2018
DOI: 10.1007/s10980-018-0611-6
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Connectivity analysis as a tool for assessing restoration success

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Cited by 27 publications
(19 citation statements)
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“…In this model, nodes are represented by habitat fragments that are connected by links, allowing species to disperse between fragments [19,20]. In agroforestry landscapes with productive areas, the results of this model can be used for decision making and planning of conservation and restoration areas [21,22].…”
Section: Introductionmentioning
confidence: 99%
“…In this model, nodes are represented by habitat fragments that are connected by links, allowing species to disperse between fragments [19,20]. In agroforestry landscapes with productive areas, the results of this model can be used for decision making and planning of conservation and restoration areas [21,22].…”
Section: Introductionmentioning
confidence: 99%
“…Maintaining or restoring landscape connectivity is an important component of conservation [ 15 , 19 ]. We demonstrated with the use of dynamic state variable models that the state of the animal, the foraging strategy (e.g., energy maximization or foraging time minimization to avoid predation as reflected in the fitness function), and the difference in patch quality all had a strong influence on the motivation to move to a new patch, which we considered reflected functional connectivity.…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, Belisle (2005) advocated for an assessment of functional connectivity that connects a behavioural understanding of why animals are motivated to move to a new patch along with the degree to which landscapes both facilitate or impede animal movement among resource patches [ 6 8 ]. By differentially distributing individuals on the landscape functional connectivity directly influences population growth and trophic dynamics [ 9 13 ], and is critical for conservation and management of animal populations [ 14 – 19 ]. The motivation to move among patches comes in the form of trade-offs between rewards, such as gaining access to forage resources or mates and avoiding the risks of predation or the uncertainty in future reward.…”
Section: Introductionmentioning
confidence: 99%
“…Case studies in the Yellow River Delta showed that the depth of a tidal creek had a strong correlation with the density (P = 0.04; R 2 = 0.25 ) and height (P = 0.01; R 2 = 0.40 ) of P. australis (Wu et al, 2020). The parameters of tidal creeks were also linked to the terrain-based structural and dynamic hydrological connectivity (Dawidek and Ferencz, 2016;Volk et al, 2018) on the horizontal direction. Besides, the distribution of plant species and communities are mainly dependent on soil salinity (Cui et al, 2008;Cui et al, 2010;Meng et al, 2016).…”
Section: Influence Of Environment Factors On Plantsmentioning
confidence: 97%