in

Identifying priority core habitats and corridors for effective conservation of brown bears in Iran

  • 1.

    Kopatz, A. et al. Connectivity and population subdivision at the fringe of a large brown bear (Ursus arctos) population in North Western Europe. Conserv. Genet. 13, 681–692 (2012).

    Article  Google Scholar 

  • 2.

    Mohammadi, A. & Kaboli, M. Evaluating wildlife–vehicle collision hotspots using kernel-based estimation: a focus on the endangered Asiatic cheetah in central Iran. Hum. Wildl. Interact. 10, 13 (2016).

    Google Scholar 

  • 3.

    Murphy, S. M. et al. Consequences of severe habitat fragmentation on density, genetics, and spatial capture–recapture analysis of a small bear population. PLoS ONE 12, e0181849 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 4.

    Hosseini-Zavarei, F., Farhadinia, M. S., Beheshti-Zavareh, M. & Abdoli, A. Predation by grey wolf on wild ungulates and livestock in central Iran. J. Zool. 290, 1–8 (2013).

    Article  Google Scholar 

  • 5.

    Tumendemberel, O. et al. Phylogeography, genetic diversity, and connectivity of brown bear populations in Central Asia. PLoS ONE 14, e0220746 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 6.

    Hilty, J. A., Lidicker, W. Z. Jr. & Merenlender, A. M. Corridor Ecology: The Science and Practice of Linking Landscapes for Biodiversity Conservation (Island Press, Washington, 2012).

    Google Scholar 

  • 7.

    Cushman, S. A. et al. Limiting factors and landscape connectivity: the American marten in the Rocky Mountains. Landsc. Ecol. 26, 1137 (2011).

    Article  Google Scholar 

  • 8.

    Oriol-Cotterill, A., Valeix, M., Frank, L. G., Riginos, C. & Macdonald, D. W. Landscapes of coexistence for terrestrial carnivores: the ecological consequences of being downgraded from ultimate to penultimate predator by humans. Oikos 124, 1263–1273 (2015).

    Article  Google Scholar 

  • 9.

    Cushman, S. A. et al. Prioritizing core areas, corridors and conflict hotspots for lion conservation in southern Africa. PLoS ONE 13, e0196213 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 10.

    Rio-Maior, H., Nakamura, M., Álvares, F. & Beja, P. Designing the landscape of coexistence: integrating risk avoidance, habitat selection and functional connectivity to inform large carnivore conservation. Biol. Conserv. 235, 178–188 (2019).

    Article  Google Scholar 

  • 11.

    Macdonald, D. W. et al. Multi-scale habitat modelling identifies spatial conservation priorities for mainland clouded leopards (Neofelis nebulosa). Divers. Distrib. 25, 1639–1654 (2019).

    Article  Google Scholar 

  • 12.

    Johansson, Ö. et al. Land sharing is essential for snow leopard conservation. Biol. Conserv. 203, 1–7 (2016).

    Article  Google Scholar 

  • 13.

    López-Bao, J. V., Bruskotter, J. & Chapron, G. Finding space for large carnivores. Nat. Ecol. Evol. 1, 1–2 (2017).

    Article  Google Scholar 

  • 14.

    Crespin, S. J. & Simonetti, J. A. Reconciling farming and wild nature: Integrating human–wildlife coexistence into the land-sharing and land-sparing framework. Ambio 48, 131–138 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  • 15.

    Kaszta, Ż, Cushman, S. A. & Macdonald, D. W. Prioritizing habitat core areas and corridors for a large carnivore across its range. Anim. Conserv. 23, 1–10 (2020).

    Article  Google Scholar 

  • 16.

    Kaszta, Ż et al. Simulating the impact of Belt and Road initiative and other major developments in Myanmar on an ambassador felid, the clouded leopard, Neofelis nebulosa. Landsc. Ecol. 35, 727–746 (2020).

    Article  Google Scholar 

  • 17.

    Cushman, S. A., Compton, B. W. & McGarigal, K. Habitat fragmentation effects depend on complex interactions between population size and dispersal ability: modeling influences of roads, agriculture and residential development across a range of life-history characteristics. In Spatial Complexity, Informatics, and Wildlife Conservation (eds Cushman, S. A. & Huettmann, F.) 369–385 (Springer, Berlin, 2010).

