Influence of water depth on nest success of the endangered Cape Sable seaside sparrow in the Florida Everglades

The restoration of the Florida Everglades rests largely on the ability of managers to re-create a more natural hydrologic regime throughout the remaining natural areas. The Cape Sable seaside sparrow, an endangered subspecies endemic to the freshwater marl prairies of the Everglades, has suffered from changes in the depth and the timing of water flows through its habitat. However, it remains unclear what temporal and spatial aspects of water inputs (both managed and natural) affect nesting success. We monitored 429 nests in two of the six extant sparrow subpopulations over 10 breeding seasons and a variety of water levels. Using an information-theoretic approach, we find that nests initiated early in the breeding season experience substantially higher success rates than those initiated later. We suggest that this seasonal effect is due to a change in predator abundance or activity levels as the season progresses, which are tied to the increase in water levels that accompany the onset of the wet season. In addition, nest success is influenced to a lesser degree by where sparrows choose to nest across the landscape, the height of base water levels within the sparrow's breeding season and the height of water levels when nests are active. Our observation of extreme variability in nest success over the span of a single season suggests that successful late-season breeding, although shown to be important for population recovery, is a rare event. Management actions that maximize the success of late-season broods or increase the number of early broods are warranted, but the ecosystem implications of such actions are poorly understood.     

A method of determining rooting depth from a terrestrial biosphere model and its impacts on the global water and carbon cycle

We outline a method of inferring rooting depth from a Terrestrial Biosphere Model by maximizing the benefit of the vegetation within the model. This corresponds to the evolutionary principle that vegetation has adapted to make best use of its local environment. We demonstrate this method with a simple coupled biosphere/soil hydrology model and find that deep rooted vegetation is predicted in most parts of the tropics. Even with a simple model like the one we use, it is possible to reproduce biome averages of observations fairly well. By using the optimized rooting depths global Annual Net Primary Production (and transpiration) increases substantially compared to a standard rooting depth of one meter, especially in tropical regions that have a dry season. The decreased river discharge due to the enhanced evaporation complies better with observations. We also found that the optimization process is primarily driven by the water deficit/surplus during the dry/wet season for humid and arid regions, respectively. Climate variability further enhances rooting depth estimates. In a sensitivity analysis where we simulate changes in the water use efficiency of the vegetation we find that vegetation with an optimized rooting depth is less vulnerable to variations in the forcing. We see the main application of this method in the modelling communities of land surface schemes of General Circulation Models and of global Terrestrial Biosphere Models. We conclude that in these models, the increased soil water storage is likely to have a significant impact on the simulated climate and the carbon budget, respectively. Also, effects of land use change like tropical deforestation are likely to be larger than previously thought.