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Habitat probability prediction of umbrella species in urban ecosystems including habitat suitability of prey species

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A Correction to this article was published on 10 April 2023

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Abstract

Habitat management through distribution tracking of umbrella species has been used to improve urban ecosystem health and sustainability to enhance the life quality of citizens. However, there are practical limitations to the application of habitat distribution analysis methods applied to urban ecosystems due to human disturbance. Considering additional habitat suitability information of prey species, the prediction of habitat reflecting complex urban environmental characteristics would be improved in Suwon city, South Korea. The habitat probability of Strigidae, which is an umbrella species of Suwon city, and prey species is predicted using the Maximum Entropy (MaxEnt) model. We determined whether the inclusion of prey species habitat probability in that of Strigidae can improve the prediction as well as has the same effect for a Eurasian hobby (Falco Subbuteo) like Strigidae. The performance of MaxEnt was improved when not only environmental variables but also prey species habitat probability is added. When the presence information was sampled by the k-fold method, the probability of detection of surveyed points was improved by 1.38 times. Our results indicate that prey species information is important to both Strigidae and the Eurasian hobby. Therefore, using prey species habitat information can improve the reliability of habitat analysis by supplementing information and reflect complex urban ecosystems.

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Data availability

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

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References

  • Abumandour MM (2014) Histomorphological studies on the stomach of Eurasian hobby (Falconinae. Falco subbuteo, Linnaeus1758) and its relation with its feeding habits. Life Sci J 11(7):809–819

    Google Scholar 

  • Ansari A, Golabi MH, Abad BSE (2021) Evaluation of factors affecting predator-prey distribution for grey wolves, wild sheep, and wild goats in Haftad-Gholleh National Park, Iran. J Wildlife Biodivers 5(4):53-67

    Google Scholar 

  • Bartholomew GA, Cade TJ (1963) The water economy of land birds. Auk 80(4):504–539

    Article  Google Scholar 

  • Beery S, Cole E, Parker J, Perona P, Winner K (2021). Species distribution modeling for machine learning practitioners: a review. In: ACM SIGCAS Conference on Computing and Sustainable Societies, pp 329–348

  • Boal CW, Dykstra CR (eds) (2018) Urban raptors: ecology and conservation of birds of prey in cities. Island Press

    Google Scholar 

  • Boitani L, Fuller T (2000) Research techniques in animal ecology, 2nd edn. Columbia University Press, New York

    Google Scholar 

  • Buffum B, Masse R, McWilliams SR (2021) Novel use of species distribution modeling to identify high priority sites for American woodcock habitat management. Northeast Nat 28(3):233–247

    Article  Google Scholar 

  • Caro T (2010) Conservation by proxy: Indicator, umbrella, keystone, flagship, and other surrogate species. Island Press, Washington

    Google Scholar 

  • Chae H, Park J, Choi C, Bing K (2009) Field guide to the raptors of Korea. Korea National Park Service, Seoul

    Google Scholar 

  • Choi C, Nam H, Lee W (2007) Diets and foraging tactics of Eurasian eagle owls (Bubo bubo) in two different habitat types. Korean J Environ Ecol 21(1):30–37

    Google Scholar 

  • Collinge SK (1996) Ecological consequences of habitat fragmentation: implications for landscape architecture planning. Landscape Urban Plann 36(1):59-77. https://doi.org/10.1016/S0169-2046(96)00341-6

    Article  Google Scholar 

  • Del Hoyo J, Elliott A, Sargatal J (1992) Handbook of the birds of the world, vol 2. Lynx edicions, Barcelona (No. 8)

    Google Scholar 

  • Drake EC, Gignoux-Wolfsohn S, Maslo B (2020) Systematic review of the roost-site characteristics of North American forest bats: implications for conservation. Diversity 12(2):76

    Article  Google Scholar 

  • Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17(1):43–57

    Article  Google Scholar 

  • Engler R, Guisan A, Rechsteiner L (2004) An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo‐absence data. J Appl Ecol 41(2):263–274

    Article  Google Scholar 

  • Favreau JM, Drew CA, Hess GR, Rubino MJ, Koch FH, Eschelbach KA (2006) Recommendations for assessing the effectiveness of surrogate species approaches. Biodivers Conserv 15(12):3949–3969. https://doi.org/10.1007/s10531-005-2631-1

    Article  Google Scholar 

  • Fleishman E, Murphy DD (2009) A realistic assessment of the indicator potential of butterflies and other charismatic taxonomic groups. Conserv Biol 23(5):1109–1116. https://doi.org/10.1111/j.1523-1739.2009.01246.x