    Google Scholar 

  • 18.

    Kaszta, Ż et al. Integrating Sunda clouded leopard (Neofelis diardi) conservation into development and restoration planning in Sabah (Borneo). Biol. Conserv. 235, 63–76 (2019).

    Article  Google Scholar 

  • 19.

    Beier, P., Majka, D. R. & Spencer, W. D. Forks in the road: choices in procedures for designing wildland linkages. Conserv. Biol. 22, 836–851 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  • 20.

    Romportl, D. et al. Designing migration corridors for large mammals in the Czech Republic. J. Landsc. Ecol. 6, 47–62 (2013).

    Article  Google Scholar 

  • 21.

    Ruiz-González, A. et al. Landscape genetics for the empirical assessment of resistance surfaces: the European pine marten (Martes martes) as a target-species of a regional ecological network. PLoS ONE 9, e110552 (2014).

    PubMed  PubMed Central  Article  ADS  CAS  Google Scholar 

  • 22.

    Cushman, S. A., Elliot, N. B., Macdonald, D. W. & Loveridge, A. J. A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change. Landsc. Ecol. 31, 1337–1353 (2016).

    Article  Google Scholar 

  • 23.

    Linnell, J., Salvatori, V. & Boitani, L. Guidelines for population level management plans for large carnivores in Europe. A Large Carnivore Initiative for Europe (2008).

  • 24.

    Reljic, S. et al. Challenges for transboundary management of a European brown bear population. Glob. Ecol. Conserv. 16, e00488 (2018).

    Article  Google Scholar 

  • 25.

    Mateo Sanchez, M. C., Cushman, S. A. & Saura, S. Scale dependence in habitat selection: the case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain). Int. J. Geogr. Inf. Sci. 28, 1531–1546 (2014).

    Article  Google Scholar 

  • 26.

    Vergara, M., Cushman, S. A., Urra, F. & Ruiz-González, A. Shaken but not stirred: multiscale habitat suitability modeling of sympatric marten species (Martes martes and Martes foina) in the northern Iberian Peninsula. Landsc. Ecol. 31, 1241–1260 (2016).

    Article  Google Scholar 

  • 27.

    Ziółkowska, E. et al. Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians. Landsc. Ecol. 31, 1863–1882 (2016).

    Article  Google Scholar 

  • 28.

    Sarkar, M. S. et al. Multiscale statistical approach to assess habitat suitability and connectivity of common leopard (Panthera pardus) in Kailash Sacred Landscape, India. Spat. Stat. 28, 304–318 (2018).

    MathSciNet  Article  Google Scholar 

  • 29.

    Ashrafzadeh, M. R. et al. A multi-scale, multi-species approach for assessing effectiveness of habitat and connectivity conservation for endangered felids. Biol. Conserv. 245, 108523 (2020).

    Article  Google Scholar 

  • 30.

    McGarigal, K., Wan, H. Y., Zeller, K. A., Timm, B. C. & Cushman, S. A. Multi-scale habitat selection modeling: a review and outlook. Landsc. Ecol. 31, 1161–1175 (2016).

    Article  Google Scholar 

  • 31.

    Wasserman, T. N., Cushman, S. A., Shirk, A. S., Landguth, E. L. & Littell, J. S. Simulating the effects of climate change on population connectivity of American marten (Martes americana) in the northern Rocky Mountains, USA. Landsc. Ecol. 27, 211–225 (2012).

    Article  Google Scholar 

  • 32.

    Mateo-Sánchez, M. C. et al. A comparative framework to infer landscape effects on population genetic structure: Are habitat suitability models effective in explaining gene flow?. Landsc. Ecol. 30, 1405–1420 (2015).

    Article  Google Scholar 

  • 33.

    Zeller, K. A. et al. Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data. Divers. Distrib. 24, 868–879 (2018).

    Article  Google Scholar 

  • 34.

    Cushman, S. A., Lewis, J. S. & Landguth, E. L. Why did the bear cross the road? Comparing the performance of multiple resistance surfaces and connectivity modeling methods. Diversity 6, 844–854 (2014).

    Article  Google Scholar 

  • 35.

