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dc.contributor.authorPadilla, Benjamin Juan
dc.contributor.authorSutherland, Chris
dc.date.accessioned2021-11-22T11:30:13Z
dc.date.available2021-11-22T11:30:13Z
dc.date.issued2021-11-18
dc.identifier276762328
dc.identifier2b677c63-8fb0-478c-b8c2-a877f39fd86c
dc.identifier85119608295
dc.identifier000755319200008
dc.identifier.citationPadilla , B J & Sutherland , C 2021 , ' Defining dual-axis landscape gradients of human influence for studying ecological processes ' , PLoS ONE , vol. 16 , no. 11 , e0252364 . https://doi.org/10.1371/journal.pone.0252364en
dc.identifier.issn1932-6203
dc.identifier.otherJisc: 68401f711a3248dc94a5d9eb8e3393c3
dc.identifier.otherpublisher-id: pone-d-21-15482
dc.identifier.otherORCID: /0000-0003-2073-1751/work/103511206
dc.identifier.urihttps://hdl.handle.net/10023/24376
dc.description.abstractEcological processes are strongly shaped by human landscape modification, and understanding the reciprocal relationship between ecosystems and modified landscapes is critical for informed conservation. Single axis measures of spatial heterogeneity proliferate in the contemporary gradient ecology literature, though they are unlikely to capture the complexity of ecological responses. Here, we develop a standardized approach for defining multi-dimensional gradients of human influence in heterogeneous landscapes and demonstrate this approach to analyze landscape characteristics of ten ecologically distinct US cities. Using occupancy data of a common human-adaptive songbird collected in each of the cities, we then use our dual-axis gradients to evaluate the utility of our approach. Spatial analysis of landscapes surrounding ten US cities revealed two important axes of variation that are intuitively consistent with the characteristics of multi-use landscapes, but are often confounded in single axis gradients. These were, a hard-to-soft gradient, representing transition from developed areas to non-structural soft areas; and brown-to-green, differentiating between two dominant types of soft landscapes: agriculture (brown) and natural areas (green). Analysis of American robin occurrence data demonstrated that occupancy responds to both hard-to-soft (decreasing with development intensity) and brown-to-green gradient (increasing with more natural area). Overall, our results reveal striking consistency in the dominant sources of variation across ten geographically distinct cities and suggests that our approach advances how we relate variation in ecological responses to human influence. Our case study demonstrates this: robins show a remarkably consistent response to a gradient differentiating agricultural and natural areas, but city-specific responses to the more traditional gradient of development intensity, which would be overlooked with a single gradient approach. Managing ecological communities in human dominated landscapes is extremely challenging due to a lack of standardized approaches and a general understanding of how socio-ecological systems function, and our approach offers promising solutions.
dc.format.extent17
dc.format.extent1332040
dc.language.isoeng
dc.relation.ispartofPLoS ONEen
dc.subjectHA Statisticsen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subject.lccHAen
dc.subject.lccQH301en
dc.titleDefining dual-axis landscape gradients of human influence for studying ecological processesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doi10.1371/journal.pone.0252364
dc.description.statusPeer revieweden


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