Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

In arid and Mediterranean regions, landscape-scale wetland conservation
requires understanding how wildlife responds to dynamic freshwater
availability and human actions to enhance wetland habitat. Taking
advantage of the Landsat satellite time series (2007–2016) and structured
and community science bird survey data, we built species distribution
models to describe how three duck species – Northern Pintail (Anas acuta),
Green-winged Teal (A. crecca), and Northern Shoveler (A. clypeata) –
respond to freshwater supply and food resources on different flooded land
cover types in the Central Valley of California. Specifically, our models
were designed to compare duck habitat suitability between the wettest to
driest conditions in each month from September through April. Using
abundance-weighted boosted regression trees, we created three sets of
species occurrence models based on different covariates: (i) near
real-time (hereafter “real-time”) covariates in which duck observations
were matched to the surface water availability within the 16-day window of
a Landsat observation, (ii) a combination of real-time covariates and
waterfowl food resource covariates describing annual corn and rice biomass
and managed wetland moist soil seed yield estimates derived from Landsat
data, and (iii) long-term average covariates – the most common approach to
species distribution modeling – in which long-term average surface water
availability was used. We modeled the monthly occurrence of three duck
species as a function of surface water availability, land cover type, road
density, temperature, and bird data source. We found that dry conditions
result in reduced habitat suitability, with the biggest reductions in
November through January and in agricultural fields; in contrast,
suitability of flooded wetland habitat was relatively robust to overall
surface water availability. When models of habitat suitability based on
the long-term average climate conditions were compared to models based on
real-time conditions, the highest long-term suitability values occurred in
areas where suitability was high regardless of whether it was a wet or a
dry year. While all models performed well, the inclusion of crop and
wetland plant yield covariates resulted in slightly more accurate models.
Overall, species distribution models created using data on the
environmental conditions present at the time of bird observations can aid
conservation efforts under extreme conditions over large spatial scales.