    Adriaensen, F. et al. The application of ‘least-cost’modelling as a functional landscape model. Landsc. Urban Plan. 64, 233–247 (2003).

    Article  Google Scholar 

  • 36.

    McRae, B. H. Isolation by resistance. Evolution (N. Y.) 60, 1551–1561 (2006).

    Google Scholar 

  • 37.

    Cushman, S. A., McKelvey, K. S. & Schwartz, M. K. Use of empirically derived source–destination models to map regional conservation corridors. Conserv. Biol. 23, 368–376 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  • 38.

    Compton, B. W., McGarigal, K., Cushman, S. A. & Gamble, L. R. A resistant-kernel model of connectivity for amphibians that breed in vernal pools. Conserv. Biol. 21, 788–799 (2007).

    PubMed  Article  PubMed Central  Google Scholar 

  • 39.

    Panzacchi, M. et al. Predicting the continuum between corridors and barriers to animal movements using step selection functions and randomized shortest paths. J. Anim. Ecol. 85, 32–42 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  • 40.

    Cushman, S. A., Lewis, J. S. & Landguth, E. L. Evaluating the intersection of a regional wildlife connectivity network with highways. Mov. Ecol. 1, 12 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  • 41.

    Moqanaki, E. M. & Cushman, S. A. All roads lead to Iran: predicting landscape connectivity of the last stronghold for the critically endangered Asiatic cheetah. Anim. Conserv. 20, 29–41 (2017).

    Article  Google Scholar 

  • 42.

    Khosravi, R., Hemami, M. & Cushman, S. A. Multispecies assessment of core areas and connectivity of desert carnivores in central Iran. Divers. Distrib. 24, 193–207 (2018).

    Article  Google Scholar 

  • 43.

    Shahnaseri, G. et al. Contrasting use of habitat, landscape elements, and corridors by grey wolf and golden jackal in central Iran. Landsc. Ecol. 34, 1263–1277 (2019).

    Article  Google Scholar 

  • 44.

    Cushman, S. A. & Landguth, E. L. Ecological associations, dispersal ability, and landscape connectivity in the northern Rocky Mountains. In Research Paper RMRS-RP-90. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. vol. 90, 21 p (2012).

  • 45.

    McGarigal, K. & Cushman, S. A. Comparative evaluation of experimental approaches to the study of habitat fragmentation effects. Ecol. Appl. 12, 335–345 (2002).

    Article  Google Scholar 

  • 46.

    Cozzi, G. et al. Anthropogenic food resources foster the coexistence of distinct life history strategies: year-round sedentary and migratory brown bears. J. Zool. 300, 142–150 (2016).

    Article  Google Scholar 

  • 47.

    McLellan, B. N., Proctor, M. F., Huber, D. & Michel, S. Ursus arctos (amended version of 2017 assessment). The IUCN Red List of Threatened Species 2017: e. T41688A121229971 (2017).

  • 48.

    Penteriani, V. & Melletti, M. Bears of the World: Ecology, Conservation and Management (Cambridge University Press, Cambridge, 2020).

    Google Scholar 

  • 49.

    Wolf, C. & Ripple, W. J. Range contractions of the world’s large carnivores. R. Soc. Open Sci. 4, 170052 (2017).

    PubMed  PubMed Central  Article  ADS  Google Scholar 

  • 50.

    Garshelis, D. & McLellan, B. Are bear subspecies a thing of the past?. Int. Bear News 20, 9–10 (2011).

    Google Scholar 

  • 51.

    Hajjar, I. The Syrian bear still lives in Syria. Int. Bear News 20, 7–11 (2011).

    Google Scholar 

  • 52.

    Calvignac, S., Hughes, S. & Hänni, C. Genetic diversity of endangered brown bear (Ursus arctos) populations at the crossroads of Europe, Asia and Africa. Divers. Distrib. 15, 742–750 (2009).

    Article  Google Scholar 

  • 53.

    Ansari, M. & Ghoddousi, A. Water availability limits brown bear distribution at the southern edge of its global range. Ursus 29, 13–24 (2018).

    Article  Google Scholar 

  • 54.