    Article  PubMed  Google Scholar 

  • Goosem M (2007) Fragmentation impacts caused by roads through rainforests. Curr Sci 93(11):1587–1595

    Google Scholar 

  • Han SY, Kwan YS et al (2020) Endangered wildlife in Korea. The Korean Association for Conservation of Nature. https://terms.naver.com/list.nhn?cid=42555&categoryId=58530. Accessed 23 Dec 2022

  • Jafari A, Zamani-Ahmadmahmoodi R, Mirzaei R (2019) Persian leopard and wild sheep distribution modeling using the Maxent model in the Tang-e-Sayad protected area, Iran, Mammalia 83(1):84–96

    Article  Google Scholar 

  • Jaksić FM, Braker HE (1983) Food-niche relationships and guild structure of diurnal birds of prey: competition versus opportunism. Can J Zool 61(10):2230–2241. https://doi.org/10.1139/z83-295

    Article  Google Scholar 

  • Ji W, Han K, Lu Y, Wei J (2020) Predicting the potential distribution of the vine mealybug, Planococcus ficus under climate change by MaxEnt. Crop Prot 137:105268. https://doi.org/10.1016/j.cropro.2020.105268

    Article  Google Scholar 

  • Johnson NK (2002) Handbook of the birds of the world, Volume 6. Auk 119(2):573–574. https://doi.org/10.1093/auk/119.2.573

    Article  Google Scholar 

  • Kaivanto K (2008) Maximization of the sum of sensitivity and specificity as a diagnostic cutpoint criterion. J Clin Epidemiol 61(5):517–518. https://doi.org/10.1016/j.jclinepi.2007.10.011

    Article  PubMed  Google Scholar 

  • Kameyama A (2004) Ecological engineering. Seok-ki Moon, Bomundang

    Google Scholar 

  • Kie JG, Matthiopoulos J, Fieberg J, Powell RA, Cagnacci F, Mitchell MS, Moorcroft PR (2010) The home-range concept: Are traditional estimators still relevant with modern telemetry technology? Philos Trans R Soc B: Biol Sci 365:2221–2231. https://doi.org/10.1098/rstb.2010.0093

    Article  Google Scholar 

  • Kittle AM, Watson AC, Cushman SA, Macdonald DW (2018) Forest cover and level of protection influence the island-wide distribution of an apex carnivore and umbrella species, the Sri Lankan leopard (Panthera pardus kotiya). Biodivers Conserv 27(1):235–263. https://doi.org/10.1007/s10531-017-1431-8

    Article  Google Scholar 

  • Kohsaka R, Pereira HM, Elmqvist T, Chan L, Moreno-Peñaranda R, Morimoto Y, Pearsell G (2013) Indicators for management of urban biodiversity and ecosystem services: city biodiversity index. In: Elmqvist T, Fragkias M, Goodness J, Güneralp B, Marcotullio PJ, McDonald RI, Wilkinson C (eds) Urbanization, biodiversity and ecosystem services: challenges and opportunities. Springer, Dordrecht, pp 699–718

    Chapter  Google Scholar 

  • König C, Friedhelm W, Becking JH (2009) Owls of the World, 2nd edn. Christopher Helm, London

    Google Scholar 

  • Lack D (1946) Competition for food by birds of prey. J Anim Ecol 15(2):123–129

    Article  Google Scholar 

  • Lindenmayer DB, Westgate MJ (2020) Are flagship, umbrella and keystone species useful surrogates to understand the consequences of landscape change? Curr Landsc Ecol Rep 5:76–84. https://doi.org/10.1007/s40823-020-00052-x

    Article  Google Scholar 

  • Liu C, White M, Newell G (2013) Selecting thresholds for the prediction of species occurrence with presence-only data. J Biogeogr 40(4):778–789. https://doi.org/10.1111/jbi.12058

    Article  Google Scholar 

  • Liu C, Newell G, White M (2016) On the selection of thresholds for predicting species occurrence with presence-only data. Ecol Evol 6(1):337–348. https://doi.org/10.1002/ece3.1878

    Article  PubMed  Google Scholar 

  • Lundberg J, Andersson E, Cleary G, Elmqvist T (2008) Linkages beyond borders: targeting spatial processes in fragmented urban landscapes. Landscape Ecol 23(6):717–726. https://doi.org/10.1007/s10980-008-9232-9

    Article  Google Scholar 

  • Mace GM, Norris K, Fitter AH (2012) Biodiversity and ecosystem services: a multilayered relationship. Trends Ecol Evol 27(1):19–26. https://doi.org/10.1016/j.tree.2011.08.006

