Korean Journal of Environmental Biology (환경생물)

Korean Society of Environmental Biology (한국환경생물학회)
권호 표지
DOI QR코드

DOI QR Code

Developing system of forest habitat quality assessment for endangered species

멸종위기 야생생물 산림 서식지 질적 평가 체계 개발

  • Kwang Bae Yoon (Division of Restoration Strategy, National Institute of Ecology) ;
  • Sunryoung Kim (Division of Restoration Strategy, National Institute of Ecology) ;
  • Seokwan Cheong (Division of Restoration Strategy, National Institute of Ecology) ;
  • Jinhong Lee (Division of Restoration Strategy, National Institute of Ecology) ;
  • Jae Hwa Tho (Division of Restoration Strategy, National Institute of Ecology) ;
  • Seung Hyun Han (Forest Technology and Management Research Center, National Institute of Forest Science)
  • 윤광배 (국립생태원 복원전략실) ;
  • 김선령 (국립생태원 복원전략실) ;
  • 정석환 (국립생태원 복원전략실) ;
  • 이진홍 (국립생태원 복원전략실) ;
  • 도재화 (국립생태원 복원전략실) ;
  • 한승현 (국립산림과학원 산림기술경영연구소)
  • Received : 2022.09.01
  • Accepted : 2022.09.20
  • Published : 2022.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

In terms of habitat conservation, it is essential to develop a habitat assessment system that can evaluate not only the suitability of the current habitat, but also the health and stability of the habitat. This study aimed to develop a methodology of habitat quality assessment for endangered species by analyzing various existing habitat assessment methods. The habitat quality assessment consisted of selecting targeted species, planning of assessment, selecting targeted sites, assessing performance, calculating grade, and expert verification. Target sites were selected separately from core and potential habitats using a species distribution model or habitat suitability index. Habitat assessment factors were classified into ecological characteristic, landscape characteristic, and species-habitat characteristic. Ecological characteristic consisted of thirteen factors related to health of tree, vegetation, and soil. Landscape characteristic consisted of five factors related to fragment and connectivity of habitat. Species-habitat characteristic consisted of factors for evaluating habitat suitability depending on target species. Since meanings are different depending on characteristics, habitat quality assessment of this study could be used by classifying results for each characteristic according to various assessment purposes, such as designation of alternative habitats, assessment of restoration project, and protected area valuation for endangered species. Forest habitat quality assessment is expected to play an important role in conservation acts of endangered species in the future through continuous supplementation of this system in regard to quantitative assessment criteria and weighting for each factor with an influence.

본 연구에서는 서식지 질적 평가에 대한 추진체계를 6단계로 구분하고, 평가 대상지 선정 방법과 서식지 질적 평가 항목을 제시하였다. 서식지 질적 평가 항목은 서식지의 건강성, 안정성, 단절화 및 파편화 정도, 서식지 적합성, 위협 정도 등에 대한 종합적인 평가가 가능하도록 구성되었다. 그러나 현시점에서는 자료부족으로 인하여 서식지 질적 평가 체계가 적용 가능한 멸종위기종이 극히 일부에 해당된다. 서식지 질적 평가 체계는 향후 멸종위기종들에 관한 서식환경자료가 축적되고 이를 기반으로 평가항목들에 대한 정량적 기준 및 가중치가 부여되면 멸종위기종별 주요 서식지에 대한 보전방안 마련에 크게 기여할 것으로 기대된다.

Keywords

Acknowledgement

본 연구는 국립생태원 연구과제(NE-고유연구-2022-34)의 지원에 의해 수행되었습니다.

