<i>landscapemetrics</i>: an open‐source <i>R</i> tool to calculate landscape metrics

Hesselbarth, Maximillian H.K.; Sciaini, Marco; Wiegand, Kerstin; Nowosad, Jakub

doi:10.1111/ecog.04617

Cited by 626 publications

(386 citation statements)

References 41 publications

(75 reference statements)

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“…The number of trees was 1000, and 999 permutations for the 'out-of-bag' data were conducted to assess the variable importance. We used the 'randomforest' (Liaw and Wiener 2002) and 'landscapemetrics' packages (Hesselbarth et al 2019) in R to perform these analyses.…”

Section: Resultsmentioning

confidence: 99%

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

et al. 2020

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Climate change can affect the habitat resources available to species by changing habitat quantity, suitability and spatial configuration, which largely determine population persistence in the landscape. In this context, dispersal is a central process for species to track their niche. Assessments of the amount of reachable habitat (ARH) using static snap‐shots do not account, however, for the temporal overlap of habitat patches that may enhance stepping‐stone effects. Here, we quantified the impacts of climate change on the ARH using a spatio–temporal connectivity model. We first explored the importance of spatio–temporal connectivity relative to purely spatial connectivity in a changing climate by generating virtual species distributions and analyzed the relative effects of changes in habitat quantity, suitability and configuration. Then, we studied the importance of spatio–temporal connectivity in three vertebrate species with divergent responses to climate change in North America (grey wolf, Canadian lynx and white‐tailed deer). We found that the spatio–temporal connectivity could enhance the stepping‐stone effect for species predicted to experience range contractions, and the relative importance of the spatio–temporal connectivity increased with the reduction in habitat quantity and suitability. Conversely, for species that are likely to expand their ranges, spatio–temporal connectivity had no additional contribution to improve the ARH. We also found that changes in habitat amount (quantity and suitability) were more influential than changes in habitat configuration in determining the relative importance of spatio–temporal connectivity. We conclude that spatio–temporal connectivity may provide less biased and more realistic estimates of habitat connectivity than purely spatial connectivity.

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Section: Resultsmentioning

confidence: 99%

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

et al. 2020

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“…The 5 × 5 pixel moving window was also used for analysis of two local patch‐based metrics, total edge (TE) and percent habitat (PHAB), using FRAGSTATS metrics TE and PLAND via the landscapemetrics package in R (R Core Team, 2018, v1.1 , Hesselbarth, Sciaini, With, Wiegand, & Nowosad, 2019). We chose TE and PHAB because melting causes sea ice patches to be spatially correlated during breakup, which precludes the use of configuration metrics in FRAGSTATS (Sahanatien & Derocher, 2012).…”

Section: Methodsmentioning

confidence: 99%

Comparing sea ice habitat fragmentation metrics using integrated step selection analysis

Biddlecombe

Bayne

Lunn

et al. 2020

Ecology and Evolution

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Habitat fragmentation occurs when continuous habitat gets broken up as a result of ecosystem change. While commonly studied in terrestrial ecosystems, Arctic sea ice ecosystems also experience fragmentation, but are rarely studied in this context. Most fragmentation analyses are conducted using patch‐based metrics, which are potentially less suitable for sea ice that has gradual changes between sea ice cover, than distinct “long‐term” patches. Using an integrated step selection analysis, we compared the descriptive power of a patch‐based metric to a more novel metric, the variation in local spatial autocorrelation over time. We used satellite telemetry data from 39 adult female polar bears (Ursus maritimus) in Hudson Bay to examine their sea ice habitat using Advanced Microwave Scanning Radiometer 2 data during sea ice breakup in May through July from 2013–2018. Spatial autocorrelation resulted in better model fits across 64% of individuals, although both metrics were more effective in describing movement patterns than habitat selection. Variation in local spatial autocorrelation allows for the visualization of sea ice habitat at complex spatial and temporal scales, condensing a targeted time period of habitat that would otherwise have to be analyzed daily.

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“…We found that the calculation for effective connectivity can be performed with reasonable accuracy in equivalent computational time to other landscape metrics such as average patch size and edge-to-area ratio (see Hesselbarth et al 2019). We used heuristic arguments involving the effective connectivity metric to develop the following ansatz for equilibrium species richness in a neutral model on a fragmented landscape:…”

Section: Analytical Solutions For Complex Landscapes: Incorporating Ementioning

confidence: 99%

Characterising extinction debt following habitat fragmentation using neutral theory

2019

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Habitat loss leads to species extinctions, both immediately and over the long term as ‘extinction debt’ is repaid. The same quantity of habitat can be lost in different spatial patterns with varying habitat fragmentation. How this translates to species loss remains an open problem requiring an understanding of the interplay between community dynamics and habitat structure across temporal and spatial scales. Here we develop formulas that characterise extinction debt in a spatial neutral model after habitat loss and fragmentation. Central to our formulas are two new metrics, which depend on properties of the taxa and landscape: ‘effective area’, measuring the remaining number of individuals and ‘effective connectivity’, measuring individuals’ ability to disperse through fragmented habitat. This formalises the conventional wisdom that habitat area and habitat connectivity are the two critical requirements for long‐term preservation of biodiversity. Our approach suggests that mechanistic fragmentation metrics help resolve debates about fragmentation and species loss.

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landscapemetrics: an open‐source R tool to calculate landscape metrics

Cited by 626 publications

References 41 publications

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

Comparing sea ice habitat fragmentation metrics using integrated step selection analysis

Characterising extinction debt following habitat fragmentation using neutral theory

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