    Article  PubMed  Google Scholar 

  • MacMillen RE (1990) Water economy of granivorous birds: a predictive model. The Condor 92(2):379–392

    Article  Google Scholar 

  • Maslo B, Leu K, Faillace C, Weston MA, Pover T, Schlacher TA (2016) Selecting umbrella species for conservation: a test of habitat models and niche overlap for beach-nesting birds. Biol Cons 203:233–242

    Article  Google Scholar 

  • Merow C, Smith MJ, Silander JA Jr (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36(10):1058–1069

    Article  Google Scholar 

  • Michailidou DE, Lazarina M, Sgardelis SP (2021) Temperature and prey species richness drive the broad-scale distribution of a generalist predator. Diversity 13(4):169. https://doi.org/10.3390/d13040169

    Article  Google Scholar 

  • Ministry of Environment, Korea (2020) Natural Environment Conservation Act. https://www.law.go.kr/LSW/eng/engLsSc.do?menuId=2andsection=lawNmandquery=Natural+Environment+Conservation+Actandx=0andy=0#liBgcolor19. Accessed 2021.04.14.

  • Ministry of Land and Infrastructure and Transport, Korea (2019) The National Atlas of Korea. http://nationalatlas.ngii.go.kr/us/index.php. Accessed 14 Apr 2021

  • Nielsen AB, Van Den Bosch M, Maruthaveeran S, Van Den Bosch CK (2014) Species richness in urban parks and its drivers: a review of empirical evidence. Urban Ecosyst 17(1):305–327. https://doi.org/10.1007/s11252-013-0316-1

    Article  Google Scholar 

  • Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson A (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34(1):102–117

    Article  Google Scholar 

  • Phillips SB, Dudík M, Schapire RE (2006) Modelling and analysis of the atmospheric nitrogen deposition in North Carolina. Int J Glob Environ Issues 6(2–3):231–252. https://doi.org/10.1016/j.ecolmodel.2005.03.026

    Article  Google Scholar 

  • Radosavljevic A, Anderson RP (2014) Making better Maxent models of species distributions: complexity, overfitting and evaluation. J Biogeogr 41(4):629–643

    Article  Google Scholar 

  • Reidinger RF Jr, Miller JE (2013) Wildlife damage management: prevention, problem solving, and conflict resolution. JHU Press

    Book  Google Scholar 

  • Reza MIH, Abdullah SA, Nor SB, Ismail MH (2013) Integrating GIS and expert judgment in a multi-criteria analysis to map and develop a habitat suitability index: a case study of large mammals on the Malayan Peninsula. Ecol Indic 34:149–158. https://doi.org/10.1016/j.ecolind.2013.04.023

    Article  Google Scholar 

  • Rudebeck G (1950) The choice of prey and modes of hunting of predatory birds with special reference to their selective effect. Oikos 2(1):65–88

    Article  Google Scholar 

  • Sattler T, Pezzatti GB, Nobis MP, Obrist MK, Roth T, Moretti M (2014) Selection of multiple umbrella species for functional and taxonomic diversity to represent urban biodiversity. Conserv Biol 28(2):414–426. https://doi.org/10.1111/cobi.12213

    Article  CAS  PubMed  Google Scholar 

  • Sauvajot RM, Buechner M, Kamradt DA, Schonewald CM (1998) Patterns of human disturbance and response by small mammals and birds in chaparral near urban development. Urban Ecosyst 2(4):279–297

    Article  Google Scholar 

  • Savard JPL, Clergeau P, Mennechez G (2000) Biodiversity concepts and urban ecosystems. Landsc Urban Plan 48(3–4):131–142. https://doi.org/10.1016/S0169-2046(00)00037-2

    Article  Google Scholar 

  • Seddon PJ, Leech T (2008) Conservation short cut, or long and winding road? A critique of umbrella species criteria. Oryx 42(2):240–245

    Article  Google Scholar 

  • Smit B, Woodborne S, Wolf BO, McKechnie AE (2019) Differences in the use of surface water resources by desert birds are revealed using isotopic tracers. Auk 136(1):uky005

    Article  Google Scholar 

  • Thomas JA (2005) Monitoring change in the abundance and distribution of insects using butterflies and other indicator groups. Philos Trans R Soc Lond B Biol Sci 360(1454):339–357. https://doi.org/10.1098/rstb.2004.1585

