Robust Projections of Future Fire Probability for the Conterminous United States

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\u27s 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

Developing a translational ecology workforce

We define a translational ecologist as a professional ecologist with diverse disciplinary expertise and skill sets, as well as a suitable personal disposition, who engages across social, professional, and disciplinary boundaries to partner with decision makers to achieve practical environmental solutions. Becoming a translational ecologist requires specific attention to obtaining critical non-scientific disciplinary breadth and skills that are not typically gained through graduate-level education. Here, we outline a need for individuals with broad training in interdisciplinary skills, use our personal experiences as a basis for assessing the types of interdisciplinary skills that would benefit potential translational ecologists, and present steps that interested ecologists may take toward becoming translational. Skills relevant to translational ecologists may be garnered through personal experiences, informal training, short courses, fellowships, and graduate programs, among others. We argue that a translational ecology workforce is needed to bridge the gap between science and natural resource decisions. Furthermore, we argue that this task is a cooperative responsibility of individuals interested in pursuing these careers, educational institutions interested in training scientists for professional roles outside of academia, and employers seeking to hire skilled workers who can foster stakeholder-engaged decision making

Foundations of Translational Ecology

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today\u27s complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist–practitioner partnerships. The creativity and context-specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use-driven, actionable science. Moreover, addressing research questions that arise from on-the-ground management issues – as opposed to the top-down or expert-oriented perspectives of traditional science – can foster the high levels of trust and commitment that are critical for long-term, sustained engagement between partners

Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements

Abstract In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers (HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom‐fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor‐shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor‐shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications

Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements.

In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers (HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom-fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor-shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor-shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications

Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs

Conducting managed species translocations and establishing climate change refugia are adaptation strategies to cope with projected consequences of global warming, but successful implementation requires on-the-ground validation of demographic responses to transient climate conditions. Here we estimated the effect of nine abiotic and biotic factors on local occupancy and an index of abundance (few or chorus) for four amphibian species (Eleutherodactylus wightmanae, E. brittoni, E. antillensis, and E. coqui) in Puerto Rico, USA. We also assessed how the same factors influenced reproductive activity of E. coqui and how species responded to hurricane María (20 September 2017). As predicted, occupancy and abundance of E. wightmanae, E. brittoni and E. coqui were positively and strongly influenced by abiotic covariates (e.g., relative humidity) that characterize high elevation, mesic habitats. E. antillensis exhibited the opposite pattern, with highest probabilities (≥0.6) recorded at ≤300 m and with average relative humidity80% and temperature of ≤26 °C. Moderate to high probabilities of detecting a chorus (0.4–0.7) were recorded at sites with average temperatures>26 °C, but no reproductive activity was detected, implying that monitoring abundance alone could misrepresent the capacity of a local population to sustain itself. The possibility underscores the importance of understanding the interplay between local demographic and environmental parameters in the advent of global warming to help guide monitoring and management decisions, especially for high elevation specialists. Hurricanes can inflict marked reductions in population numbers, but impacts vary by location and species. We found that the abundance (chorus) of E. antillensis and E. brittoni increased after the hurricane, but the abundance of the other two species did not differ between years. Lack of impacts was probably mediated by low structural damage to forest tracts (e.g., 9% canopy loss). Our findings help assess habitat suitability in terms of parameters that foster local population growth, which provides a basis for testing spatio-temporal predictions about demographic rates in potential climate refugia and for designing criteria to help guide managed translocations

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires

Examples of SLEUTH model output.

<p>Individual fifty-year model simulations (2010–2060) along with the final projection based on 200 Monte Carlo simulations for two fast-growing regions: Walton County in Georgia (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102261#pone-0102261-g004" target="_blank">Figure 4a and 4b</a>) and Wake County in North Carolina (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102261#pone-0102261-g004" target="_blank">Figure 4c and 4d</a>). Red cells in (a) and (c) correspond to new urban growth and gold cells depict 2009 classified urban areas. Cell colors in (b) and (d) are the same as color legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102261#pone-0102261-g001" target="_blank">Figure 1</a>.</p