DOI: 10.5061/dryad.hdr7sqvdw
title: Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances

description: Disturbances play a key role in driving forest ecosystem dynamics, but how
 disturbances shape wildlife habitat across space and time often remains
 unclear. A major reason for this is a lack of information about changes in
 habitat suitability across large areas and longer time periods. Here, we
 use a novel approach based on Landsat satellite image time series to map
 seasonal habitat suitability annually from 1986 to 2017. Our approach
 involves characterizing forest disturbance dynamics using Landsat-based
 metrics, harmonizing these metrics through a temporal segmentation
 algorithm, and then using them together with GPS telemetry data in habitat
 models. We apply this framework to assess how natural forest disturbances
 and post-disturbance salvage logging affect habitat suitability for two
 ungulates, roe deer (Capreolus capreolus) and red deer (Cervus elaphus),
 over 32 years in a Central European forest landscape. We found that red
 and roe deer differed in their response to forest disturbances. Habitat
 suitability for red deer consistently improved after disturbances, whereas
 the suitability of disturbed sites was more variable for roe deer
 depending on season (lower during winter than summer) and disturbance
 agent (lower in windthrow versus bark-beetle-affected stands). Salvage
 logging altered the suitability of bark beetle-affected stands for deer,
 having negative effects on red deer and mixed effects on roe deer, but
 generally did not have clear effects on habitat suitability in windthrows.
 Our results highlight long-lasting legacy effects of forest disturbances
 on deer habitat. For example, bark beetle disturbances improved red deer
 habitat suitability for at least 25 years. The duration of disturbance
 impacts generally increased with elevation. Methodologically, our approach
 proved effective for improving the robustness of habitat reconstructions
 from Landsat time series: integrating multi-year telemetry data into
 single, multi-temporal habitat models improved model transferability in
 time. Likewise, temporally segmenting the Landsat-based metrics increased
 the temporal consistency of our habitat suitability maps. As the frequency
 of natural forest disturbances is increasing across the globe, their
 impacts on wildlife habitat should be considered in wildlife and forest
 management. Our approach offers a widely applicable method for monitoring
 habitat suitability changes caused by landscape dynamics such as forest
 disturbance
description: GPS telemetry data and Landsat-based spectral-temporal metrics
 used for creating Maxent habitat models. Dataset includes presence
 observations (obtained from GPS telemetry) as well as randomly-sampled
 background points (pseudo-absences). All observations are augmented with
 spectral-temporal metrics (10th, 50th and 90th percentile) calculated for
 the Tasseled Cap indices brightness, greenness and wetness using all
 available Landsat satellite observations within a three-year moving
 window, which additionally were harmonized across time using the
 LandTrendr algorithm. Explanation of data frame
 columns: <strong>id </strong>- Name of deer
 individual <strong>date </strong>-
 Observation date (MM/DD/YYY) <strong>hour
 </strong>- Daytime hour <strong>year
 </strong>- Year <strong>species
 </strong>- Deer species (red deer / roe deer)
 <strong>presence </strong>- Binary 1/0, indicating
 whether the observation is a presence location obtained from GPS telemetry
 or a randomly sampled background point (pseudoabsence)
 <strong>greenness_p10 </strong>- 10th percentile of
 Tasseled Cap greenness <strong>greenness_p50
 </strong>- 50th percentile of Tasseled Cap greenness
 <strong>greenness_p90 </strong>- 90th percentile of
 Tasseled Cap greenness <strong>brightness_p10
 </strong>- 10th percentile of Tasseled Cap brightness
 <strong>brightness_p50 </strong>- 50th percentile of
 Tasseled Cap brightness <strong>brightness_p90
 </strong>- 90th percentile of Tasseled Cap brightness
 <strong>wetness_p10 </strong>- 10th percentile of
 Tasseled Cap wetness <strong>wetness_p50
 </strong>- 50th percentile of Tasseled Cap wetness
 <strong>wetness_p90 </strong>- 90th percentile of
 Tasseled Cap wetness <strong>season
 </strong>- "summer" or "winter", indicating
 which seasonal habitat model the observation was used for
   The Google Earth Engine Code for calculating
 the time series of Landsat-based metrics is provided under the following
 link: https://code.earthengine.google.com/?accept_repo=users/julianoeser/Oeser_et_al_2020_Landsat_habitat_dynamics