Using Landsat Satellite Imagery to Investigate Spatial and Temporal Variation in Life History Traits in a Long-Term...

Long-term, individual-level studies can provide valuable insights into the effects of climate and landscape change on the ecology and population dynamics of wild animals. However, many such studies lack environmental data collected at the spatial and temporal resolutions needed to determine how populations respond to changing conditions. In these cases, the retrospective use of satellite-derived data can provide a way to recover past environmental information. Using a 27-year dataset of an Australian insectivorous passerine, the superb fairy-wren Malurus cyaneus, we assessed how climate variation influences vegetation productivity and, indirectly, superb fairy-wren life history traits through potential changes in trophic interactions. Specifically, we combined long-term, individual-level monitoring of superb fairy-wrens and local weather records with Landsat satellite imagery, from which we derived measures of vegetation productivity using the Normalised Difference Vegetation Index (NDVI) as a proxy for food availability through arthropod abundance. We found a complex set of associations between NDVI and different components of weather, when considering both concurrent and lagged effects. Our analyses of the causes of seasonal variation in superb fairy-wren life history traits demonstrated that NDVI was associated with: (i) temporal variation in breeding success, with years with high spring and summer NDVI values having relatively high average breeding success; and (ii) spatial variation in adult mortality in autumn and winter, with superb fairy-wren territories with low autumn-winter NDVI values having higher average mortality rates. Notably, autumn-winter NDVI values were found to have remained relatively consistent over time, indicating that vegetation productivity cannot explain recently observed increases in adult autumn-winter mortality. Our study illustrates the potential of using long-term Landsat satellite imagery to investigate whether associations between animal life history traits and climate are mediated by vegetation productivity and to what extent temporal trends are influenced by climate change.