No abstract

Issue Geodiversity (i.e., the variation in Earth's abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA's Shuttle Radar Topography Mission (SRTM) and c . 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature.

No abstract

[1] Everglades freshwater marshes were once carbon sinks, but human-driven hydrologic changes have led to uncertainty about the current state of their carbon dynamics. To investigate the effect of hydrology on CO 2 exchange, we used eddy covariance measurements for 2 years (2008)(2009) in marl (short-hydroperiod) and peat (long-hydroperiod) wetlands in Everglades National Park. The importance of site, season, and environmental drivers was evaluated using linear and nonlinear modeling, and a novel method was used to test for temporally lagged patterns in the data. Unexpectedly, the long-hydroperiod peat marsh was a small CO 2 source (19.9 g C m À2 from July to December 2008 and 80.0 g C m À2 in 2009), and at no time over the study period was it a strong sink. Contrary to previous research suggesting high productivity rates from a short-hydroperiod marsh, we estimated that the marl site was a small CO 2 sink in 2008 (net ecosystem exchange [NEE] = À78.8 g C m À2 ) and was near neutral for carbon balance in 2009. In addition, both sites had relatively low gross ecosystem exchange (GEE) over the 2 years of this study. The two sites showed similar responses for NEE versus air temperature, ecosystem respiration (R eco ) versus air temperature, and R eco versus water depth, although the magnitude of the responses differed. We saw small lags (30 min in most cases) between carbon fluxes and environmental drivers. This study is foundational for understanding the carbon balance of these ecosystems prior to implementation of the planned Everglades restoration of historical water flow that will likely alter the future trajectory of the carbon dynamics of the Everglades as a whole.

No abstract