in

Assessing the effectiveness of a national protected area network for carnivore conservation

  • 1.

    Coetzee, B. W. T., Gaston, K. J. & Chown, S. L. Local scale comparisons of biodiversity as a test for global protected area ecological performance: a meta-analysis. PLoS ONE 9, e105824 (2014).

    ADS  PubMed  PubMed Central  Google Scholar 

  • 2.

    Gray, C. L. et al. Local biodiversity is higher inside than outside terrestrial protected areas worldwide. Nat. Commun. 7, 12306 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  • 3.

    Geldmann, J. et al. Effectiveness of terrestrial protected areas in reducing habitat loss and population declines. Biol. Conserv. 161, 230–238 (2013).

    Google Scholar 

  • 4.

    Jones, K. R. et al. One-third of global protected land is under intense human pressure. Science 360, 788–791 (2018).

    CAS  PubMed  Google Scholar 

  • 5.

    Jones, T., Hawes, J. E., Norton, G. W. & Hawkins, D. M. Effect of protection status on mammal richness and abundance in Afromontane forests of the Udzungwa Mountains, Tanzania. Biol. Conserv. 229, 78–84 (2019).

    Google Scholar 

  • 6.

    Cheng, B. S., Altieri, A. H., Torchin, M. E. & Ruiz, G. M. Can marine reserves restore lost ecosystem functioning? A global synthesis. Ecology 100, e02617 (2019).

    PubMed  Google Scholar 

  • 7.

    Terraube, J., Fernández‐Llamazares., Á. & Cabeza, M. The role of protected areas in supporting human health: a call to broaden the assessment of conservation outcomes. Curr. Opin. Env. Sust. 25, 50–58 (2017).

    Google Scholar 

  • 8.

    Naidoo, R. et al. Evaluating the impacts of protected areas on human well‐being across the developing world. Sci. Adv. 5, eaav3006 (2019).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  • 9.

    Rodrigues, A. S. L. et al. Effectiveness of the global protected area network in representing species diversity. Nature 428, 640–643 (2004).

    ADS  CAS  PubMed  Google Scholar 

  • 10.

    Eklund, J. & Cabeza, M. Quality of governance and effectiveness of protected areas: crucial concepts for conservation planning. Ann. N.Y. Acad. Sci. 1399, 27–41 (2017).

    ADS  PubMed  Google Scholar 

  • 11.

    Leverington, F., Costa, K. L., Pavese, H., Lisle, A. & Hockings, M. A global analysis of protected area management effectiveness. Environ. Manag. 46, 685–698 (2010).

    ADS  Google Scholar 

  • 12.

    Coad, L. et al. Measuring impact of protected area management interventions: current and future use of the global database of protected area management effectiveness. Philos. Trans. R. Soc. B. 370, 2014–2081 (2015).

    Google Scholar 

  • 13.

    Watson, J. et al. Bolder science needed now for protected areas. Conserv. Biol. 30, 243–248 (2016).

    PubMed  Google Scholar 

  • 14.

    Barnes, M. D., Glew, L., Wyborn, C. & Craigie, I. D. Prevent perverse outcomes from global protected area policy. Nat. Ecol. Evol. 2, 759–762 (2018).

    PubMed  Google Scholar 

  • 15.

    Andam, K., Ferraro, P. J., Pfaff, A., Sanchez-Azofeifa, G. A. & Robalino, J. A. Measuring the effectiveness of protected area networks in reducing deforestation. Proc. Natl Acad. Sci. USA 105, 16089–16094 (2008).

    ADS  CAS  PubMed  Google Scholar 

  • 16.

    Nolte, C., Agrawal, A., Silvius, K. M. & Soares-Filho, B. S. Governance regime and location influence avoided deforestation success of protected areas in the Brazilian Amazon. Proc. Natl Acad. Sci. USA 110, 4956–4961 (2013).

    ADS  CAS  PubMed  Google Scholar 

  • 17.

    Carranza, T., Balmford, A., Kapos, V. & Manica, A. Protected area effectiveness in reducing conversion in a rapidly vanishing ecosystem: the Brazilian Cerrado. Conserv. Lett. 7, 216–223 (2014).

    Google Scholar 

  • 18.

    Pfaff, A., Robalino, J., Herrera, D. & Sandoval, C. Protected areas’ impacts on Brazilian Amazon deforestation: examining conservation‐development interactions to Inform planning. PLoS ONE 10, 1–17 (2015).

    Google Scholar 

  • 19.

    Barnes, M. D. et al. Wildlife population trends in protected areas predicted by national socio‐economic metrics and body size. Nat. Commun. 7, 12747 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  • 20.

    Beaudrot, L. et al. Standardized assessment of biodiversity trends in tropical forest protected areas: the end is not in sight. PLoS Biol. 14, e1002357 (2016).

    PubMed  PubMed Central  Google Scholar 

  • 21.

