Burn severity data from: The heterogeneity of burn severity affects bird density in an abandoned mountain landscape of the Atlantic-Mediterranean transition

Abstract

<strong>[Abstract]</strong> Fire regimes in mountain landscapes of southern Europe have been shifting from their baselines due to the accumulation of fuel fostered by long-standing rural abandonment and fire exclusion policies. Understanding the role of fire on biodiversity is paramount to implement adequate management to mitigate the impacts of altered fire regimes and land abandonment on biodiversity. Here, we explored to what extent the spatiotemporal variation in burn severity has affected bird abundance of a mountain abandoned landscape located in the Atlantic-Mediterranean transition (NW Iberia). We took advantage of: (1) satellite images of Sentinel 2 and Landsat missions to compute burn severity indicators from 2010 to 2020, and (2) standardized bird surveys carried out over 206 point-counts along the breeding season of 2021. Bird abundance models were built from burn severity metrics together with well-known fire regime attributes (% of burnt area and time since fire). Our results showed that the spatiotemporal variation of burn severity significantly correlated with the abundance of the 39% of the modeled species, supporting the role of pyro-diversity in driving bird populations in our region. The burnt area also explained abundance patterns for 28% of species. Time since fire only correlated with the abundance of 3 species. Our findings confirm the importance of incorporating burn severity indicators into the toolkit of decision makers to anticipate the response of birds to fire management. <strong>[Dataset Description]</strong> For each year between 2010 and 2020, we used a pair of satellite images, one before (April - July) and one after (September - November) the fire season. In order to use the best available information, we selected different satellites along the study period: for years 2010 and 2011, we used Landsat 5 imagery, whereas for 2012 we used Landsat 7, since Landsat 5 imagery was not useful due to high cloudiness. Since its launch in 2013, we shifted to Landsat 8 data, and finally to Sentinel 2 data from 2015 onwards. For each of these images we calculated the Normalized Burn Ratio (NBR), which is the normalized ratio between near infrared (NIR) and short wave infrared (SWIR) radiation (Eq. 1). NIR and SWIR bands of satellite sensors respond in opposite ways to burned vegetation, allowing to identify burned areas. NBR =(NIR - SWIR) / (NIR +SWIR) (1) To obtain a quantitative measure of change for each year, we calculated the dNBR by subtracting the NBR of the post-fire season image from the NBR of the pre-fire season image (Eq. 2). Finally, dNBR values were used as an estimate for fire severity. dNBR = NBRprefire- NBRpostfire (2)