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USGS · 70276605

Quality and quantity of terrestrial landscape connectivity in the US Great Lakes Coastal Zone

Abstract

Context The Great Lakes Coastal Zone (GLCZ), the world’s longest continuous freshwater coastline, consists of interspersed natural and developed landcover and is inhabited by millions of people. Anthropogenic change fragments the GLCZ, decreasing landscape connectivity. Objectives We evaluated functional landscape connectivity of the U.S. GLCZ, assessing regional connectivity, protected areas’ effects on connectivity, and identified pinchpoints where connectivity is most vulnerable. Methods We modeled landscape connectivity to describe corridors and redundant pathways for two scenarios: (1) continuous terrestrial habitat patches and (2) protected areas. We compared these two scenarios by total corridor area and quality at two spatial scales (coastal zone and ecoregion). We used random forest analyses to examine how ecological factors influenced the connectivity rank and pinchpoint values. A principal components analysis identified how land cover influenced connectivity among ecoregions. Results The GLCZ was 69% connected. Although 91% of the GLCZ’s high-quality habitat was within corridors, less than 50% of the corridor area was high-quality (low resistance to movement). While the northernmost region retained high-quality connectivity, connectivity loss and degradation increased with development further south. Corridors between protected areas provided less connectivity, of worse quality, in areas of development and agriculture. Lower connectivity was associated with higher impervious surface cover. Conclusions Protected area placement affected both the quantity and quality of connectivity. Improving and maintaining functional connectivity could be accomplished by strategically restoring and protecting habitats most vulnerable to connectivity loss, predominantly in urban and agricultural regions. Our connectivity improvement index is a useful tool to identify areas where connectivity may be improved.

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90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 41.006373° to 48.0725979° latitude; -92.6447419° to -75.7477078° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

Lindsay Elizabeth Franc Hunt, Noel B. Pavlovic, Ralph Grundel. 2026-04-10. Quality and quantity of terrestrial landscape connectivity in the US Great Lakes Coastal Zone. https://doi.org/10.1007/s10980-025-02208-8

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Leveraging time-series remote sensing to predict post-fire invasive annual grass response in western US rangelands

Context Understanding the relationship between Exotic Annual Grass (EAG) expansion, drought, and fire frequency across western US rangelands is complex, but critical for maintaining ecological integrity. Objectives We quantified the impacts of wildfire on EAGs, with emphasis on understanding the factors driving the spatial and temporal variability of those impacts, highlighting the role of drought. Methods We investigate two study periods using 1985–2024 and 2016–2024 EAG cover datasets to better understand EAG dynamics in relation to fire. We, 1) leverage mapped EAG cover responses to fire in the context of various biophysical variables to model expected change in EAG cover (ΔG) given a fire in a specific location, even if no fire has occurred in that location in the period of record; 2) evaluate the influence of drought and other biophysical variables on the ΔG; 3) combine our ΔG values with burn probability and ecological integrity data to evaluate the profile of EAG risk due to fire in sagebrush habitats. Results Our results show that fire impacts on EAG are often delayed, with limited effects in the first post-fire year followed by increasing cover over subsequent years. Importantly, areas with low pre-fire EAG cover exhibited the greatest potential for post-fire increases, whereas heavily invaded sites showed lower incremental responses, suggesting saturation or carrying-capacity constraints. Conclusions Understanding the connections among EAGs, drought, and wildfire is critical for maintaining the ecological integrity of western rangelands. Identifying the magnitude of fire impacts to EAG cover provides critical insight for land managers.

western United States↗

Ecological diffusion models are still useful in ecology

Context Connecting animal movement across scales—both among spatial scales and between individual and population level processes—is a central theme in ecology, including the sub-fields of movement and landscape ecology. However, most modeling frameworks operate at either the individual (Lagrangian) or population (Eulerian) level. Objectives We aimed to review how a partial differential equation (PDE) known as the ecological diffusion equation (EDE) offers connections among the scales of animal movement and how it can be embedded in commonly used statistical frameworks (e.g., hierarchical models) and fit to multiple types of data, such as count, presence-only, presence-absence, and telemetry data. In doing so, we also highlight emerging and promising avenues of research related to statistical EDE models. Methods We present how the EDE is derived from a simple set of first principles, can be used to represent both individual animal movement and spatiotemporal population dynamics, and can be fit to data by being applied in a hierarchical statistical framework. Finally, we review literature on recent applications and advances related to EDE models. Results In presenting the derivation of the EDE and reviewing recent advances and applications of EDE models, we established that the EDE can enable a mechanistic understanding of animal movement across scales, as well as the integration of multiple types of data. We also identified a number of topics where EDE models can be advanced to gain additional ecological insight. Conclusions Ecological diffusion is a process that emerges naturally from first principles governing animal movement and can be used to model both individual and population-level spatiotemporal dynamics. Statistical EDE models are related to other modeling frameworks, such as species distribution models, occupancy models, and step-selection analysis. The flexibility of hierarchical statistical modeling allows combining different types of data collected on movement and population dynamics, and the theoretical underpinnings of the EDE allow it to connect ecological processes occurring at fine and coarse spatial scales, as well as individual animal movement and population dynamics.

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Assessing environmental influences on gene flow for a migratory ungulate in a fire-prone landscape

Context Migratory species traverse long distances across complex landscape mosaics. Shifts in environmental attributes across space and time could affect movement paths and genetic connectivity of migratory species. Objectives We identified boundaries to genetic connectivity based on population structure and evaluated environmental influences on gene flow in a migratory ungulate. We projected how genetic connectivity might be affected by actual wildfire events. Methods We collected over 168,400 GPS locations for 97 bighorn sheep ( Ovis canadensis ) and estimated kinship with 5,140 single nucleotide polymorphisms for 95 individuals. We identified subpopulations and employed machine-learning optimization to evaluate how environmental attributes affect gene flow between them. We projected future genetic connectivity based on recent landscape changes. Results We observed that water bodies and > 70% canopy cover may limit effective dispersal, suggesting that shifts in these landscape attributes, influenced by climate and vegetation management, may affect future gene flow. We also predicted recent wildfire events will change gene flow between three subpopulations, predicting more flow where fire reduced canopy cover at a pinchpoint near a linear lake and less flow where fire was internal to the subpopulation. Conclusions Modifications in canopy cover could be applied to facilitate or impede connectivity and gene flow, depending on management goals. Large, semi-linear lakes could form movement barriers in other bighorn populations. Recent wildfires will likely increase gene flow between semi-isolated subpopulations, with implications for disease management. As wildfire and tree encroachment and densification increase, gene flow between other spatially structured populations in similar landscapes may shift.

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