The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Connectivity metrics for conservation planning and monitoring
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The 0-100 range represents the most efficient and most likely most frequented routes between sites, suggesting direct and recurrent routes in the logic of Neanderthal mobility.
“These represent the most efficient and, most likely, the most frequented routes between sites, suggesting direct and recurrent routes in the logic of Neanderthal mobility [22,51].”
From Tracing neanderthal mobility through the romanian carpathians: a GIS-based least-cost connectivity model (2025) · cites this paper as [51]
Section 3.1 describes resistance-based metrics that calculate cost-weighted paths between habitat patches, supporting the general idea of modeling efficient routes. It does not define a 0–100 range or establish that such routes were the most frequented, direct and recurrent routes of Neanderthal mobility. Page numbers are not available in our copy. (LLM, conf=0.83)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062
USING CIRCUIT THEORY TO MODEL CONNECTIVITY IN ECOLOGY, EVOLUTION, AND CONSERVATION
McRae, B. H., Dickson, B. G., Keitt, T. H., & Shah, V. B. (2008) · Ecology · doi:10.1890/07-1861.1 · Cited by 2,244
Pelletier, D., Clark, M., Anderson, M. G., Rayfield, B., Wulder, M. A., & Cardille, J. A. (2014) · PLOS One · doi:10.1371/journal.pone.0084135 · Cited by 158
Flagged first, then by citations
Research works printed but not linked: 69
- Albert, 2017, Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change, Conserv. Biol., 31, 1383, 10.1111/cobi.12943 · DOI · Paper page
- Beier, 1995, Dispersal of juvenile cougars in fragmented habitat, J. Wildl. Manag., 59, 228, 10.2307/3808935 · DOI
- Beier, 2019, A rule of thumb for widths of conservation corridors, Conserv. Biol., 33, 976, 10.1111/cobi.13256 · DOI
- Beier, 2012, Desperately seeking stable 50-year-old landscapes with patches and long, wide corridors, PLoS Biol., 10, 10.1371/journal.pbio.1001253 · DOI
- Beier, 2008, Forks in the road: choices in procedures for designing wildland linkages, Conserv. Biol., 22, 836, 10.1111/j.1523-1739.2008.00942.x · DOI · Paper page
- Bélisle, 2005, Measuring landscape connectivity: the challenge of behavioral landscape ecology, Ecology, 86, 1988, 10.1890/04-0923 · DOI
- Belote, 2020, A framework for developing connectivity targets and indicators to guide global conservation efforts, BioScience, 70, 122, 10.1093/biosci/biz148 · DOI
- Berger, 2006, Connecting the dots: an invariant migration corridor links the Holocene to the present, Biol. Lett., 2, 528, 10.1098/rsbl.2006.0508 · DOI
- Bunn, 2000, Landscape connectivity: a conservation application of graph theory, J. Environ. Manag., 59, 265, 10.1006/jema.2000.0373 · DOI
- Calabrese, 2004, A comparison-shopper’s guide to connectivity metrics, Front. Ecol. Environ., 2, 529, 10.1890/1540-9295(2004)002[0529:ACGTCM]2.0.CO;2 · DOI · Paper page
- Conde, 2010, Sex matters: modeling male and female habitat differences for jaguar conservation, Biol. Conserv., 143, 1980, 10.1016/j.biocon.2010.04.049 · DOI
- Damschen, 2019, Ongoing accumulation of plant diversity through habitat connectivity in an 18-year experiment, Science, 6460, 1478, 10.1126/science.aax8992 · DOI
- Dickson, 2016, Informing strategic efforts to expand and connect protected areas using a model of ecological flow, with application to the western United States, Conserv. Lett., 10, 564, 10.1111/conl.12322 · DOI
- Dixon, 2006, Effectiveness of a regional corridor in connecting two Florida black bear populations, Conserv. Biol., 10, 155, 10.1111/j.1523-1739.2005.00292.x · DOI
- Elliot, 2014, The devil is in the dispersers: predictions of landscape connectivity change with demography, J. Appl. Ecol., 51, 1169, 10.1111/1365-2664.12282 · DOI · Paper page
- Fahrig, 2002, Effect of habitat fragmentation on the extinction threshold: a synthesis, Ecol. Appl., 12, 346
- Fischer, 2007, Landscape modification and habitat fragmentation: a synthesis, Glob. Ecol. Biogeogr., 16, 265, 10.1111/j.1466-8238.2007.00287.x · DOI
- Gao, 2013, Identifying functionally connected habitat compartments with a novel regionalization technique, Landsc. Ecol., 28, 1949, 10.1007/s10980-013-9938-1 · DOI
