Characterization of Kemp's Ridley Sea Turtles in the Florida Big Bend Area: Final report

The Kemp's ridley (Lepidochelys kempo is considered the most endangered of the seven extant marine turtle species (Ross et al. 1989). The US Fish and Wildlife Service (USFWS) and the National Marine Fisheries Service (NMFS) estimate the breeding population at 1,500 to 3,000 individuals. The nesting population has been reduced from approximately 40,000 on one day to no more than 700 annually (Magnuson et al. 1990, USFWS & NMFS 1992). Conservation measures for the species have focused on the protection of the nesting beach, captive rearing (head starting), and the implementation of turtle excluder devices (TEDs) on shrimp nets. Five hundred to 5,000 ridleys are still taken incidentally yearly by shrimp trawls (Magnuson et al. 1990). Lack of knowledge about early life stages of the Kemp's ridley sea turtle currently hinders recovery efforts for this federally listed species. (Document has 18 pages.

Responses of boreal vegetation to recent climate change

The high northern latitudes have warmed faster than anywhere else in the globe during the past few decades. Boreal ecosystems are responding to this rapid climatic change in complex ways and some times contrary to expectations, with large implications for the global climate system. This thesis investigates how boreal vegetation has responded to recent climate change, particularly to the lengthening of the growing season and changes in drought severity with warming. The links between the timing of the growing season and the seasonal cycle of atmospheric CO2 are evaluated in detail to infer large-scale ecosystem responses to changing seasonality and extended period of plant growth. The influence of warming on summer drought severity is estimated at a regional scale for the first time using improved data. The results show that ecosystem responses to warming and lengthening of the growing season in autumn are opposite to those in spring. Earlier springs are associated with earlier onset of photosynthetic uptake of atmospheric CO2 by northern vegetation, whereas a delayed autumn, rather than being associated with prolonged photosynthetic uptake, is associated with earlier ecosystem carbon release to the atmosphere. Moreover, the photosynthetic growing season has closely tracked the pace of warming and extension of the potential growing season in spring, but not in autumn. Rapid warming since the late 1980s has increased evapotranspiration demand and consequently summer and autumn drought severity, offsetting the effect of increasing cold-season precipitation. This is consistent with ongoing amplification of the hydrological cycle and with model projections of summer drying at northern latitudes in response to anthropogenic warming. However, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and vegetation photosynthesis across extensive regions of the boreal zone, where vegetation growth is often assumed to be dominantly temperature-limited. Snow-mediated moisture controls of vegetation growth are particularly significant in northwestern North America. In this region, a non-linear growth response of white spruce growth to recent warming at high elevations was observed. Taken together, these results indicate that net observed responses of northern ecosystems to warming involve significant seasonal contrasts, can be non-linear and are mediated by moisture availability in about a third of the boreal zone

Can We Detect Changes in Amazon Forest Structure Using Measurements of the Isotopic Composition of Precipitation?

Large‐scale (>500 km) spatial gradients of precipitation oxygen isotope‐ratios (δ18Op) hold information about the hydrological cycle. They result from the interplay between rainout and evapotranspiration along air‐parcel paths, but these counteracting effects are difficult to disentangle complicating quantification of the effect of land cover change on δ18Op. We show that disentangling can qualitatively be achieved using climate model simulations with a land‐derived precipitation tracer for tropical South America. We then either vary land cover as observed since 1870 or by replacing Amazon forests with bare land to determine the resulting signals. Our results indicate that effects of historically changing land cover on annual mean δ18O isotope‐ratio gradients are small and unlikely detectable, although there is a noticeable signal during the dry season. Furthermore, the effect of changes in water recycling on Amazon δ18Op in paleo‐records may have been overestimated and need reinterpretation

Was the extreme Northern Hemisphere greening in 2015 predictable?

The year 2015 was, at the time, the warmest since 1880, and many regions in the Northern Hemisphere (NH) registered record breaking annual temperatures. Simultaneously, a remarkable and widespread growing season greening was observed over most of the NH in the record from the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). While the response of vegetation to climate change (i.e. the long term trend) is assumed to be predictable, it is still unclear whether it is also possible to predict the interannual variability in vegetation activity. Here, we evaluate whether the unprecedented magnitude and extent of the greening observed in 2015 corresponds to an expected response to the 2015 climate anomaly, or to a change in the sensitivity of NH vegetation to climate. We decompose NDVI into the long-term and interannual variability components, and find that the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) explain about half of NDVI interannual variability. This response is in addition to the long-term temperature and human-induced greening trend. We use a simple statistical approach to predict the NDVI anomaly in 2015, using the PDO and AMO states as predictors for interannual variability, and temperature and precipitation trends for the long-term component. We show that the 2015 anomaly can be predicted as an expected vegetation response to temperature and water-availability associated with the very strong state of the PDO in 2015. The link found between climate variability patterns and vegetation activity should contribute to increase the predictability of carbon-cycle processes at interannual time-scales, which may be relevant, for instance, for optimizing land-management strategies

Understanding the uncertainty in global forest carbon turnover

The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985-2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world\u27s forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth

The accuracy of climate variability and trends across Arctic Fennoscandia in four reanalyses

Arctic Fennoscandia has undergone significant climate change over recent decades. Reanalysis datasets allow us to understand the atmospheric processes driving such changes. Here we evaluate four reanalyses against observations of near-surface air temperature (SAT) and precipitation (PPN) from 35 meteorological stations across the region for the 35-year period from 1979-2013. The reanalyses compared are the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), the European Centre for Medium-Range Weather Forecast (ECMWF) Interim reanalysis (ERA-Interim), the Japanese Meteorological Agency (JMA) 55-year reanalysis (JRA-55) and National Aeronautics and Space Administration (NASA)’s Modern-Era Retrospective Analysis for Research and Applications (MERRA). All four reanalyses have an overall small cool bias across Arctic Fennoscandia, with MERRA typically ~1°C cooler than the others. They generally reproduce the broad spatial patterns of mean SAT across the region, although less well in areas of complex orography. Observations reveal a statistically significant warming across Arctic Fennoscandia, with the majority of trends significant at p < 0.01. Three reanalyses show similar regional warming but of smaller magnitude while CFSR is anomalous, even having a slight cooling in some areas. In general the other reanalyses are sufficiently accurate to correctly reproduce the varying significance of observed seasonal trends. There are much greater differences between the reanalyses when comparing PPN to observations. MERRA-Land, which merges a gauge-based dataset, is clearly the best: CFSR is the least successful, with a significant wet bias. The smoothed reanalysis orography means that the high PPN associated with the western side of the Scandinavian Mountains extends too far inland. Spatial patterns of PPN trends across the region differ markedly between the reanalyses, which have varying success at matching observations and generally fail to replicate sites with significant observed trends. Therefore, using reanalyses to analyse PPN changes in Arctic Fennoscandia should be undertaken with caution.G.J.M. was supported by the UK Natural Environment Research Council (NERC) through the British Antarctic Survey research programme Polar Science for Planet Earth. K.J. was partially funded by the Academy of Finland (Decision No. 278067 for the PLUMES project). R.M.V. is funded by NERC PhD studentship NE/L002507/1