    Ashrafzadeh, M. R., Kaboli, M. & Naghavi, M. R. Mitochondrial DNA analysis of Iranian brown bears (Ursus arctos) reveals new phylogeographic lineage. Mamm. Biol. 81, 1–9 (2016).

    Article  Google Scholar 

  • 55.

    Gutleb, B. & Ziaie, H. On the distribution and status of the Brown Bear, Ursus arctos, and the Asiatic Black Bear, U. thibetanus, Iran. Zool. Middle East 18, 5–8 (1999).

    Article  Google Scholar 

  • 56.

    Moqanaki, E. M., Jiménez, J., Bensch, S. & López-Bao, J. V. Counting bears in the Iranian Caucasus: remarkable mismatch between scientifically-sound population estimates and perceptions. Biol. Conserv. 220, 182–191 (2018).

    Article  Google Scholar 

  • 57.

    Yusefi, G. H., Faizolahi, K., Darvish, J., Safi, K. & Brito, J. C. The species diversity, distribution, and conservation status of the terrestrial mammals of Iran. J. Mammal. 100, 55–71 (2019).

    Article  Google Scholar 

  • 58.

    Almasieh, K., Rouhi, H. & Kaboodvandpour, S. Habitat suitability and connectivity for the brown bear (Ursus arctos) along the Iran–Iraq border. Eur. J. Wildl. Res. 65, 57 (2019).

    Article  Google Scholar 

  • 59.

    Nezami, B. & Farhadinia, M. S. Litter sizes of brown bears in the Central Alborz Protected Area, Iran. Ursus 22, 167–171 (2011).

    Article  Google Scholar 

  • 60.

    Darvishsefat, A. A. Atlas of Protected Areas of Iran. (Ravi, 2006).

  • 61.

    Atzeni, L. et al. Meta-replication, sampling bias, and multi-scale model selection: a case study on snow leopard (Panthera uncia) in western China. Ecol. Evol. 10, 7686–7712 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  • 62.

    Ambarli, H., Erturk, A. & Soyumert, A. Current status, distribution, and conservation of brown bear (Ursidae) and wild canids (gray wolf, golden jackal, and red fox; Canidae) in Turkey (2016).

  • 63.

    Brown, J. L. SDM toolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol. Evol. 5, 694–700 (2014).

    Article  Google Scholar 

  • 64.

    Evans, J. S. & Oakleaf, J. Geomorphometry and gradient metrics toolbox (ArcGIS 10.0) (2012).

  • 65.

    Ghorbanian, A. et al. Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples. ISPRS J. Photogram. Remote Sens. 167, 276–288 (2020).

    Article  ADS  Google Scholar 

  • 66.

    Sanderson, E. W. et al. The human footprint and the last of the wild: the human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. Bioscience 52, 891–904 (2002).

    Article  Google Scholar 

  • 67.

    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  • 68.

    Jueterbock, A. ‘MaxentVariableSelection’vignette. (2015).

  • 69.

    R Development Core, team. A Language ans Environment for Statistical Computing. R Found Stat. Comput. Vienna Austria 2, (2018).

  • 70.

    Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K. & Toxopeus, A. G. Where is positional uncertainty a problem for species distribution modelling?. Ecography (Cop.) 37, 191–203 (2014).

    Article  Google Scholar 

  • 71.

    Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).

    Article  Google Scholar 

  • 72.

    Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).

    Google Scholar 

  • 73.

    Evans, J. S. & Cushman, S. A. Gradient modeling of conifer species using random forests. Landsc. Ecol. 24, 673–683 (2009).

    Article  Google Scholar 

  • 74.

    Wasserman, T. N., Cushman, S. A., Schwartz, M. K. & Wallin, D. O. Spatial scaling and multi-model inference in landscape genetics: Martes Americana in Northern Idaho. Landsc. Ecol. 25, 1601–1612 (2010).

    Article  Google Scholar 

  • 75.

    Cushman, S. A. & Lewis, J. S. Movement behavior explains genetic differentiation in American black bears. Landsc. Ecol. 25, 1613–1625 (2010).

    Article  Google Scholar 

  • 76.

    Cushman, S. A., Macdonald, E. A., Landguth, E. L., Malhi, Y. & Macdonald, D. W. Multiple-scale prediction of forest loss risk across Borneo. Landsc. Ecol. 32, 1581–1598 (2017).