- Greenwald, 2009, Efficacy of land-cover models in predicting isolation of marbled salamander populations in a fragmented landscape, Conserv. Biol., 23, 1232, 10.1111/j.1523-1739.2009.01204.x · DOI
- Gregory, 2014, Response variables for evaluation of the effectiveness of conservation corridors, Conserv. Biol., 28, 689, 10.1111/cobi.12252 · DOI
- Gurrutxaga, 2011, Key connectors in protected forest area networks and the impact of highways: a transnational case study from the Cantabrian Range to the Western Alps (SW Europe), Landsc. Urban Plan., 101, 310, 10.1016/j.landurbplan.2011.02.036 · DOI
- Hanski, 1994, A practical model of metapopulation dynamics, J. Anim. Ecol., 151, 10.2307/5591 · DOI
- Heller, 2009, Biodiversity management in the face of climate change: a review of 22 years of recommendations, Biol. Conserv., 142, 14, 10.1016/j.biocon.2008.10.006 · DOI · Paper page
- Horskins, 2006, Corridors and connectivity: when use and function do not equate, Landsc. Ecol., 21, 641, 10.1007/s10980-005-5203-6 · DOI
- Hou, 2017, A simplified econet model for mapping and evaluating structural connectivity with particular attention of ecotones, small habitats, and barriers, Landsc. Urban Plan., 160, 28, 10.1016/j.landurbplan.2016.11.008 · DOI
- Inglis, 1992, Comments on some designs proposed for experiments on the biological importance of corridors, Conserv. Biol., 6, 581, 10.1046/j.1523-1739.1992.06040581.x · DOI
- Jaeger, 2000, Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation, Landsc. Ecol., 15, 115, 10.1023/A:1008129329289 · DOI
- Jantz, 2008, Using widely available geospatial data sets to assess the influence of roads and buffers on habitat core areas and connectivity, Nat. Areas J., 28, 261, 10.3375/0885-8608(2008)28[261:UWAGDS]2.0.CO;2 · DOI
- Jordán, 2003, Characterizing the importance of habitat patches and corridors in maintaining the landscape connectivity of a Pholidoptera transsylvanica (Orthoptera) metapopulation, Landsc. Ecol., 18, 83, 10.1023/A:1022958003528 · DOI
- Kays, 2015, Terrestrial animal tracking as an eye on life and planet, Science, 348, 10.1126/science.aaa2478 · DOI · Paper page
- Keeley, 2017, Habitat suitability is a poor proxy for landscape connectivity during dispersal and mating movements, Landsc. Urban Plan., 161, 90, 10.1016/j.landurbplan.2017.01.007 · DOI · Paper page
- Keeley, 2018, New concepts, models, and assessments of climate-wise connectivity, Environ. Res. Lett., 13, 073002, 10.1088/1748-9326/aacb85 · DOI
- Keitt, 1997, Detecting critical scales in fragmented landscapes, Conserv. Ecol., 1
- Kindlmann, 2008, Connectivity measures: a review, Landsc. Ecol., 23, 879
- King, 2002, Dispersal success on spatially structured landscapes: when do spatial pattern and dispersal behavior really matter?, Ecol. Model., 147, 23, 10.1016/S0304-3800(01)00400-8 · DOI
- Krosby, 2010, Ecological connectivity for a changing climate, Conserv. Biol., 24, 1686, 10.1111/j.1523-1739.2010.01585.x · DOI · Paper page
- Krosby, 2015, Focal species and landscape “naturalness” corridor models offer complementary approaches for connectivity conservation planning, Landsc. Ecol., 30, 2121, 10.1007/s10980-015-0235-z · DOI
- Lidicker, 2008, Levels of organization in biology: on the nature and nomenclature of ecology’s fourth level, Biol. Rev., 83, 71, 10.1111/j.1469-185X.2007.00032.x · DOI
- Locke, 2019, Three global conditions for biodiversity conservation and sustainable use: an implementation framework, Natl. Sci. Rev., 10.1093/nsr/nwz136 · DOI
- Marulli, 2005, A GIS methodology for assessing ecological connectivity: application to the Barcelona Metropolitan Area, Landsc. Urban Plan., 71, 243, 10.1016/S0169-2046(04)00079-9 · DOI
- Mawdsley, 2009, A review of climate-change adaptation strategies for wildlife management and biodiversity conservation, Conserv. Biol., 23, 1080, 10.1111/j.1523-1739.2009.01264.x · DOI
- McRae, 2007, Circuit theory predicts gene flow in plant and animal populations, Proc. Natl. Acad. Sci., 104, 19885, 10.1073/pnas.0706568104 · DOI · Paper page
- Mech, 2001, Evaluating the effectiveness of corridors: a genetic approach, Conserv. Biol., 5, 467, 10.1046/j.1523-1739.2001.015002467.x · DOI
- Metzger, 1997, The structural connectivity threshold: an hypothesis in conservation biology at the landscape scale, Acta Oecol., 18, 1, 10.1016/S1146-609X(97)80075-6 · DOI
