The effect of scale in quantifying fire impacts on species habitats

Abstract

Background: Fire size and severity have increased in the western United States in recent decades, and are expected to continue to increase with warming climate. Habitats for many species are threatened by large and high-severity fires, but the effect of spatial scale on the relationship between fires and habitat modifications is poorly understood. We used the 2011 Wallow Fire-the largest wildfire in the state history of Arizona, USA-as a case study and assessed changes in predicted nesting habitat of the threatened Mexican spotted owl (Strix occidentalis Xántus de Vésey) in the first three years following the fire. Our objective was to explore potential relationships between burn severity and changes in habitat suitability at different spatial scales. To accomplish this, we applied a multi-scale optimized habitat selection model to pre-and post-fire landscapes and compared the differences in predictions along a continuous scale gradient. Results: Fire effects on habitat quality were spatially variable and the strength and direction of relationships were scale-dependent. Spatial patterns of burn-severity mosaic resembled the patterns of habitat suitability change. High burn severity reduced nesting habitat suitability and this relationship was strongest at broad scales. Pre-fire habitat suitability was positively related to burn severity, again at fairly broad scales, but the relationship was weak. Low-severity fires had little effect on habitat suitability. Conclusions: Multi-scale analysis may influence the statistical measures of goodness of fit in assessing fire effects on species and their habitats. Future studies should explicitly address spatial scale when quantifying fire effects.

Megafire causes persistent loss of an old‐forest species

“…As a result, this study answers a criticism of such short‐term studies that owls and other old‐forest species may simply return after a brief displacement by a fire event. In addition, we (i) conducted our population analysis at multiple spatial scales to assess whether and to what extent fire effects are scale‐dependent (McGarigal et al., 2016; Wan, Cushman, & Ganey, 2020), (ii) included survey data from additional spotted owl territories in our study area to strengthen inferences about fire effects, (iii) applied a novel data filtering approach of detection/non‐detection data to improve biological meaning of effects (Berigan et al., 2019) and (iv) explored the potential role of pyrodiversity (variation in burn severity) in mediating population response to fire (Jones and Tingley, in press).…”

Southwestern ponderosa pine forest patterns following wildland fires managed for resource benefit differ from reference landscapes

“…We see evidence for this as the range of most metric values became increasingly constrained as the scale of landscape extents grew, while tending towards divergent metric values for each landscape type. Understanding the behavior of ponderosa forest landscape pattern across scales is necessary for scale-dependent ecological function and management objectives (Turner and Gardner 2015), including wildland re behavior (Povak et al 2018), habitat suitability (Timm et al 2016;McGarigal et al 2016;Wan et al 2020), forest health and ecohydrology (Stevens 2017), and climate mitigation and carbon sequestration (McCauley et al 2019). Shape metrics were consistently unimportant in our models, suggesting area and aggregation metrics are more important for assessing treatment effectiveness and guiding future restoration plans.…”

Southwestern ponderosa pine forest patterns following wildland fires managed for resource benefit differ from reference landscapes

“…We see evidence for this as the range of most metric values became increasingly constrained as the scale of landscape extents grew, while tending towards divergent metric values for each landscape type. Understanding the behavior of ponderosa forest landscape pattern across scales is necessary for scale-dependent ecological function and management objectives (Turner and Gardner 2015), including wildland re behavior (Povak et al 2018), habitat suitability (Timm et al 2016;McGarigal et al 2016;Wan et al 2020), forest health and ecohydrology (Stevens 2017), and climate mitigation and carbon sequestration (McCauley et al 2019). Shape metrics were consistently unimportant in our models, suggesting area and aggregation metrics are more important for assessing treatment effectiveness and guiding future restoration plans.…”

“…While we initially explored a large suite of landscape metrics, we concentrated on twelve common metrics which easily translated to forest management and silvicultural prescriptions in particular (Reynolds et al 2013;Churchill et al 2013;Rodman et al 2016), were parsimonious in their description of landscape pattern (Cushman et al 2008), and were useful in evaluation of restoration treatment success (Dickinson et al 2016;Ziegler et al 2017;Huffman et al 2017). Our approach to assessing differences across scale allowed us to examine those outcomes and provided some insight into the scales at which management would be necessary to address particular ecological processes and functions (Kerr and Ostrovsky 2003;Uuemaa et al 2013;Wan et al 2020) and could serve to help outline future restoration planning efforts (Churchill et al 2013;Dickinson et al 2016;Cannon et al 2020;Wan et al 2020).…”