Examining local and regional ecological connectivity throughout North America

Belote, R. Travis; Barnett, Kate; Zeller, Katherine A.; Brennan, Angela; Gage, Josh

doi:10.1007/s10980-022-01530-9

Cited by 11 publications

(4 citation statements)

References 50 publications

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“…Y645C 3bMKHs). The revised analysis for 2017 is very similar to the results from the original connectivity published in Belote et al (2022) based on the 2015 (pairwise comparisons between output from different years within moving window size and resistance transformations were highly correlated). Therefore, the conclusions from the paper have not changed.…”

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confidence: 62%

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Correction to: Examining local and regional ecological connectivity throughout North America

Belote¹,

Barnett²,

Zeller

et al. 2023

Landsc Ecol

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supporting

confidence: 62%

“…The original article has been corrected. In the article, Examining local and regional ecological connectivity throughout North America (Belote et al 2022), we used the global human modification data of Theobald et al (2020)…”

mentioning

confidence: 99%

Correction to: Examining local and regional ecological connectivity throughout North America

Belote¹,

Barnett²,

Zeller

et al. 2023

Landsc Ecol

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“…Therefore, species-agnostic approaches have been used to model generalized connectivity across large landscape extents (e.g. Belote et al 2022). However, it is important to note that different species sometimes require very different connectivity strategies (Unnithan ; generalized connectivity may therefore produce connectivity predictions which are suitable for many species, but not suitable for others.…”

Section: Introductionmentioning

confidence: 99%

Measuring ecological connectivity with ecological distance and dynamic resistant kernels

Zeller,

Compton,

P. Finn

et al. 2024

Landsc Ecol

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Context Species-agnostic connectivity models are often used to inform management over broad spatial scales. The four main approaches to species-agnostic models parameterize resistance to movement based on naturalness, structural features, climate, or geodiversity variables. Though all four of these factors simultaneously affect species movement and flow of ecological processes, they are rarely combined. Objectives We built upon an approach that uses all four of these factors to model current and future ecological connectivity for the Crown of the Continent Ecoregion, in Canada and the USA. Methods We estimated resistance for each pixel on the landscape based on multivariate ecological distances to surrounding pixels. We then modeled connectivity with resistant kernels at different scales, and dynamically in response to future climates from 2020 to 2080. Results Across the study area, we found median connectivity values decreased by 17–50% from 2020 to 2080 depending on the scale, with broader scales experiencing greater losses in connectivity. Though often considered natural conduits for movement, stream and valley bottoms generally lost connectivity through time. Wilderness areas had significantly higher connectivity values than unprotected lands for all time steps and scales, indicating their importance for maintaining future connectivity of ecological processes. Conclusions We offer an updated approach for species-agnostic connectivity modeling that combines naturalness, structural features, and topo-climatic layers while considering multiple scales of ecological processes over a large spatial extent and dynamism through time. This approach can be applied to other landscapes to produce products for short- and long-term management of connectivity and ecological resilience.

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“…Studying landscape connectivity is crucial for better understanding many ecological processes including animal foraging behaviour [1], population distribution [2,3], gene or pathogen ow [4], migration behaviour [5], species interactions [6,7], or metapopulation persistance [8]. Analysis of landscape connectivity can also be useful to identify critical areas favouring movements [9][10][11] or to evaluate and compare the effect of land planning actions (e.g., site restoration) [12,13]. Consequently, an accurate assessment and prediction of landscape connectivity is needed to avoid spurious understanding of multiple theoretical and applied landscape connectivity-related processes.…”

Section: Introductionmentioning

confidence: 99%

Combined effects of landscape fragmentation and sampling frequency of movement data on the assessment of landscape connectivity

Prima,

Garel,

Marchand

et al. 2023

Preprint

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Background - Network theory is largely applied in real-world systems to assess landscape connectivity using empirical or theoretical networks. Empirical networks are usually built from discontinuous individual movement trajectories without knowing the effect of relocation frequency on the assessment of landscape connectivity while theoretical networks generally rely on simple movement rules. We investigated the combined effects of relocation sampling frequency and landscape fragmentation on the assessment of landscape connectivity using simulated trajectories and empirical high-resolution (1 Hz) trajectories of Alpine ibex (Capra ibex). We also quantified the capacity of commonly used theoretical networks to accurately predict landcape connectivity from multiple movement processes. Methods – We simulated forager trajectories from continuous correlated biased random walks in simulated landscapes with three levels of landscape fragmentation. High-resolution ibex trajectories were reconstructed using GPS-enabled multi-sensor biologging data and the dead-reckoning technique. For both simulated and empirical trajectories, we generated spatial networks from regularly resampled trajectories and assessed changes in their topology and information loss depending on the resampling frequency and landscape fragmentation. We finally built commonly used theoretical networks in the same landscapes and compared their predictions to actual connectivity. Results - We demonstrated that an accurate assessment of landscape connectivity can be severely hampered (e.g., up to 66% of undetected visited patches and 29% of spurious links) when the relocation frequency is too coarse compared to the temporal dynamics of animal movement. However, the level of landscape fragmentation and underlying movement processes can both mitigate the effect of relocation sampling frequency. We also showed that network topologies emerging from different movement behaviours and a wide range of landscape fragmentation were complex, and that commonly used theoretical networks accurately predicted only 30–50% of landscape connectivity in such environments. Conclusions - Very high-resolution trajectories were generally necessary to accurately identify complex network topologies and avoid the generation of spurious information on landscape connectivity. New technologies providing such high-resolution datasets over long period should thus grow in the movement ecology sphere. In addition, commonly used theoretical models should be applied with caution to the study of landscape connectivity in real-world systems as they did not perform well as predictive tools.

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Examining local and regional ecological connectivity throughout North America

Cited by 11 publications

References 50 publications

Correction to: Examining local and regional ecological connectivity throughout North America

Correction to: Examining local and regional ecological connectivity throughout North America

Measuring ecological connectivity with ecological distance and dynamic resistant kernels

Combined effects of landscape fragmentation and sampling frequency of movement data on the assessment of landscape connectivity

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