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Lidar-based MaxEnt models to support conservation planning for endangered Red-cockaded Woodpeckers in urbanizing environments

Brett L. Lawrence

Published 2024 in Remote Sensing Applications Society and Environment

ABSTRACT

13 Sensitive and intensively managed species require carefully thought-out management plans to 14 promote and maintain specific habitat conditions. Urban features and land-use change must be 15 assimilated into these habitat management plans, as they become increasingly present globally. As 16 a case study, several MaxEnt species distribution models were developed that could enable habitat 17 management efforts for the endangered Red-cockaded Woodpecker (RCW) in moderate to 18 increasingly urbanized environments. Model development began with a classification of fine-scale, 19 lidar-based habitat indicators with the area normalized at the stand level and developed around 20 known habitat characteristics of RCW. Other explanatory rasters included distance to different 21 urban features, and experimentation with spectral layers outside the visible light spectrum. Models 22 were trained using presence data from a relatively small but comprehensively surveyed population 23 in Montgomery County, Texas, and three compartments that were recently pedestrian surveyed for 24 RCWs on the Sam Houston National Forest. The former is experiencing moderate levels of 25 urbanization, and the latter is in earlier stages. The best performing model predicted RCW presence 26 94% of the time at a 0.4 probability threshold and resulted in an area under the curve (AUC) of 27 0.88. Successful model development required a specific combination of steps and data processing, 28 including the use of lidar-based habitat indicators created using data fusion and machine learning 29 classification, land-use features, and non-visible spectra . These methods can provide valuable 30 insights into strategic habitat planning for the RCW and other sensitive species in urbanizing 31 landscapes. This study reinforces what habitat characteristics promote RCW success, while 32 providing valuable insights to guide management activities around urbanization. These could 33 include mapping suitable recruitment areas that remain unoccupied, spatially identifying where 34 habitat quality was lacking or sufficient, and predicting the impact of future land-use change. This 35 case study demonstrates that species distribution modelling can be successfully applied at 36 subpopulation and fine scales, and for the practical purpose of enabling habitat and conservation 37 planning where anthropogenic activities are adding challenging complexities.

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