Abstract

Wildfire disturbances can cause modifications in different dimensions of ecosystem functioning, i.e., the flows of matter and energy. There is an increasing need for methods to assess such changes, as functional approaches offer advantages over those focused solely on structural or compositional attributes. In this regard, remote sensing can support indicators for estimating a wide variety of effects of fire on ecosystem functioning, beyond burn severity assessment. These indicators can be described using intra-annual metrics of quantity, seasonality, and timing, called Ecosystem Functioning Attributes (EFAs). Here, we propose a satellite-based framework to evaluate the impacts, at short to medium term (i.e., from the year of fire to the second year after), of wildfires on four dimensions of ecosystem functioning: (i) primary productivity, (ii) vegetation water content, (iii) albedo, and (iv) sensible heat. We illustrated our approach by comparing inter-annual anomalies in satellite-based EFAs in the northwest of the Iberian Peninsula, from 2000 to 2018. Random Forest models were used to assess the ability of EFAs to discriminate burned vs. unburned areas and to rank the predictive importance of EFAs. Together with effect sizes, this ranking was used to select a parsimonious set of indicators for analyzing the main effects of wildfire disturbances on ecosystem functioning, for both the whole study area (i.e., regional scale), as well as for four selected burned patches with different environmental conditions (i.e., local scale). With both high accuracies (area under the receiver operating characteristic curve (AUC) > 0.98) and effect sizes (Cohen’s |d| > 0.8), we found important effects on all four dimensions, especially on primary productivity and sensible heat, with the best performance for quantity metrics. Different spatiotemporal patterns of wildfire severity across the selected burned patches for different dimensions further highlighted the importance of considering the multi-dimensional effects of wildfire disturbances on key aspects of ecosystem functioning at different timeframes, which allowed us to diagnose both abrupt and lagged effects. Finally, we discuss the applicability as well as the potential advantages of the proposed approach for more comprehensive assessments of fire severity.

Highlights

  • Wildfire disturbances are considered an integral part of the natural dynamics of ecosystems in several biomes [1,2]

  • In terms of the performance of the Random Forest (RF) models for our test case, the results obtained for leave-group-out cross-validation can be considered very good across all sample sets, with around 0.9815 ± 0.0004 for AUC, 0.9080 ± 0.0015 for sensitivity, and

  • The same exception was observed within all seasonality Ecosystem Functioning Attributes (EFAs), where otherwise, land surface temperature (LST) was the dimension from which EFA anomalies obtained higher variable importance scores overall, especially for standard deviation

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Summary

Introduction

Wildfire disturbances are considered an integral part of the natural dynamics of ecosystems in several biomes [1,2]. Notwithstanding, wildfire events can modify the composition, structure, and functioning of ecosystems and, the provision of ecosystem services to humankind [3] Among those alterations, changes in ecosystem functioning are of particular interest, as fire can cause rapid modifications in the matter and energy budgets of ecosystems [4]. Wildfires can have profound impacts on many key aspects of the flows of matter and energy These include dimensions of ecosystem functioning related to the biogeochemical cycles of carbon (e.g., primary productivity, biomass), and water (e.g., vegetation water content, soil moisture), as well as energy balances (e.g., albedo, latent heat, sensible heat)

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