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Data from: Habitat loss and thermal tolerances influence the sensitivity of resident bird populations to winter weather at regional scales

Citation

Latimer, Christopher; Zuckerberg, Benjamin (2020), Data from: Habitat loss and thermal tolerances influence the sensitivity of resident bird populations to winter weather at regional scales, Dryad, Dataset, https://doi.org/10.5061/dryad.18931zctp

Abstract

1. Climate change and habitat loss pose the greatest contemporary threats to biodiversity, but their impacts on populations largely vary across species. These differential responses could be caused by complex interactions between landscape and climate change and species-specific sensitivities.

2. Understanding the factors that determine which species are most vulnerable to the synergistic effects of climate change and habitat loss is a high conservation priority. Here, we ask (a) whether and to what extent land cover moderates the impacts of winter weather on population dynamics of wintering birds, and (b) what role species’ physiology might play in modifying their responses to changing weather conditions.

3. To address these questions, we used thousands of observations collected by citizen scientists participating in Project FeederWatch to build dynamic occupancy models for 14 species of wintering birds.

4. Populations of wintering birds were more dynamic, having higher rates of local extinction and colonization, in more forested landscapes during extreme cold – presumably enabling them to better track resources. However, urban areas appeared to provide refuge for some species, as demonstrated by increased local colonization during the harshest winter weather. Lastly, we found that species-specific differences in thermal tolerances strongly influenced occupancy dynamics such that species that are less cold-tolerant were more likely to go locally extinct at colder sites and during colder periods throughout winter.

5. Together, our results suggest species that are less cold-tolerant and populations occupying less forested landscapes are most vulnerable to extreme winter weather. 11-Jun-2020

Methods

Project FeederWatch (PFW) data have undergone the automated filter and validation checks established by PFW researchers and were analyzed in consultation with members of the Cornell Lab of Ornithology (CLO). Requests for data beyond the scope of the linked publication should be submitted directly to PFW through the CLO. Re-use of PFW data should acknowledge the thousands of participants who have made FeederWatch possible, as well as to Birds Canada and the Cornell Lab of Ornithology for developing and managing the program. Additional details can be found at the Project FeederWatch website: https://feederwatch.org/explore/raw-dataset-requests/

Maximum cold-induced metabolic rates (Msum) were obtained from the literature and standardized by body mass (in grams). Please see the linked paper for more details. In cases where there were multiple Msum values per species, we selected the value closest to the years of study (2009, 2012 & 2015). Slope values for local extinction/colonization and detection probabilities versus seasonal temperature fluctuations were obtained through dynamic multi-season occupancy models.  

Usage Notes

PFW Data

Column variables: 

1) ID_DATE -- Combination internal user ID, Location ID, FeederWatch year and Pseudojulian date. Note: Some users have multiple locations associated with their unique user ID.

2)  Year -- Numeric year in which the observation was made

3) Month -- Numeric month in which the observation was made

4) Day -- Numeric day in which the observation was made

5) LATITUDE -- decimal latitude of the centroid of the PFW observation location

6) LONGITUDE -- decimal longitude of the centroid of the PFW observation location

7) NHalfDays -- number of half-day periods over the 2-day count in which observations were made (1, 2, 3, or 4 half-days)

8) EFFORT_HRS_ATLEAST -- Low end of the recorded effort range of number of hours spent observing. Note: some participants record a range of effort while others record a precise number. 

9) StatProv -- State/province code of the PFW site as provided by the user

10) BirdSpp -- code for the species seen

11) NSeen -- Maximum count of the species seen at any one time during the 2-day count period

 

Msum Data

Column variables:

1) sp -- species identifier codes from Project Feederwatch

2) Msum -- mass-corrected maximum cold-induced metabolic rate

3) slp_col -- colonization slope (Beta) coefficient quantifying the relation between local colonization and minimum temperature

4) slp_ext -- extinction slope (Beta) coefficient quantifying the rlationship between local extinction and minimum teperature

5) slp_det -- detection slope (Beta) coefficient quantifying the relationship between detection probability and minimum temperature

6) year -- numeric year corresponding to each Project FeederWatch season