Birds respond rapidly to changes in both habitat and climate conditions and thus are good indicators of the ecological effects of a changing climate, which may include warmer temperatures, changing habitat conditions, and increased frequency and magnitude of extreme events like drought. We investigated how a widespread tree mortality event concurrent with a severe drought influenced the avian community of the Sierra Nevada mountain range in California. We assessed and compared the separate effects of climate stresses and altered habitat conditions on the avian community and used this information to evaluate the changes that are likely to occur in the near future. We built tree mortality maps from freely available Landsat imagery with Google Earth Engine. We analyzed avian point counts from 2010 to 2016 in the southern Sierra Nevada, to model temperature, water deficit, and tree mortality effects on the abundances of 45 bird species, and then used these models to project abundances into the future based on three climate projections. A large portion of the avian community, 47%, had a positive relationship with temperature increase, compared to 20% that responded negatively. More species (36%) declined with drier conditions than increased (29%). More species declined in response to high tree mortality (36%) than increased (9%). A preponderance of species adapted to colder temperatures (higher elevation) had negative responses to high tree mortality and water deficit, but positive responses to increasing temperature. We projected the highest total bird abundances in the future under the warmest climate scenario that we considered, but habitat modification (e.g., tree mortality) and water deficit could offset the positive influence of temperature for many species. As other studies have shown, climate warming may lead to substantial but idiosyncratic effects on wildlife species that could result in community composition shifts. We conclude that future climate conditions may not have a universally negative effect on biodiversity in the Sierra Nevada, but probable vegetation changes and increased likelihood of extreme events such as drought should be incorporated into climate‐smart forest and wildlife management decisions.
data formatted for analysis_Roberts et al. 2019 EcoApps
Bird survey detections and covariates file. Each row in this spreadsheet is a detection of a single species at a particular distance (in some cases may be more than one individual). Fields in this file include: PointYrID (a unique identifier for each point visited in a given year); Point (unique identifier for each field location); Transect (unique identifier for groups of points arranged in a 5-point transect); Year (calendar year in which the detections were recorded); Site (unique identifier for a pair of two 5-point transects in close proximity); Rep2 (visit identifier in sequential order across all years of surveys); Rep1 (visit identifier for sequential visit within the same calendar year, 1-2-3 are only possible values); Date (calendar date of the visit); DOY (numerical identifier of day of year on which the visit took place, possible values = 1-365); TOD (numerical format of time of day); Count (number of individuals detected); Spp (species identified, conforming to 4-letter AOU codes); Detection Cue (song=S, visual=V, call=C, drumming=D, hum=H, juvenile=J); Distance (distance in meters at first detection); Temp (temperature in degrees celsius); Wind (Beaufort scale estimated wind measurment).
Site covs.Roberts et al. 2019 EcoApps
Site covariates file. Fields include: PointYrID (unique identifier for each point visited in each year); Forested (visual estimate from Google Earth imagery of the forest condition); ConDieOffGIS (visual estimate from GoogleEarth imagery and field survey estimates of the percent of standing trees within 100m of the bird survey plot center that have succumbed to beetle mortality); ConDieOfffield (visual estimate by field survey crew members of the percent of standing trees within 100m of the bird survey plot center that have succumbed to beetle mortality); CWHR1 (California Wildlife Habitat Relationship forest type classification); Point (unique point identifier); Year (calendar year in which the visit occurred); MaxOfVisit (number of visits in a single calendar year in which bird survey data were gathered); latitude (geographic coordinate WGS84/NAD83); longitude (geographic coordinate WGS84/NAD83); elevation (elevation in meters sampled from DEM); elevres (elevation residual from a regression of elevation vs. latitude for entire Bioregional Monitoring project sample); aspect (degrees aspect, 0-360); slope (% of vertical); SRI (Solar Radiation Index); southness (proportion of completely south-facing aspect [180 degrees]); ShrubCov (shrub cover, field estimated % cover); TreeCov (tree cover, field estimated % cover); BA (basal area, square feet per acre); g30SNAGS (count of snags greater than 30cm in diameter), totSNAGS (count of snags greater than 10cm in diameter); MaxDBH (diameter in inches of largest trees within 50m); PineProp (proportion of total tree cover that is either Sugar Pine, Ponderosa Pine, or Jeffrey Pine); NDWI (normalized difference wetness index); dNDWI (difference in normalized difference wetness index from baseline value in 2009); cwd (climatic water deficit in mm H2O); dCWD (difference in CWD from baseline value in 2009); tmn (average daily minimum temperature in june); tmx (average daily maximum temperature in June); dtmn (difference in average daily minimum temperature in June from baseline value in 2009); dtmx (difference in average daily maximum temperature in June from baseline value in 2009).
species list
List of species included in this analysis. Fields include Spp (4-letter AOU code); model (best fitting distsamp model detection function)
Site covs CNRM85b
Covariates file for future predictions of species abundances based on the CNRM climate projections. All covariates as described in "Site covs.Roberts et al. 2019 EcoApps.csv" file except that temperature (TMN, TMX, dDMN, dTMX) data are sampled from future predictions according to the CNRM85 scenario.
Site covs GFDLB1b
Covariates file for future predictions of species abundances based on the CNRM climate projections. All covariates as described in "Site covs.Roberts et al. 2019 EcoApps.csv" file except that temperature (TMN, TMX, dDMN, dTMX) data are sampled from future predictions according to the GFDLB1 scenario.
Site covs MIROC85b
Covariates file for future predictions of species abundances based on the CNRM climate projections. All covariates as described in "Site covs.Roberts et al. 2019 EcoApps.csv" file except that temperature (TMN, TMX, dDMN, dTMX) data are sample from future predictions according to the MIROC85 scenario.