    Lindsey, P. A. et al. Relative efforts of countries to conserve world’s megafauna. Glob. Ecol. Conserv. 10, 243–252 (2017).

    Google Scholar 

  • 22.

    Bauer, H. et al. Lion (Panthera leo) populations are declining rapidly across Africa, except in intensively managed areas. Proc. Natl Acad. Sci. USA 112, 14894–14899 (2015).

    ADS  CAS  PubMed  Google Scholar 

  • 23.

    Durant, S. M. et al. The global decline of cheetah Acinonyx jubatus and what it means for conservation. Proc. Natl Acad. Sci. USA 114, 528–533 (2017).

    CAS  PubMed  Google Scholar 

  • 24.

    Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).

    PubMed  Google Scholar 

  • 25.

    Chapron, G. et al. Recovery of large carnivores in Europe’s modern human-dominated landscapes. Science 346, 1517–1519 (2014).

    ADS  CAS  PubMed  Google Scholar 

  • 26.

    Liberg, O. et al. Shoot, shovel and shut up: cryptic poaching slows restoration of a large carnivore in Europe. Proc. R. Soc. Biol. Sci. Ser. B. 279, 910–915 (2012).

    Google Scholar 

  • 27.

    Chapron, G. & Treves, A. Blood does not buy goodwill: allowing culling increases poaching of a large carnivore. Proc. R. Soc. Biol. Sci. Ser. B. 283, 20162577 (2016).

    Google Scholar 

  • 28.

    Rauset, G. R. et al. National parks in northern Sweden as refuges for illegal killing of large carnivores. Conserv. Lett. 9, 334–341 (2016).

    Google Scholar 

  • 29.

    Transparency International (TI). Corruption Perceptions Index. https://www.transparency.org/cpi2018. Accessed 15 Nov 2019 (2018).

  • 30.

    Pohja-Mykrä, M. & Kurki, S. Strong community support for illegal killing challenges wolf management. Eur. J. Wildl. Res. 60, 759–770 (2014).

    Google Scholar 

  • 31.

    Suutarinen, J. & Kojola, I. Poaching regulates the legally hunted wolf population in Finland. Biol. Conserv. 215, 11–18 (2017).

    Google Scholar 

  • 32.

    Inman, R. M., Nagoin, A. J., Persson, J. & Mattisson, J. The wolverine’s niche: linking reproductive chronology, caching, competition and climate. J. Mammal. 93, 634–644 (2012).

    Google Scholar 

  • 33.

    Heim, N., Fisher, J. T., Clevenger, A., Paczkowski, J. & Volpe, J. Cumulative effects of climate and landscape change drive spatial distribution of Rocky Mountain wolverine (Gulo gulo L.). Ecol. Evol. 7, 8903–8914 (2017).

    PubMed  PubMed Central  Google Scholar 

  • 34.

    Ruusila, V. & Kojola. I. Ungulates and their management in Finland. In: European ungulates and their management in the 21st century. (eds Apollonio, M., Andersen, R. & Putman, R.) 86–102 (Cambridge University Press, Cambridge, 2010).

  • 35.

    Stenset, N. E. et al. Seasonal and annual variation in the diet of brown bears Ursus arctos in the boreal forest of southcentral Sweden. Wildl. Biol. 22, 107–116 (2016).

    Google Scholar 

  • 36.

    Pulliainen, E., Lindgren, E. & Tunkkari, P. S. Influence of food availability and reproductive status on the diet and body condition of the European lynx in Finland. Acta Theriol. 40, 181–196 (1995).

    Google Scholar 

  • 37.

    Ministry of the Agriculture and Forestry. Management plan for the lynx population in Finland. Vammalan Kirjapaino Oy (2007).

  • 38.

    Persson, J., Ericsson, G. & Segerström, P. Human caused mortality in the endangered Scandinavian wolverine population. Biol. Conserv. 142, 325–331 (2009).

    Google Scholar 

  • 39.

    Metsähallitus. Principles of Protected Area Management in Finland. (Natural Heritage Services, 2016).

  • 40.

    Mattisson, J. et al. Predation or scavenging? Prey body condition influences decision-making in a facultative predator, the wolverine. Ecosphere 7, e01407 (2016).

    Google Scholar 

  • 41.

    Hobbs, N. T., Andrén, H., Persson, J., Aronsson, M. & Chapron, G. Native predators reduce harvest of reindeer by Sami pastoralists. Ecol. Appl. 22, 1640–1654 (2012).

    PubMed  Google Scholar 

  • 42.

    Colpaert, A. & Kumpula, J. Detecting changes in the state of reindeer pastures in northernmost Finland, 1995–2005. Polar Rec. 48, 74–82 (2012).

    Google Scholar 

  • 43.

    Heikkinen, H. I., Moilanen, O., Nuttall, M. & Sarkki, S. Managing predators, managing reindeer: contested conceptions of predator policies in Finland’s southeast reindeer herding area. Polar Rec. 47, 218–230 (2011).

