2012
DOI: 10.2981/11-073
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Defining spatial priorities for capercaillieTetrao urogalluslekking landscape conservation in south‐central Finland

Abstract: SummaryAnimals' avoidance of humans or human activities can have several adverse effects on their distribution and abundance, and a frequent tool used by conservation managers to avoid such effects is to designate 'buffer zones' (or set-back distances or protection zones) around centres of animals' distribution within which human activity is restricted.A common method used to prescribe buffer zones involves one or two measures of disturbance distance: 'alert distance' (AD), the distance between the disturbance… Show more

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Cited by 18 publications
(15 citation statements)
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“…To inform management of populations of these focal species in national parks, it is necessary to make accurate predictions while simultaneously achieving a resolution precise enough for management planning. The resolution of SDMs should ideally be determined by the size of forest stands in the region, the scale of habitat selection for the target organism, and the scale of management units (Sirkiä et al 2012, Aguirre-Gutiérrez et al 2013, Pradervand et al 2014). In practice, most SDMs are constructed to reflect the resolution of available data layers (predictions can only be as fine as the coarsest layer of the input data) or limited computing power (Franklin 2009).…”
Section: Modeling Species Associated With Wet Forest Habitatsmentioning
confidence: 99%
“…To inform management of populations of these focal species in national parks, it is necessary to make accurate predictions while simultaneously achieving a resolution precise enough for management planning. The resolution of SDMs should ideally be determined by the size of forest stands in the region, the scale of habitat selection for the target organism, and the scale of management units (Sirkiä et al 2012, Aguirre-Gutiérrez et al 2013, Pradervand et al 2014). In practice, most SDMs are constructed to reflect the resolution of available data layers (predictions can only be as fine as the coarsest layer of the input data) or limited computing power (Franklin 2009).…”
Section: Modeling Species Associated With Wet Forest Habitatsmentioning
confidence: 99%
“…The areas shifted between the wood availability categories were selected based on conservation value predicted for each NFI plot as a function of site characteristics and species-specific volume and mean diameter of the growing stock . Similar proxy values have been used for conservation (Lehtomäki et al 2009;Arponen et al 2012;Sirkiä et al 2012) or management prioritization (Vauhkonen and Ruotsalainen 2017), when plant mapping data have not been available for more detailed analyses. The application of the functions yielded the highest conservation values for forests with large trees, more than one species, and high site fertility.…”
Section: Using Nfi Data To Simulate Transitions Between Wood Availabimentioning
confidence: 99%
“…[ 62 , 73 , 74 ]). In Finland, the MS-NFI is being used mostly for regional level forestry planning, but it has also been used for large-scale conservation prioritization studies [ 13 , 74 , 75 ]. The MS-NFI data has been publicly available since late 2012, the thematic maps can be viewed through a web portal and the rasters can be downloaded through a file service [ 76 ].…”
Section: Methodsmentioning
confidence: 99%
“…We transformed the average diameter of the growing stock per tree species group by a sigmoidal benefit function (see S1 Appendix and S1 Fig ) and then multiplied the transformed value by the volume of the growing stock. A similar approach has been used earlier in large-scale conservation prioritizations [ 13 , 74 ] and in species-oriented prioritization [ 75 ].…”
Section: Methodsmentioning
confidence: 99%
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