Application of lidar to assess the habitat selection of an endangered small mammal in an estuarine wetland environment

Author:

Hagani Jason S.1ORCID,Takekawa John Y.1,Skalos Shannon M.23,Casazza Michael L.2,Riley Melissa K.4,Estrella Sarah A.4,Barthman‐Thompson Laureen M.5,Smith Katie R.67,Buffington Kevin J.8,Thorne Karen M.8ORCID

Affiliation:

1. Suisun Resource Conservation District Suisun City California USA

2. U.S. Geological Survey Western Ecological Research Center Dixon California USA

3. California Department of Fish and Wildlife West Sacramento California USA

4. California Department of Fish and Wildlife Fairfield California USA

5. California Department of Fish and Wildlife Stockton California USA

6. WRA, Inc. San Rafael California USA

7. Department of Wildlife, Fish and Conservation Biology UC Davis Davis California USA

8. U.S. Geological Survey Davis Field Station, University of California Davis Davis California USA

Abstract

AbstractLight detection and ranging (lidar) has emerged as a valuable tool for examining the fine‐scale characteristics of vegetation. However, lidar is rarely used to examine coastal wetland vegetation or the habitat selection of small mammals. Extensive anthropogenic modification has threatened the endemic species in the estuarine wetlands of the California coast, such as the endangered salt marsh harvest mouse (Reithrodontomys raviventris; SMHM). A better understanding of SMHM habitat selection could help managers better protect this species. We assessed the ability of airborne topographic lidar imagery in measuring the vegetation structure of SMHM habitats in a coastal wetland with a narrow range of vegetation heights. We also aimed to better understand the role of vegetation structure in habitat selection at different spatial scales. Habitat selection was modeled from data compiled from 15 small mammal trapping grids collected in the highly urbanized San Francisco Estuary in California, USA. Analyses were conducted at three spatial scales: microhabitat (25 m2), mesohabitat (2025 m2), and macrohabitat (~10,000 m2). A suite of structural covariates was derived from raw lidar data to examine vegetation complexity. We found that adding structural covariates to conventional habitat selection variables significantly improved our models. At the microhabitat scale in managed wetlands, SMHM preferred areas with denser and shorter vegetation and selected for proximity to levees and taller vegetation in tidal wetlands. At the mesohabitat scale, SMHM were associated with a lower percentage of bare ground and with pickleweed (Salicornia pacifica) presence. All covariates were insignificant at the macrohabitat scale. Our results suggest that SMHM preferentially selected microhabitats with access to tidal refugia and mesohabitats with consistent food sources. Our findings showed that lidar can contribute to improving our understanding of habitat selection of wildlife in coastal wetlands and help to guide future conservation of an endangered species.

Funder

National Fish and Wildlife Foundation

Publisher

Wiley

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