Can bottom-up procedures improve the performance of stream classifications?

Top-down methods for defining stream classifications are based on a conceptual model or expert-defined rules, whereas bottom-up methods use biological training data and statistical modelling. We compared the performance of six classification methods for explaining the taxonomic composition of invertebrate and fish assemblages recorded at 327 and 511 sites, respectively, distributed throughout France. Classification 1 and 2 were top-down classifications; The European Water Framework System A (WFDa,) and the French Hydro-ecoregions (HER 2). Four bottom-up classification procedures of increasing complexity were defined based on 11 variables that included watershed characteristics describing climate, topography, and geology, and site characteristics including elevation, bed slope and temperature. Classification 3 was defined using matrix correlation (MC) to select a combination of variable categories that produced the best discrimination of the observed taxonomic composition. Classification 4 and 5 were defined by clustering the sites based on their taxonomic data and then using linear discriminant analysis (LDA) and Random forests (RF) to discriminate the clusters based on the environmental variables. Classification 6 was defined using generalized dissimilarity modelling (GDM). Our hypothesis was that the bottom-up classifications would perform better because they flexibly accommodate complex relationships between compositional and environmental variation. We tested the classifications using the classification strength statistic (CS). The RF-based classification fitted the taxonomic patterns better than GDM or LDA and these latter classifications generally fitted better than the MC, WFDa or HER classifications. Cross validation analysis showed that differences in predictive CS (i.e. the CS statistics produced from sites not used in defining the classifications) were often significant. However, these differences were generally small. Gains in predictive performance of classifications appear to be small relative to the increase in complexity in the manner in which environmental variables are combined to define classes.     

Measurement of persistent organic pollutants (POPs) in plastic resin pellets from remote islands: toward establishment of background concentrations for International Pellet Watch

Plastic resin pellets collected from remote islands in the Pacific, Atlantic, and Indian Oceans and the Caribbean Sea were analyzed for polychlorinated biphenyls (PCBs), dichloro-diphenyltrichloroethane and its degradation products (DDTs), and hexachlorocyclohexanes (HCHs). Concentrations of PCBs (sum of 13 congeners) in the pellets were 0.1-9.9 ng/g-pellet. These were 1-3 orders of magnitude smaller than those observed in pellets from industrialized coastal shores. Concentrations of DDTs in the pellets were 0.8-4.1 ng/g-pellet. HCH concentrations were 0.6-1.7 ng/g-pellet, except for 19.3 ng/g-pellet on St. Helena, where current use of lindane is likely influence. This study provides background levels of POPs (PCBs<10 ng/g-pellet, DDTs <4 ng/g-pellet, HCHs <2 ng/g-pellet) for International Pellet Watch. Sporadic large concentrations of POPs were found in some pellet samples from remote islands and should be considered in future assessments of pollutants on plastic debris.     

Observing Global Surface Water Flood Dynamics

Flood waves moving along river systems are both a key determinant of globally important biogeochemical and ecological processes and, at particular times and particular places, a major environmental hazard. In developed countries, sophisticated observing networks and ancillary data, such as channel bathymetry and floodplain terrain, exist with which to understand and model floods. However, at global scales, satellite data currently provide the only means of undertaking such studies. At present, there is no satellite mission dedicated to observing surface water dynamics and, therefore, surface water scientists make use of a range of sensors developed for other purposes that are distinctly sub-optimal for the task in hand. Nevertheless, by careful combination of the data available from topographic mapping, oceanographic, cryospheric and geodetic satellites, progress in understanding some of the world’s major river, floodplain and wetland systems can be made. This paper reviews the surface water data sets available to hydrologists on a global scale and the recent progress made in the field. Further, the paper looks forward to the proposed NASA/CNES Surface Water Ocean Topography satellite mission that may for the first time provide an instrument that meets the needs of the hydrology community.     

