CoChat
Sign Up
Cited by 30

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Uncertainties in the identification of potential dispersal corridors: The importance of behaviour, sex, and algorithm

Maiorano, Luigi, Boitani, Luigi, Chiaverini, Luca, Ciucci, Paolo·2017·Basic and Applied Ecology
DOI 10.1016/j.baae.2017.02.005
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1016/j.baae.2017.02.005

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Circuit theory is particularly appropriate when the assumption of moving individuals having limited knowledge of the surrounding landscape is met.

    “Circuit theory is particularly appropriate when the assumption of moving individuals having limited knowledge of the surrounding landscape is met (McClure et al. 2016; Keeley et al. 2017; Maiorano et al. 2017).”

    From Circuit‐theory applications to connectivity science and conservation (2019) · cites this paper as Maiorano et al. 2017

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 47

  1. Abrahms, 2015, Lessons from integrating behaviour and resource selection: Activity-specific responses of African wild dogs to roads, Animal Conservation, 19, 247, 10.1111/acv.12235 · DOI
  2. Abrahms, 2017, Does wildlife resource selection accurately inform corridor conservation?, Journal of Applied Ecology, 54, 412, 10.1111/1365-2664.12714 · DOI
  3. Adriaensen, 2003, The application of ‘least-cost’ modelling as a functional landscape model, Landscape and Urban Planning, 64, 233, 10.1016/S0169-2046(02)00242-6 · DOI · Paper page
  4. Allen, 2016, An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis), PeerJ, 4, e2001, 10.7717/peerj.2001 · DOI
  5. Araujo, 2007, Ensemble forecasting of species distributions, Trends in Ecology and Evolution, 22, 42, 10.1016/j.tree.2006.09.010 · DOI · Paper page
  6. Boitani, 2007, Ecological networks as conceptual frameworks or operational tools in conservation, Conservation Biology, 21, 1414, 10.1111/j.1523-1739.2007.00828.x · DOI
  7. Chetkiewicz, 2009, Use of resource selection functions to identify conservation corridors, Journal of Applied Ecology, 46, 1036, 10.1111/j.1365-2664.2009.01686.x · DOI
  8. Chetkiewicz, 2006, Corridors for conservation: Integrating pattern and process, Annual Review of Ecology, Evolution, and Systematics, 37, 317, 10.1146/annurev.ecolsys.37.091305.110050 · DOI
  9. Ciucci, 2008, The Apennine brown bear: A critical review of its status and conservation problems, Ursus, 19, 130, 10.2192/07PER012.1 · DOI
  10. Cushman, 2010, Movement behaviour explains genetic differentiation in American black bears, Landscape Ecology, 25, 1613, 10.1007/s10980-010-9534-6 · DOI
  11. Driezen, 2007, Evaluating least-cost model predictions with empirical dispersal data: A case-study using radio-tracking data of hedgehogs, Ecological Modelling, 209, 314, 10.1016/j.ecolmodel.2007.07.002 · DOI
  12. Elliot, 2014, The devil is in the disperser: Predictions of landscape connectivity change with demography, Journal of Applied Ecology, 51, 1169, 10.1111/1365-2664.12282 · DOI · Paper page
  13. Fahrig, 2003, Effects of habitat fragmentation on biodiversity, Annual Review of Ecology, Evolution, and Systematics, 34, 487, 10.1146/annurev.ecolsys.34.011802.132419 · DOI · Paper page
  14. Falcucci, 2007, Changes in land-use/land-cover patterns in Italy and their implications for biodiversity conservation, Landscape Ecology, 22, 617, 10.1007/s10980-006-9056-4 · DOI
  15. Falcucci, 2008, Land-cover change and the future of the Apennine brown bear: A perspective from the past, Journal of Mammalogy, 89, 1502, 10.1644/07-MAMM-A-229.1 · DOI
  16. Falcucci, 2009, Land-cover change and the future of the Apennine brown bear: A perspective from the past, Journal of Mammalogy, 89, 1502, 10.1644/07-MAMM-A-229.1 · DOI
  17. Forester, 2007, State–space models link elk movement patterns to landscape characteristics in Yellowstone National Park, Ecological Monographs, 77, 285, 10.1890/06-0534 · DOI
  18. Gilbert-Norton, 2009, A meta-analytic review of corridor effectiveness, Conservation Biology, 24, 660, 10.1111/j.1523-1739.2010.01450.x · DOI
  19. Keeley, 2016, Estimating landscape resistance from habitat suitability: Effects of data source and nonlinearities, Landscape Ecology, 31, 2151, 10.1007/s10980-016-0387-5 · DOI · Paper page
  20. LaPoint, 2013, Animal behaviour, cost-base corridor models, and real corridors, Landscape Ecology, 28, 1615, 10.1007/s10980-013-9910-0 · DOI · Paper page
  21. Maiorano, 2006, Gap analysis of terrestrial vertebrate in Italy: Priorities for conservation planning in a human dominated landscape, Biological Conservation, 133, 455, 10.1016/j.biocon.2006.07.015 · DOI
  22. Maiorano, 2007, Contribution of the Natura 2000 network to biodiversity conservation in Italy, Conservation Biology, 21, 1433, 10.1111/j.1523-1739.2007.00831.x · DOI