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Timpone JC, Boyles JG, Robbins LW (2006) Potential for niche overlap in roosting sites between Nycticeius humeralis (evening bats) and Eptesicus fuscus (big brown bats). Northeast Nat 13(4):597–602

    Article  Google Scholar 

  • Trainor AM, Schmitz OJ, Ivan JS, Shenk TM (2014) Enhancing species distribution modeling by characterizing predator–prey interactions. Ecol Appl 24(1):204-216. https://doi.org/10.1890/13-0336.1

    Article  PubMed  Google Scholar 

  • Trocmé M, Cahill S, De Vries JG, Farrall H, Folkeson L, Fry G, Peymen J (2003) COST 341-Habitat fragmentation due to transportation infrastructure: the European review. Office for official publications of the European Communities, Luxembourg, pp 31–50

    Google Scholar 

  • Tuanmu MN, Viña A, Bearer S, Xu W, Ouyang Z, Zhang H, Liu J (2010) Mapping understory vegetation using phenological characteristics derived from remotely sensed data. Remote Sens Environ 114(8):833–1844. https://doi.org/10.1016/j.rse.2010.03.008

    Article  Google Scholar 

  • Végvári Z, Barta Z (2015) Roost site selection of the Common Crane in its largest European stop-over site. Ardea 103(2):175–181

    Article  Google Scholar 

  • Vorpahl P, Elsenbeer H, Märker M, Schröder B (2012) How can statistical models help to determine driving factors of landslides? Ecol Modell 239:27–39. https://doi.org/10.1016/j.ecolmodel.2011.12.007

    Article  Google Scholar 

  • Wang G, Wang C, Guo Z, Dai L, Wu Y, Liu H, Xue F (2020) Integrating Maxent model and landscape ecology theory for studying spatiotemporal dynamics of habitat: suggestions for conservation of endangered Red-crowned crane. Ecol Indic 116:106472. https://doi.org/10.1016/j.ecolind.2020.106472

    Article  Google Scholar 

  • Wilcox BA, Murphy DD (1985) Conservation strategy: the effects of fragmentation on extinction. Am Nat 125(6):879-887

    Article  Google Scholar 

  • Won B (1981) Illustrated flora and fauna of Korea: Avifauna. Ministry of Education

    Google Scholar 

  • Zhang J, Jiang F, Li G, Qin W, Li S, Gao H, Zhang T (2019) Maxent modeling for predicting the spatial distribution of three raptors in the Sanjiangyuan National Park, China. Ecol Evol 9(11):6643–6654. https://doi.org/10.1002/ece3.5243

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhang C, Chen Y, Xu B, Xue Y, Ren Y (2020) Improving prediction of rare species’ distribution from community data. Sci Rep 10(1):12230

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zohmann M, Pennerstorfer J, Nopp-Mayr U (2013) Modelling habitat suitability for alpine rock ptarmigan (Lagopus muta helvetica) combining object-based classification of IKONOS imagery and Habitat Suitability Index modelling. Ecol Modell 254:22–32. https://doi.org/10.1016/j.ecolmodel.2013.01.008

    Article  Google Scholar 

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Acknowledgements

This work was conducted with the support of the Korea Environment Industry & Technology Institute via the Urban Ecological Health Promotion Technology Development Project. It was funded by the Korea Ministry of Environment (grant no. 2019002760001). The experiments comply with the current laws of the country in which they were performed.

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Authors and Affiliations

  1. Department of Landscape Architecture, University of Seoul, Seoul, Republic of Korea

    Jaeyeon Choi, Chan Park & Suryeon Kim

  2. Department of Landscape Architecture, Dankook University, Cheonan, Republic of Korea

    Wonkyong Song

  3. Department of Landscape Architecture, Seoul National University, Seoul, Republic of Korea

    Youngkeun Song

  4. Department of Ecological Landscape Architecture Design, Kangwon National University, Chuncheon, Republic of Korea

    Sungho Kil

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  1. Jaeyeon Choi
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  2. Chan Park
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Contributions

JC, SK and, CP conceived the study. JC, SK and CP executed the study and wrote the manuscript. All the authors contributed to the drafts and gave final approval for publication.

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Correspondence to Chan Park.

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The original online version of this article was revised due to fourth author’s first name was published incorrectly as “Wonkyoung” and corrected to “Wonkyong” in this version.

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Choi, J., Park, C., Kim, S. et al. Habitat probability prediction of umbrella species in urban ecosystems including habitat suitability of prey species. Landscape Ecol Eng 19, 417–431 (2023). https://doi.org/10.1007/s11355-023-00550-0

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