• Energy Research

Landscape ecology is a discipline that explicitly considers the influence of time and space on the environmental patterns we observe and the processes that create them. Although many of the topics studied in landscape ecology have public policy implications, three are of particular concern: climate change; land use–land cover change (LULCC); and a particular type of LULCC, urbanization. These processes are interrelated, because LULCC is driven by both human activities (e.g., agricultural expansion and urban sprawl) and climate change (e.g., desertification). Climate change, in turn, will affect the way humans use landscapes. Interactions among these drivers of ecosystem change can have destabilizing and accelerating feedback, with consequences for human societies from local to global scales. These challenges require landscape ecologists to engage policymakers and practitioners in seeking long-term solutions, informed by an understanding of opportunities to mitigate the impacts of anthropogenic drivers on ecosystems and adapt to new ecological realities.

Landscape ecology is a discipline that explicitly considers the influence of time and space on the environmental patterns we observe and the processes that create them. Although many of the topics studied in landscape ecology have public policy implications, three are of particular concern: climate change; land use–land cover change (LULCC); and a particular type of LULCC, urbanization. These processes are interrelated, because LULCC is driven by both human activities (e.g., agricultural expansion and urban sprawl) and climate change (e.g., desertification). Climate change, in turn, will affect the way humans use landscapes. Interactions among these drivers of ecosystem change can have destabilizing and accelerating feedback, with consequences for human societies from local to global scales. These challenges require landscape ecologists to engage policymakers and practitioners in seeking long-term solutions, informed by an understanding of opportunities to mitigate the impacts of anthropogenic drivers on ecosystems and adapt to new ecological realities.

An increasing amount of California’s landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland–urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate–fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies.

An increasing amount of California’s landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland–urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate–fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies.

Significance On tropical islands, extensive extirpation of birds and other vertebrates occurred during the Holocene, following human arrival. Much less is known about pre-Holocene extirpation on islands. We focus on two species (Eastern bluebird Sialia sialis and Hispaniolan crossbill Loxia megaplaga ) that were lost in the Bahamas to changes in sea level (becoming higher), land area (getting smaller), climate (becoming warmer and wetter), and habitat (loss of pine grassland) that took place during the last glacial–interglacial transition, many millennia before peopling of the islands. While volant, the bluebird evolved a short wing in the Bahamas, whereas the crossbill retained a similar morphology to the surviving population on Hispaniola. Each major glacial–interglacial shift reconfigured the resident Bahamian flora and fauna.

Significance On tropical islands, extensive extirpation of birds and other vertebrates occurred during the Holocene, following human arrival. Much less is known about pre-Holocene extirpation on islands. We focus on two species (Eastern bluebird Sialia sialis and Hispaniolan crossbill Loxia megaplaga ) that were lost in the Bahamas to changes in sea level (becoming higher), land area (getting smaller), climate (becoming warmer and wetter), and habitat (loss of pine grassland) that took place during the last glacial–interglacial transition, many millennia before peopling of the islands. While volant, the bluebird evolved a short wing in the Bahamas, whereas the crossbill retained a similar morphology to the surviving population on Hispaniola. Each major glacial–interglacial shift reconfigured the resident Bahamian flora and fauna.

Predicting climate-driven species’ range shifts depends substantially on species’ exposure to climate change. Mountain landscapes contain a wide range of topoclimates and soil characteristics that are thought to mediate range shifts and buffer species’ exposure. Quantifying fine-scale patterns of exposure across mountainous terrain is a key step in understanding vulnerability of species to regional climate change. We demonstrated a transferable, flexible approach for mapping climate change exposure in a moisture-limited, mountainous California landscape across 4 climate change projections under phase 5 of the Coupled Model Intercomparison Project (CMIP5) for mid-(2040–2069) and end-of-century (2070–2099). We produced a 149-year dataset (1951–2099) of modeled climatic water deficit (CWD), which is strongly associated with plant distributions, at 30-m resolution to map climate change exposure in the Tehachapi Mountains, California, USA. We defined climate change exposure in terms of departure from the 1951–1980 mean and historical range of variability in CWD in individual years and 3-year moving windows. Climate change exposure was generally greatest at high elevations across all future projections, though we encountered moderate topographic buffering on poleward-facing slopes. Historically dry lowlands demonstrated the least exposure to climate change. In moisture-limited, Mediterranean-climate landscapes, high elevations may experience the greatest exposure to climate change in the 21st century. High elevation species may thus be especially vulnerable to continued climate change as habitats shrink and historically energy-limited locations become increasingly moisture-limited in the future.