
  32. Moore C T, Lonsdorf E V, Knutson M G et al., 2011. Adaptive management in the U.S. National Wildlife Refuge System: science- management partnerships for conservation delivery. Journal of Environmental Management, 92(5): 1395–1402. doi:  https://doi.org/10.1016/j.jenvman.2010.10.065 CrossRefGoogle Scholar
  33. Na X D, Zhou H T, Zang S Y et al., 2018. Maximum entropy modeling for habitat suitability assessment of Red-crowned crane. Ecological Indicators, 91: 439–446. doi:  https://doi.org/10.1016/j.ecolind.2018.04.013 CrossRefGoogle Scholar
  34. Nazeri M, Jusoff K, Madani N et al., 2012. Predictive modeling and mapping of Malayan sun bear (Helarctos malayanus) distribution using maximum entropy. PLoS One, 7(10): e48104. doi:  https://doi.org/10.1371/journal.pone.0048104 CrossRefGoogle Scholar
  35. Newmark W D, 2008. Isolation of African protected areas. Frontiers in Ecology and the Environment, 6(6): 321–328. doi:  https://doi.org/10.1890/070003 CrossRefGoogle Scholar
  36. Parker D P, Thurman W N, 2013. Conservation easements: tools for conserving and enhancing ecosystem services. Encyclopedia of Energy, Natural Resource, and Environmental Economics, 2: 133–143. doi:  https://doi.org/10.1016/B978-0-12-375067-9.00053-X CrossRefGoogle Scholar
  37. Phillips S J, Anderson R P, Schapire R E, 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3–4): 231–259. doi:  https://doi.org/10.1016/j.ecolmodel.2005.03.026 CrossRefGoogle Scholar
  38. Phillips S J, Dudík M, 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2): 161–175. doi:  https://doi.org/10.1111/j.0906-7590.2008.5203.x CrossRefGoogle Scholar
  39. Phillips S J, Dudik M, Schapire R E, 2012. A Brief Tutorial on Maxent. AT&T Labs-Research, Princeton University, the Center for Biodiversity and Conservation, American Museum of Natural History.Google Scholar
  40. Pressey R L, Cowling R M, Rouget M, 2003. Formulating conservation targets for biodiversity pattern and process in the Cape Floristic Region, South Africa. Biological Conservation, 112(1–2): 99–127. doi:  https://doi.org/10.1016/s0006-3207(02)00424-x CrossRefGoogle Scholar
  41. Pulliam H R, 2000. On the relationship between niche and distribution. Ecology Letters, 3(4): 349–361. doi:  https://doi.org/10.1046/j.1461-0248.2000.00143.x CrossRefGoogle Scholar
  42. Qian Fawen, Jiang Hongxing, Yu Guohai et al., 2012. Survey of breeding populations of the Red-crowned crane (Grus japonensis) in the Songnen Plain, Northeastern China. Chinese Birds, 3(3): 217–224. doi:  https://doi.org/10.5122/cbirds.2012.0028 Google Scholar
  43. Rodríguez-Rodríguez D, Martínez-Vega J, 2018. Protected area effectiveness against land development in Spain. Journal of Environmental Management, 215: 345–357. doi:  https://doi.org/10.1016/j.jenvman.2018.03.011 CrossRefGoogle Scholar
  44. Rondinini C, Chiozza F, 2010. Quantitative methods for defining percentage area targets for habitat types in conservation planning. Biological Conservation, 143(7): 1646–1653. doi:  https://doi.org/10.1016/j.biocon.2010.03.037 CrossRefGoogle Scholar
  45. Sánchez-Clavijo L M, Hearns J, Quintana-Ascencio P F, 2016. Modeling the effect of habitat selection mechanisms on population responses to landscape structure. Ecological Modelling, 328: 99–107. doi:  https://doi.org/10.1016/j.ecolmodel.2016.03.004 CrossRefGoogle Scholar
  46. Schmeller D S, Evans D, Lin Y P et al., 2014. The national responsibility approach to setting conservation priorities — recommendations for its use. Journal for Nature Conservation, 22(4): 349–357. doi:  https://doi.org/10.1016/j.jnc.2014.03.002 CrossRefGoogle Scholar
  47. Senzaki M, Yamaura Y, Nakamura F et al., 2015. The usefulness of top predators as biodiversity surrogates indicated by the relationship between the reproductive outputs of raptors and other bird species. Biological Conservation, 191: 460–468. doi:  https://doi.org/10.1016/j.biocon.2015.07.027 CrossRefGoogle Scholar
  48. Shi K F, Huang C, Chen Y et al., 2018. Remotely sensed nighttime lights reveal increasing human activities in protected areas of China mainland. Remote Sensing Letters, 9(5): 467–476. doi:  https://doi.org/10.1080/2150704X.2018.1439199 CrossRefGoogle Scholar
  49. Sonnier G, Bohlen P J, Swain H M et al., 2018. Assessing the success of hydrological restoration in two conservation easements within Central Florida ranchland. PLoS One, 13(7): e0199333. doi:  https://doi.org/10.1371/journal.pone.0199333 CrossRefGoogle Scholar
  50. Wang Wen, Wang Xiuhui, Gao Zhongxin et al., 1999. Distribution of cranes in Hulunber grassland and Daxing’an Mountains forest region in Inner Mongolia. Journal of Forestry Research, 10(1): 55–58. doi:  https://doi.org/10.1007/bf02855482 CrossRefGoogle Scholar
  51. Wang Zhiliang, 2016. GAP Analysis of Wetland Nature Reserve in Nenjiang River Basin, Northeast China. Changchun: Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences. (in Chinese)Google Scholar
  52. Wang Z L, Wang Z M, Zhang B et al., 2015. Impact of land use/land cover changes on ecosystem services in the Nenjiang River Basin, Northeast China. Ecological Processes, 4(1): 11. doi:  https://doi.org/10.1186/s13717-015-0036-y CrossRefGoogle Scholar
  53. Wu Qingming, Wang Lei, Zhu Ruiping et al., 2016. Nesting habitat suitability analysis of red-crowned crane in Zhalong Nature Reserve based on Maxent modeling. Acta Ecologica Sinica, 36(12): 3758–3764. (in Chinese)Google Scholar
  54. Xu H G, Cao M C, Wang Z et al., 2018. Low ecological representation in the protected area network of China. Ecology and Evolution, 8(12): 6290–6298. doi:  https://doi.org/10.1002/ece3.4175 CrossRefGoogle Scholar
  55. Zhang L B, Luo Z H, Mallon D et al., 2017. Biodiversity conservation status in China’s growing protected areas. Biological Conservation, 210: 89–100. doi:  https://doi.org/10.1016/j.biocon.2016.05.005 CrossRefGoogle Scholar
  56. Zhang Yanhong, He Chunguang, 2009. Dynamic change of suitable habitat for Red-crowned crane in Zhalong Natural Reserve based on GIS. Journal of Northeast Forestry University, 37(4): 43–45. (in Chinese)Google Scholar
  57. Zisenis M, 2017. Is the Natura 2000 network of the European Union the key land use policy tool for preserving Europe’s biodiversity heritage? Land Use Policy, 69: 408–416. doi:  https://doi.org/10.1016/j.landusepol.2017.09.045 CrossRefGoogle Scholar

Copyright information

© Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zhiliang Wang
    • 1
    • 2
  • Bai Zhang
    • 3
    Email author
  • Xuezhen Zhang
    • 1
  • Hongxu Tian
    • 2
  1. 1.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.College of ScienceQiqihar UniversityQiqiharChina
  3. 3.Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchunChina

Personalised recommendations