    Article  Google Scholar 

  • 77.

    Zeller, K. A., McGarigal, K. & Whiteley, A. R. Estimating landscape resistance to movement: a review. Landsc. Ecol. 27, 777–797 (2012).

    Article  Google Scholar 

  • 78.

    Wan, H. Y., Cushman, S. A. & Ganey, J. L. Improving habitat and connectivity model predictions with multi-scale resource selection functions from two geographic areas. Landsc. Ecol. 34, 503–519 (2019).

    Article  Google Scholar 

  • 79.

    Landguth, E. L., Hand, B. K., Glassy, J., Cushman, S. A. & Sawaya, M. A. UNICOR: a species connectivity and corridor network simulator. Ecography (Cop.) 35, 9–14 (2012).

    Article  Google Scholar 

  • 80.

    Cushman, S. A., Landguth, E. L. & Flather, C. H. Evaluating population connectivity for species of conservation concern in the American Great Plains. Biodivers. Conserv. 22, 2583–2605 (2013).

    Article  Google Scholar 

  • 81.

    Kaszta, Ż, Cushman, S. A., Sillero-Zubiri, C., Wolff, E. & Marino, J. Where buffalo and cattle meet: modelling interspecific contact risk using cumulative resistant kernels. Ecography (Cop.) 41, 1616–1626 (2018).

    Article  Google Scholar 

  • 82.

    Støen, O.-G. Natal Dispersal and Social Organization in Brown Bears. (Norwegian University of Life Sciences, Department of Ecology and Natural, 2006).

  • 83.

    Saura, S. & Pascual-Hortal, L. A new habitat availability index to integrate connectivity in landscape conservation planning: comparison with existing indices and application to a case study. Landsc. Urban Plan. 83, 91–103 (2007).

    Article  Google Scholar 

  • 84.

    Saura, S. & Torné, J. Conefor Sensinode 2.2: a software package for quantifying the importance of habitat patches for landscape connectivity. Environ. Model. Softw. 24, 135–139 (2009).

    Article  Google Scholar 

  • 85.

    Avon, C. & Bergès, L. Prioritization of habitat patches for landscape connectivity conservation differs between least-cost and resistance distances. Landsc. Ecol. 31, 1551–1565 (2016).

    Article  Google Scholar 

  • 86.

    Ahmadi, M. et al. SPECIES OR SPACE: a combined gap analysis to guide management planning of conservation areas. Landsc. Ecol. 35, 1505–1517 (2020).

    Article  Google Scholar 

  • 87.

    Saura, S. & Rubio, L. A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography (Cop.) 33, 523–537 (2010).

    Google Scholar 

  • 88.

    Elliot, N. B., Cushman, S. A., Macdonald, D. W. & Loveridge, A. J. The devil is in the dispersers: predictions of landscape connectivity change with demography. J. Appl. Ecol. 51, 1169–1178 (2014).

    Article  Google Scholar 

  • 89.

    Noroozi, J., Akhani, H. & Breckle, S.-W. Biodiversity and phytogeography of the alpine flora of Iran. Biodivers. Conserv. 17, 493–521 (2008).

    Article  Google Scholar 

  • 90.

    Habibzadeh, N. & Ashrafzadeh, M. R. Habitat suitability and connectivity for an endangered brown bear population in the Iranian Caucasus. Wildl. Res. 45, 602–610 (2018).

    Article  Google Scholar 

  • 91.

    Ashrafzadeh, M.-R., Khosravi, R., Ahmadi, M. & Kaboli, M. Landscape heterogeneity and ecological niche isolation shape the distribution of spatial genetic variation in Iranian brown bears, Ursus arctos (Carnivora: Ursidae). Mamm. Biol. 93, 64–75 (2018).

    Article  Google Scholar 

  • 92.

    Ash, E., Cushman, S. A., Macdonald, D. W., Redford, T. & Kaszta, Ż. How important are resistance, dispersal ability, population density and mortality in temporally dynamic simulations of population connectivity? A case study of tigers in southeast Asia. Land 9, 415 (2020).

    Article  Google Scholar 

  • 93.

