The pervasive influence of island biogeography theory on forest fragmentation research has often led to a misleading conceptualization of landscapes as areas of forest/habitat and ‘non‐forest/non‐habitat’ and an overriding focus on processes within forest remnants at the expense of research in the human‐modified matrix. The matrix, however, may be neither uniformly unsuitable as habitat nor serve as a fully–absorbing barrier to the dispersal of forest taxa. In this paper, we present a conceptual model that addresses how forest habitat loss and fragmentation affect biodiversity through reduction of the resource base, subdivision of populations, alterations of species interactions and disturbance regimes, modifications of microclimate and increases in the presence of invasive species and human pressures on remnants. While we acknowledge the importance of changes associated with the forest remnants themselves (e.g. decreased forest area and increased isolation of forest patches), we stress that the extent, intensity and permanence of alterations to the matrix will have an overriding influence on area and isolation effects and emphasize the potential roles of the matrix as not only a barrier but also as habitat, source and conduit. Our intention is to argue for shifting the examination of forest fragmentation effects away from a patch‐based perspective focused on factors such as patch area and distance metrics to a landscape mosaic perspective that recognizes the importance of gradients in habitat conditions.

Landscape pattern indicators or ‘metrics’ provide simple measures of landscape structure that can be easily calculated with readily available data and software. Unfortunately, the ecological relevance of many metrics (i.e. the relationship between metric values and the real-world ecological processes that they are meant to serve as proxies for) is often unproven and questionable, and concerns are regularly voiced that such metrics fail to capture important aspects of landscape function. In this paper, I provide a review of landscape measures that may better link landscape pattern and function, ranging from approaches that extend existing metrics by incorporating a more functional component (e.g. core area measures, least cost distances) to those rooted in graph, network, and electrical circuit theory. While more ‘functional’ approaches are becoming increasingly popular, the selection of appropriate landscape metrics in many applications involves tradeoffs regarding data requirements, ease of calculation, functional basis, and simplicity of interpretation by a range of specialist and non-specialist stakeholders. Regardless, there continues to be a need for landscape metrics because they are seen by many land managers and stakeholders as simple, intuitive tools for assessing and monitoring changes in landscape pattern and, by extension, the effects on underlying ecological processes. Future needs include: (1) the development of more user-friendly landscape analysis software that can simplify graph-based analyses and visualization; and (2) studies that clarify the strengths and weaknesses of different approaches, including the potential limitations and biases in graph and network-based measures.

Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (a ‘burn window’) are met. Here, we evaluate the potential impacts of projected climatic change on prescribed burning in the south-eastern United States by applying a set of burn window criteria that capture temperature, relative humidity and wind speed to projections from an ensemble of Global Climate Models under two greenhouse gas emission scenarios. Regionally, the percentage of suitable days for burning changes little during winter but decreases substantially in summer owing to rising temperatures by the end of the 21st century compared with historical conditions. Management implications of such changes for six representative land management units include seasonal shifts in burning opportunities from summer to cool-season months, but with considerable regional variation. We contend that the practical constraints of rising temperatures on prescribed fire activities represent a significant future challenge and show that even meeting basic burn criteria (as defined today) will become increasingly difficult over time, which speaks to the need for adaptive management strategies to prepare for such changes.

Globally increasing wildfires have been attributed to anthropogenic climate change. However, providing decision makers with a clear understanding of how future planetary warming could affect fire regimes is complicated by confounding land use factors that influence wildfire and by uncertainty associated with model simulations of climate change. We use an ensemble of statistically downscaled Global Climate Models in combination with the Physical Chemistry Fire Frequency Model (PC2FM) to project changing potential fire probabilities in the conterminous United States for two scenarios representing lower (RCP 4.5) and higher (RCP 8.5) greenhouse gas emission futures. PC2FM is a physically-based and scale-independent model that predicts mean fire return intervals from both fire reactant and reaction variables, which are largely dependent on a locale's climate. Our results overwhelmingly depict increasing potential fire probabilities across the conterminous US for both climate scenarios. The primary mechanism for the projected increases is rising temperatures, reflecting changes in the chemical reaction environment commensurate with enhanced photosynthetic rates and available thermal molecular energy. Existing high risk areas, such as the Cascade Range and the Coastal California Mountains, are projected to experience greater annual fire occurrence probabilities, with relative increases of 122% and 67%, respectively, under RCP 8.5 compared to increases of 63% and 38% under RCP 4.5. Regions not currently associated with frequently occurring wildfires, such as New England and the Great Lakes, are projected to experience a doubling of occurrence probabilities by 2100 under RCP 8.5. This high resolution, continental-scale modeling study of climate change impacts on potential fire probability accounts for shifting background environmental conditions across regions that will interact with topographic drivers to significantly alter future fire probabilities. The ensemble modeling approach presents a useful planning tool for mitigation and adaptation strategies in regions of increasing wildfire risk.

Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices and released by SafeGraph as part of their Social Distancing Metric dataset. Based on comparisons with visitation statistics released by the U.S. National Park Service, our results confirmed that mobility records from digital devices can effectively capture park visitation patterns but with much finer spatiotemporal granularity. In general, triggers of visitation changes corresponded well with the parks’ management responses to COVID-19, with all six parks showing dramatic decreases in the number of visitors (compared to 2019) beginning in March 2020 and continuing through April and May. As restrictions were eased to promote access to the parks and the benefits associated with outdoor recreation, visitation in 2020 approached or even passed that from 2019 by late summer or early autumn at most of the parks. The results also revealed that parks initially saw the greatest increases in visitation after reopening originating from nearby states, with visitorship coming from a broader range of states as time passed. Our study highlights the capability of mobility data for providing spatiotemporally explicit knowledge of place visitation.