- Minor, 2008, A graph-theory framework for evaluating landscape connectivity and conservation planning, Conserv. Biol., 22, 297, 10.1111/j.1523-1739.2007.00871.x · DOI
- Moilanen, 2001, On the use of connectivity measures in spatial ecology, Oikos, 95, 147, 10.1034/j.1600-0706.2001.950116.x · DOI
- Moilanen, 2002, Simple connectivity measures in spatial ecology, Ecology, 83, 1131, 10.1890/0012-9658(2002)083[1131:SCMISE]2.0.CO;2 · DOI · Paper page
- Morin, 2017, Model-based estimators of density and connectivity to inform conservation of spatially structured populations, Ecosphere, 8, 10.1002/ecs2.1623 · DOI
- Pascual-Hortal, 2006, Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation, Landsc. Ecol., 21, 959, 10.1007/s10980-006-0013-z · DOI · Paper page
- Prugh, 2009, An evaluation of patch connectivity measures, Ecol. Appl., 19, 1300, 10.1890/08-1524.1 · DOI
- Rae, 2007, Implications of error and uncertainty for an environmental planning scenario: a sensitivity analysis of GIS-based variables in a reserve design exercise, Landsc. Urban Plan., 79, 210, 10.1016/j.landurbplan.2006.01.001 · DOI
- Ricotta, 2000, Quantifying the network connectivity of landscape mosaics: a graph-theoretical approach, Commun. Ecol., 1, 89, 10.1556/ComEc.1.2000.1.12 · DOI
- Riley, 2006, A southern California freeway is a physical and social barrier to gene flow in carnivores, Mol. Ecol., 15, 1733, 10.1111/j.1365-294X.2006.02907.x · DOI
- Saura, 2007, 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, 10.1016/j.landurbplan.2007.03.005 · DOI
- Saura, 2010, A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape, Ecography, 33, 523, 10.1111/j.1600-0587.2009.05760.x · DOI · Paper page
- Saura, 2011, Network analysis to assess landscape connectivity trends: application to European forests (1990–2000), Ecol. Indic., 11, 407, 10.1016/j.ecolind.2010.06.011 · DOI
- Saura, 2017, Protected areas in the world’s ecoregions: how well connected are they?, Ecol. Indic., 76, 144, 10.1016/j.ecolind.2016.12.047 · DOI
- Saura, 2018, Protected area connectivity: shortfalls in global targets and country-level priorities, Biol. Conserv., 219, 53, 10.1016/j.biocon.2017.12.020 · DOI
- Schumaker, 1996, Using landscape indices to predict habitat connectivity, Ecology, 77, 1210, 10.2307/2265590 · DOI · Paper page
- Sharma, 2013, Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India, Proc. R. Soc. B, 280, 10.1098/rspb.2013.1506 · DOI
- Storfer, 2007, Putting the ‘landscape’ in landscape genetics, Heredity, 98, 128, 10.1038/sj.hdy.6800917 · DOI
- Taylor, 1993, Connectivity is a vital element of landscape structure, Oikos, 571, 10.2307/3544927 · DOI · Paper page
- Theobald, 2013, A general model to quantify ecological integrity for landscape assessments and US application, Landsc. Ecol., 28, 1859, 10.1007/s10980-013-9941-6 · DOI
- Tischendorf, 2000, On the usage and measurement of landscape connectivity, Oikos, 90, 7, 10.1034/j.1600-0706.2000.900102.x · DOI
- Urban, 2001, Landscape connectivity: a graph-theoretic perspective, Ecology, 82, 1205, 10.1890/0012-9658(2001)082[1205:LCAGTP]2.0.CO;2 · DOI
- Watling, 2011, Meta-analysis reveals the importance of matrix composition for animals in fragmented habitat, Glob. Ecol. Biogeogr., 20, 209, 10.1111/j.1466-8238.2010.00586.x · DOI
- Watts, 2010, Developing a functional connectivity indicator to detect change in fragmented landscapes, Ecol. Indic., 10, 552, 10.1016/j.ecolind.2009.07.009 · DOI
- Zeller, 2012, Estimating landscape resistance to movement: a review, Landsc. Ecol., 27, 777, 10.1007/s10980-012-9737-0 · DOI · Paper page
- Zeller, 2016, Using step and path selection functions for estimating resistance to movement: pumas as a case study, Landsc. Ecol., 31, 1319, 10.1007/s10980-015-0301-6 · DOI
Cited by
Sorted by citations
Murătoreanu, G., & Cosac, M. (2025) · PLOS One · doi:10.1371/journal.pone.0334149 · Cited by 1
Metadata
- Authors
- Keeley, A. T. H., Beier, P., & Jenness, J. S.
- Venue
- Biological Conservation
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 255
- Pages
- 109008
- ISSN
- 0006-3207
- Cited by
- 243
- References
- 3
- Language
- en
- Licence
- Funders
- Yellowstone to Yukon Conservation Initiative
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