Geomechanical property estimation of unconventional reservoirs using seismic data and rock physics

An extension of a previously developed rock physics model is made that quantifies the relationship between the ductile fraction of a brittle/ductile binary mixture and the isotropic seismic reflection response. By making a weak scattering (Born) approximation and plane wave (eikonal) approximation, with a subsequent ordering according to the angles of incidence, singular value decomposition analyses are performed to understand the stack weightings, number of stacks, and the type of stacks that will optimally estimate two fundamental rock physics parameters – the ductile fraction and the compaction and/or diagenesis. It is concluded that the full PP stack, i.e., sum of all PP offset traces, and the “full” PS stack, i.e., linear weighted sum of PS offset traces, are the two optimal stacks needed to estimate the two rock physics parameters. They dominate over both the second‐order amplitude variation offset “gradient” stack, which is a quadratically weighted sum of PP offset traces that is effectively the far offset traces minus the near offset traces, and the higher order fourth order PP stack (even at large angles of incidence). Using this result and model‐based Bayesian inversion, the seismic detectability of the ductile fraction (shown by others to be the important rock property for the geomechanical response of unconventional reservoir fracking) is demonstrated on a model characteristic of the Marcellus shale play.     

Carbon Stores,Sinks, and Sources in Forests of Northwestern Russia: Can We Reconcile Forest Inventories with Remote Sensing Results?

Forest inventories and remote sensing are the two principal data sources used to estimate carbon (C) stocks and fluxes for large forest regions. National governments have historically relied on forest inventories for assessments but developments in remote sensing technology provide additional opportunities for operational C monitoring. The estimate of total C stock in live forest biomass modeled from Landsat imagery for the St. Petersburg region was consistent with estimates derived from forest inventory data for the early 1990s (272 and 269 TgC, respectively). The estimates of mean C sink in live forest biomass also agreed well (0.36 and 0.34 Mg C ha^–1 yr^–1). Virtually all forest lands were accumulating C in live biomass, however when the net change in total ecosystem C stock was considered, 19% of the forest area were a net source of C. The average net C sink in total ecosystem biomass is quite weak (0.08 MgC ha^–1 yr^–1 and could be reversed by minor increases in harvest rates or a small decline in biomass growth rates.     

Decadal predictions of the cooling and freshening of the North Atlantic in the 1960s and the role of ocean circulation

In the 1960s North Atlantic sea surface temperatures (SST) cooled rapidly. The magnitude of the cooling was largest in the North Atlantic subpolar gyre (SPG), and was coincident with a rapid freshening of the SPG. Here we analyze hindcasts of the 1960s North Atlantic cooling made with the UK Met Office’s decadal prediction system (DePreSys), which is initialised using observations. It is shown that DePreSys captures—with a lead time of several years—the observed cooling and freshening of the North Atlantic SPG. DePreSys also captures changes in SST over the wider North Atlantic and surface climate impacts over the wider region, such as changes in atmospheric circulation in winter and sea ice extent. We show that initialisation of an anomalously weak Atlantic Meridional Overturning Circulation (AMOC), and hence weak northward heat transport, is crucial for DePreSys to predict the magnitude of the observed cooling. Such an anomalously weak AMOC is not captured when ocean observations are not assimilated (i.e. it is not a forced response in this model). The freshening of the SPG is also dominated by ocean salt transport changes in DePreSys; in particular, the simulation of advective freshwater anomalies analogous to the Great Salinity Anomaly were key. Therefore, DePreSys suggests that ocean dynamics played an important role in the cooling of the North Atlantic in the 1960s, and that this event was predictable.     

The importance of population,climate change and CO2 plant physiological forcing in determining future global water stress

Future levels of water stress depend on changes in several key factors including population, climate-change driven water availability, and a carbon dioxide physiological-forcing effect on evaporation and run-off. In this study we use an ensemble of the HadCM3 climate model forced with a range of future emissions scenarios combined with a simple water scarcity index to assess the contribution of each of these factors to the projected population living in water stress over the 21st century.Population change only scenarios increase the number of people living in water stress such that at peak global population 65% of people experience some level of water stress. Globally, the climate model ensemble projects an increase in water availability which partially offsets some of the impacts of population growth. The result is 1 billion fewer people living in water stress by the 2080s under the high end emissions scenarios than if population increased in the absence of climate change.This study highlights the important role plant-physiological forcing has on future water resources. The effect of rising CO₂ is to increase available water and to reduce the number of people living in high water stress by around 200 million compared to climate only projections. This effect is of a similar order of magnitude to climate change.