References

  1. Beier P and RF Noss. 1998. Do habitat corridors provide connectivity? Conserv. Biol. 12:1241-1252. https://doi.org/10.1111/j.1523-1739.1998.98036.x
  2. Chau JF, AC Bagtzoglou and MR Willig. 2011. The effect of soil texture on richness and diversity of bacterial communities. Environ. Forensics 12:333-341. https://doi.org/10.1080/15275922.2011.622348
  3. Evans MC, JEM Watson, RA Fuller, O Venter, SC Bennett, PR Marsack and HP Possingham. 2011. The spatial distribution of threats to species in Autralia. Bioscience 61:281-289. https://doi.org/10.1525/bio.2011.61.4.8
  4. Fahrig L. 2018. Habitat fragmentation: A long and tangled tale. Glob. Ecol. Biogeogr. 28:33-41. https://doi.org/10.1111/geb.12839
  5. Guisan A and NE Zimmermann. 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135:147-186. https://doi.org/10.1016/S0304-3800(00)00354-9
  6. Han SH, JH Kim, WS Kang, JH Hwang, KH Park and CB Kim. 2019. Monitoring soil characteristics and growth of Pinus densiflora five years after restoration in the Baekdudaegan ridge. Korean J. Environ. Ecol. 33:453-461. https://doi.org/10.13047/KJEE.2019.33.4.453
  7. He J, J Huang and C Li. 2017. The evaluation for the impact of land use change on habitat quality: A joint contribution of cellular automata scenario simulation and habitat quality assessment model. Ecol. Model. 366:58-67. https://doi.org/10.1016/j.ecolmodel.2017.10.001
  8. IUCN Red List version 2022-1. International Union for Conservation of Nature. https://www.iucn.org/press-release/202207/migratory-monarch-butterfly-now-endangerediucn-red-list. Date/time: 3 Aug, 2022, 9 am.
  9. Jung J, Y Shimizu, K Omasa, S Kim and S Lee .2016. Developing and testing a habitat suitability index model for Korean water deer (Hydropotes inermis argyropus) and its potential for landscape management decisions in Korea. Anim. Cells Syst. 20:218-227. https://doi.org/10.1080/19768354.2016.1210228
  10. Kangas J, R Store, P Leskinene and L Mehtatalo. 2000. Improving the quality of landscape ecological forests planning by utilizing advanced decision-support tool. For. Ecol. Manage. 132:157-171. https://doi.org/10.1016/S0378-1127(99)00221-2
  11. Kim HG, EJ Lee, C Park, KS Lee, DK Lee, WS Lee and JU Kim. 2016. Modeling the habitat of the red-crowned crane (Grus japonensis) wintering in Cheorwon-Gun to support decision making. Sustainability 8:576. https://doi.org/10.3390/su8060576
  12. Kim JY, JG Kim, DY Bae, HJ Kim, JE Kim, HS Lee, JY Lim and KG An. 2020. International and domestic research trends in longitudinal connectivity evaluations of aquatic ecosystems, and the applicability analysis of fish-based models. Korean J. Environ. Biol. 38:634-649. https://doi.org/10.11626/KJEB.2020.38.4.634
  13. Korea Forest Service. 2020. 2020 Statistical Yearbook of Forestry. Korea Forest Service. Daejeon, Korea. p. 40.
  14. Liana W, H Jean-Marc and H Michael. 2013. Evaluating ecological restoration success: A review of the literature. Restor. Ecol. 21:537-543. https://doi.org/10.1111/rec.12028
  15. Liang J, S Hua, G Zeng, Y Yuan, X Lai, X Li, F Li, H Wu, L Huang and X Yu. 2015. Application of weight method based on canonical correspondence analysis for assessment of Anatidae habitat suitability: A case study in East Dongting Lake, Middle China. Ecol. Eng. 77:119-126. https://doi.org/10.1016/j.ecoleng.2015.01.016
  16. Ministry of Environment(ME). 2011. A Study on Plan Preparation for Habitat Suitability Assessment of Endangered Species by Development Project. Ministry of Environment. Sejong, Korea. pp. 60-63.
  17. NIFOS. 2017. Development of Monitoring Indicators and Evaluation Techniques for Forest Health. National Institute of Forest Science. Seoul. pp. 35-57.
  18. Park T, H Jang, SE Eom, K Son and JJ Park. 2022. Analysis and estimation of species distribution of Mythimna seperata and Cnaphalocrocis medinalis with land-cover data under climate change scenario using MaxEnt. Korean J. Environ. Biol. 40:214-223. https://doi.org/10.11626/KJEB.2022.40.2.214
  19. Ross S, JM Costanzi, MA Jahdhami, HA Rawahi and M Ghazali. 2020. First evaluation of the population structure, genetic diversity and landscape connectivity of the Endangered Arabian tahr. Mamm. Biol. 100:659-673. https://doi.org/10.1007/s42991-020-00072-4
  20. Salsabila R, H Hariyadi and N Santoso. 2021. Tree health management strategy in Cianjur urban forest. Jurnal Sylva Lestari 9:86-103. https://doi.org/10.23960/jsl1986-103
  21. Santruckova H, E Cienciala, J Kana and J Kopacek. 2019. The chemical composition of forest soils and their degree of acidity in Central Europe. Sci. Total Environ. 687:96-103. https://doi.org/10.1016/j.scitotenv.2019.06.078
  22. Sharp, R. HT Tallis, T Ricketts, AD Guerry, SA Wood, R Chaplin-Kramer, E Nelson, D Ennaanay, S Wolny, N Olwero, K Vigerstol, D Pennington, G Mendoza, J Aukema, J Foster, J Forrest, D Cameron, K Arkema, E Lonsdorf, C Kennedy, G Verutes, CK Kim, GGuannel, M Papenfus, J Toft, M Marsik, J Bernhardt, R Griffin, K Glowinski, N Chaumont, A Perelman, M Lacayo, L Mandle, R Griffin and P Hamel. 2014. InVEST Tip User's Guide. The Natural Capital Project, Stanford University. Stanford, CA.
  23. State of Queensland. 2015. BioCondition (A Condition Assessment Framework for Terrestrial Biodiversity in Queensland). Queensland Government. Australia. pp. 27-33.
  24. State of Queensland. 2020. Guide to Determining Terrestrial Habitat Quality. Queensland Government. Australia.
  25. Stiver SJ, ET Rinkes, DE Naugle, PD Makela, DA Nance and JW Karl. 2015. Sage-Grouse Habitat Assessment Framework: A Multiscale Assessment Tool. Technical Reference 6710-1. Bureau of Land Management and Western Association of Fish and Wildlife Agencies. Denver, CO. pp. 9-11.
  26. Terrado M, S Sabater, B Chaplin-Kramer, L Mandle, G Ziv and V Acuna. 2016. Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning. Sci. Total Environ. 540:63-70. https://doi.org/10.1016/j.scitotenv.2015.03.064
  27. Wolf J, R Baker and E Reed. 2012. An assessment of vegetation cover for grassland bird breeding habitat in southeastern Wisconsin. Bird Popul. 11:22-29.
  28. Yang X, J Fan and SB Jones. 2018. Effect of soil texture on estimates of soil-column carbon dioxide flux comparing chamber and gradient methods. Vadose Zone J. 17:1-9. https://doi.org/10.2136/vzj2018.05.0112
  29. Zhang W, B Hu, M Woods and G Brown. 2017. Characterizing forest succession stages for wildlife habitat assessment using multispectral airborne imagery. Forests 8:234. https://doi.org/10.3390/f8070234
  30. Zuquim G, FRC Costa, H Tuomisto, GM Moulatlet and FOG Figueiredo. 2020. The importance of soils in predicting the future of plant habitat suitability in a tropical forest. Plant Soil 450:151-170. https://doi.org/10.1007/s11104-018-03915-9