    Cushman, S. A. et al. Biological corridors and connectivity [Chapter 21]. In Key Topics in Conservation Biology 2 (eds Macdonald, D. W. & Willis, K. J.) 384–404 (Wiley, Hoboken, 2013).

    Google Scholar 

  • 94.

    Ghoddousi, A. Habitat suitability modelling of the Brown bear Ursus arctos in Croatia and Slovenia using telemetry data (2010).

  • 95.

    Steyaert, S. M. J. G. et al. Ecological implications from spatial patterns in human-caused brown bear mortality. Wildl. Biol. 22, 144–152 (2016).

    Article  Google Scholar 

  • 96.

    Güthlin, D. et al. Estimating habitat suitability and potential population size for brown bears in the Eastern Alps. Biol. Conserv. 144, 1733–1741 (2011).

    Article  Google Scholar 

  • 97.

    Penteriani, V. et al. Evolutionary and ecological traps for brown bears Ursus arctos in human-modified landscapes. Mamm. Rev. 48, 180–193 (2018).

    Article  Google Scholar 

  • 98.

    Zarzo-Arias, A. et al. Identifying potential areas of expansion for the endangered brown bear (Ursus arctos) population in the Cantabrian Mountains (NW Spain). PLoS ONE 14, e0209972 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 99.

    Morales-González, A., Ruiz-Villar, H., Ordiz, A. & Penteriani, V. Large carnivores living alongside humans: brown bears in human-modified landscapes. Glob. Ecol. Conserv. 22, e00937 (2020).

    Article  Google Scholar 

  • 100.

    Fedorca, A. et al. Inferring fine-scale spatial structure of the brown bear (Ursus arctos) population in the Carpathians prior to infrastructure development. Sci. Rep. 9, 1–12 (2019).

    Article  CAS  Google Scholar 

  • 101.

    Liu, C., Newell, G., White, M. & Bennett, A. F. Identifying wildlife corridors for the restoration of regional habitat connectivity: a multispecies approach and comparison of resistance surfaces. PLoS ONE 13, e0206071 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 102.

    Macdonald, D. W. et al. Predicting biodiversity richness in rapidly changing landscapes: Climate, low human pressure or protection as salvation?. Biodivers. Conserv. 29, 4035–4057 (2020).

    Article  Google Scholar 

  • 103.

    Herrero, S., Smith, T., DeBruyn, T. D., Gunther, K. & Matt, C. A. From the field: brown bear habituation to people—safety, risks, and benefits. Wildl. Soc. Bull. 33, 362–373 (2005).

    Article  Google Scholar 

  • 104.

    Skuban, M. et al. Effects of roads on brown bear movements and mortality in Slovakia. Eur. J. Wildl. Res. 63, 82 (2017).

    Article  Google Scholar 

  • 105.

    Findo, S., Skuban, M., Kajba, M., Chalmers, J. & Kalaš, M. Identifying attributes associated with brown bear (Ursus arctos) road-crossing and roadkill sites. Can. J. Zool. 97, 156–164 (2019).

    Article  Google Scholar 

  • 106.

    Watson, J. E. M. et al. Persistent disparities between recent rates of habitat conversion and protection and implications for future global conservation targets. Conserv. Lett. 9, 413–421 (2016).

    Article  Google Scholar 

  • 107.

    Boitani, L., Ciucci, P., Corsi, F. & Dupre, E. Potential range and corridors for brown bears in the Eastern Alps. Italy. Ursus 11, 123–130 (1999).

    Google Scholar 

  • 108.

    Cushman, S. A., McKelvey, K. S., Hayden, J. & Schwartz, M. K. Gene flow in complex landscapes: testing multiple hypotheses with causal modeling. Am. Nat. 168, 486–499 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  • 109.

    Mohammadi, A. et al. Road expansion: a challenge to conservation of mammals, with particular emphasis on the endangered Asiatic cheetah in Iran. J. Nat. Conserv. 43, 8–18 (2018).

    Article  Google Scholar 


  • Source: Ecology - nature.com

    Stoichiometric niche, nutrient partitioning and resource allocation in a solitary bee are sex-specific and phosphorous is allocated mainly to the cocoon

    Professor Emeritus Peter Eagleson, pioneering hydrologist, dies at 92