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Abstract Emperor penguins (Aptenodytes forsteri) are under increasing environmental pressure. Monitoring colony size and population trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when light conditions levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that can predict the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are rare or unavailable.
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Remotely sensed environmental measurements detect decoupled processes driving population dynamics at contrasting scales
Abstract The increasing availability of satellite imagery has supported a rapid expansion in forward‐looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat‐5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well‐characterized population of banner‐tailed kangaroo rats (Dipodomys spectabilis) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco‐evolutionary studies.
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- Award ID(s):
- 2010251
- PAR ID:
- 10441329
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecology and Evolution
- Volume:
- 13
- Issue:
- 8
- ISSN:
- 2045-7758
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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