  23. Maiorano, 2015, Modeling the distribution of Apennine brown bears during hyperphagia to reduce the impact of wild boar hunting, European Journal of Wildlife Research, 61, 241, 10.1007/s10344-014-0894-0 · DOI
  24. Mateo-Sánchez, 2015, A comparative framework to infer landscape effects on population genetic structure: Are habitat suitability models effective in explaining gene flow?, Landscape Ecology, 30, 1405, 10.1007/s10980-015-0194-4 · DOI
  25. McClure, 2016, Connecting models to movements: Testing connectivity model predictions against empirical migration and dispersal data, Landscape Ecology, 31, 1419, 10.1007/s10980-016-0347-0 · DOI · Paper page
  26. McGuire, 2016, Achieving climate connectivity in a fragmented landscape, Proceedings of the National Academy of Sciences USA, 113, 7195, 10.1073/pnas.1602817113 · DOI
  27. Morales, 2004, Extracting more out of relocation data: Building movement models as mixtures of random walks, Ecology, 85, 2436, 10.1890/03-0269 · DOI
  28. Nams, 2006, Improving accuracy and precision in estimating fractal dimension of animal movement paths, Acta Biotheoretica, 54, 1, 10.1007/s10441-006-5954-8 · DOI
  29. Panzacchi, 2016, Prediting the continuum between corridors and barriers to animal movements using step selection functions and randomised shortest paths, Journal of Animal Ecology, 85, 32, 10.1111/1365-2656.12386 · DOI
  30. Poor, 2012, Comparing habitat suitability and connectivity modelling methods for conserving pronghorn migrations, PLoS One, 7, e49390, 10.1371/journal.pone.0049390 · DOI · Paper page
  31. Posillico, 2004, A habitat model for brown bear conservation and land use plan- ning in the central Apennines, Biological Conservation, 118, 141, 10.1016/j.biocon.2003.07.017 · DOI
  32. Potts, 2014, Predicting local and non-local effects of resources on animal space use using a mechanistic step-selection models, Methods in Ecology and Evolution, 5, 253, 10.1111/2041-210X.12150 · DOI
  33. Rode, 2006, Sexual dimorphism, reproductive strategy, and human activities determine resource use by brown bears, Ecology, 87, 2636, 10.1890/0012-9658(2006)87[2636:SDRSAH]2.0.CO;2 · DOI
  34. Rudnick, 2012, The role of landscape connectivity in planning and implementing conservation and restoration priorities, Issues in Ecology, 16, 1
  35. Saura, 2014, Stepping stones are crucial for species’ long-distance dispersal and range expansion through habitat networks, Journal of Applied Ecology, 41, 171, 10.1111/1365-2664.12179 · DOI · Paper page
  36. Schloss, 2012, Dispersal will limit ability of mammals to track climate change in the Western Hemisphere, Proceedings of the National Academy of Sciences of the USA, 109, 8606, 10.1073/pnas.1116791109 · DOI
  37. Squires, 2013, Combining resource selection and movement behaviour to predict corridor for Canada lynx at their southern range periphery, Biological Conservation, 157, 187, 10.1016/j.biocon.2012.07.018 · DOI
  38. Swets, 1988, Measuring the accuracy of diagnostic systems, Science, 240, 1285, 10.1126/science.3287615 · DOI · Paper page
  39. Thuiller, 2009, BIOMOD—a platform for ensemble forecasting of species distributions, Ecography, 32, 369, 10.1111/j.1600-0587.2008.05742.x · DOI
  40. Thurfjell, 2014, Applications of step-selection functions in ecology and conservation, Movement Ecology, 2, 4, 10.1186/2051-3933-2-4 · DOI
  41. Tsoar, 2011, Large-scale navigational map in a mammal, Proceedings of the National Academy of Sciences USA, 108, E718, 10.1073/pnas.1107365108 · DOI
  42. Vogt, 2009, Mapping functional connectivity, Ecological Indicators, 9, 64, 10.1016/j.ecolind.2008.01.011 · DOI
  43. Zedrosser, 2007, Should I stay or should I go? Natal dispersal in the brown bear, Animal Behaviour, 74, 369, 10.1016/j.anbehav.2006.09.015 · DOI
  44. Zeller, 2014, Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioural state: Pumas as a case study, Landscape Ecology, 29, 541, 10.1007/s10980-014-9991-4 · DOI · Paper page
  45. Zeller, 2016, Using step and path selection functions for estimating resistance to movement: Pumas as a case study, Landscape Ecology, 31, 1319, 10.1007/s10980-015-0301-6 · DOI
  46. Zeller, 2012, Estimating landscape resistance to movement: A review, Landscape Ecology, 27, 777, 10.1007/s10980-012-9737-0 · DOI · Paper page
  47. Ziólkowska, 2016, Assessing differences in connectivity based on habitat versus movements models for brown bears in the Carpathian, Landscape Ecology, 31, 1863, 10.1007/s10980-016-0368-8 · DOI

Cited by

Sorted by citations

Metadata

Authors
Maiorano, L., Boitani, L., Chiaverini, L., & Ciucci, P.
Venue
Basic and Applied Ecology
Publisher
Elsevier BV
Published
2017-06
Volume
21
Pages
66-75
ISSN
1439-1791
DOI
10.1016/j.baae.2017.02.005
Cited by
30
References
3
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review