Contrasting human influences and macro-environmental factors on fire activity inside and outside protected areas of North America

Abstract

Human activities threaten the effectiveness of protected areas (PAs) in achieving their conservation goals across the globe. In this study, we contrast the influence of human and macro-environmental factors driving fire activity inside and outside PAs. Using area burned between 1984 and 2014 for 11 ecoregions in Canada and the United States, we built and compared statistical models of fire likelihood using the MaxEnt software and a set of 11 key anthropogenic, climatic, and physical variables. Overall, the full model (i.e. including all variables) performed better (adjusted area under the curve ranging from 0.71 to 0.95 for individual ecoregions) than the model that excluded anthropogenic variables. Both model types (with and without anthropogenic variables) generally performed better inside than outside the PAs. Climatic variables were usually of foremost importance in explaining fire activity inside and outside PAs, with anthropogenic variables being the second most important predictors, even inside PAs. While the individual contributions of anthropogenic variables indicate that fire activity decreased as of function of increasing human footprint, the anthropogenic effects were often substantially greater than those of physical features and were comparable to or even greater than climatic effects in some densely developed ecoregions, both outside and within PAs (e.g. Mediterranean California, Eastern Temperate Forest, and Tropical Wet Forests). Together, these results show the pervasive impact of humans on fire regimes inside PAs, as well as outside PAs. Given the increasing attractiveness of PAs, the implications for adaptive fire management beyond the concept of naturalness in the PAs are discussed. Our assessment of human-altered fire activity could serve as an indicator of human pressure in PAs; however, we suggest that further analysis is needed to understand specific interactions among fire, human pressures, and the environmental conditions at the scale of PAs. Significance statementProtected areas (PAs) are critical for maintaining habitat integrity, species diversity, and ecosystem health. Untangling the biophysical and anthropogenic drivers of fire regimes within PAs is crucial for developing effective strategies to preserve and manage biodiversity and ecosystem functions. Our study reveals the large influence of humans on fire activity in and outside of PAs. Even in PAs with minimal human activity, human influence on fire is pervasive and reduces fire activity. Our assessment of human-altered fire activity could be used as an indicator to measure the effectiveness of PAs in meeting conservation goals.

COVID-19 and Forests in Canada and the United States: Initial Assessment and Beyond

“…A poll (Harris Poll, 2020) suggested that nearly two in five urban residents in the United States considered moving to a less crowded place. Outmigration from cities into rural areas due to the COVID-19 pandemic could have multiple impacts on rural communities near forests by further stressing services (Mueller et al, 2021), as well as on forest management, specifically from exacerbating the impacts of expanding the wildland-urban interface (WUI) on wildland firefighting, wildlife conflicts, and changing expectations of forest management (Radeloff et al, 2005;Hammer et al, 2009;Abrams et al, 2014;Mansuy et al, 2019). A recent survey of the rural western states in the United States is an example of changing expectations; it showed weak support for logging (41%), as opposed to 81% who supported traditional farming and ranching (Farrell et al, 2020).…”

Contrasting responses to climate change at Himalayan treelines revealed by population demographics of two dominant species

“…This upward shift is more complex than simple climate change, as fire frequency and intensity were also found to be significant drivers (Luckman & Kavanagh, ). In North America, shifts toward hotter, more frequent wildfires has been linked to climate change (Kirchmeier‐Young, Gillett, Zwiers, Cannon, & Anslow, ; Mansuy et al, ).…”

A review of machine learning applications in wildfire science and management

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