    Google Scholar 

  • 44.

    Pape, R. & Löffler, J. Climate change, land use conflicts, predation and ecological degradation as challenges for reindeer husbandry in northern Europe: What do we really know after half a century of research? Ambio 41, 421–434 (2012).

    PubMed  PubMed Central  Google Scholar 

  • 45.

    De Pourcq, K. et al. Conflict in protected areas: who says co-management does not work? PLoS ONE 10, e0144943 (2015).

    PubMed  PubMed Central  Google Scholar 

  • 46.

    Eklund, J., Coad, L., Geldmann, J. & Cabeza, M. What constitutes a useful measure of protected area effectiveness? A case study of management inputs and protected area impacts in Madagascar. Conserv. Sci. Pract. 1, e107 (2019).

    Google Scholar 

  • 47.

    Uboni, A., Smith, D. W., Mao, J. S., Stahler, D. R. & Vucetich, J. A. Long‐ and short‐term temporal variability in habitat selection of a top‐predator. Ecosphere 6, 51 (2015).

    Google Scholar 

  • 48.

    Filla, M. et al. Habitat selection by Eurasian lynx (Lynx lynx) is primarily driven by avoidance of human activity during day and prey availability during night. Ecol. Evol. 7, 6367–6381 (2017).

    PubMed  PubMed Central  Google Scholar 

  • 49.

    Sazatornil, V. et al. The role of human‐related risk in breeding site selection by wolves. Biol. Conserv. 201, 103–110 (2016).

    Google Scholar 

  • 50.

    Metz, M. C., Smith, D. W., Vucetich, J. A., Stahler, D. R. & Peterson, R. O. Seasonal patterns of predation for gray wolves in the multi-prey system of Yellowstone National Park. J. Anim. Ecol. 81, 553–563 (2012).

    PubMed  Google Scholar 

  • 51.

    Golden, H. N. et al. Estimating wolverine Gulo gulo population size using quadrat sampling of tracks in snow. Wildl. Biol. 13, 52–61 (2007).

    Google Scholar 

  • 52.

    Kojola, I. et al. (2014). Tracks in snow and population size estimation: the wolf Canis lupus in Finland. Wildl. Biol. 20, 279–284 (2014).

    Google Scholar 

  • 53.

    Wikenros, C. et al. Fear or food–abundance of red fox in relation to occurrence of lynx and wolf. Sci. Rep. 7, 9059 (2017).

    ADS  PubMed  PubMed Central  Google Scholar 

  • 54.

    Geldmann, J., Manica, A., Burgess, N. D., Coad, L. & Balmford, A. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. Proc. Natl Acad. Sci. USA 116, 23209–23215 (2019).

    ADS  CAS  PubMed  Google Scholar 

  • 55.

    Schleicher, J., Peres, C. A. & Leader‐Williams, N. Conservation performance of tropical protected areas: How important is management? Conserv. Lett. 12, e12650 (2019).

    Google Scholar 

  • 56.

    Pringle, R. M. Upgrading protected areas to conserve wild biodiversity. Nature 546, 91–99 (2017).

    ADS  CAS  PubMed  Google Scholar 

  • 57.

    Visconti, P. et al. Protected area targets post‐2020. Science 364, 239–241 (2019).

    ADS  CAS  PubMed  Google Scholar 

  • 58.

    Lindén, H. et al. Wildlife triangle scheme in Finland: methods and aims for monitoring wildlife populations. Finn. Game Res. 49, 4–11 (1996).

    Google Scholar 

  • 59.

    Milanesi, P., Breiner, F. T., Puopolo, F. & Holderegger, R. European human-dominated landscapes provide ample space for the recolonization of large carnivore populations under future land change scenarios. Ecography 40, 1359–1368 (2017).

    Google Scholar 

  • 60.

    R. Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2018).

  • 61.

    IUCN and UNEP-WCMC.The World Database on Protected Areas (WDPA). (UNEP-WCMC, Cambridge, UK, 2017). www.protectedplanet.net Accessed 3 May 2018.

    Google Scholar 

  • 62.

    Ho, D. E., Imai, K., King, G. & Stuart, E. A. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Anal. 15, 199–236 (2007).

    Google Scholar 

  • 63.

    Imbens, G. W. & Wooldridge, J. M. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47, 5–86 (2009).

    Google Scholar 

  • 64.

    Rizopoulos, D. GLMMadaptive: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature. https://drizopoulos.github.io/GLMMadaptive/, https://github.com/drizopoulos/GLMMadaptive. (2019).

  • 65.

    Hedeker, D., du Toit, S. H., Demirtas, H. & Gibbons, R. D. A note on marginalization of regression parameters from mixed models of binary outcomes. Biometrics 74, 354–361 (2018).

    MathSciNet  PubMed  MATH  Google Scholar 


  • Source: Ecology - nature.com

    Competitive ability and plasticity of Wedelia trilobata (L.) under wetland hydrological variations

    A layered approach to safety