Simple procedures to assess and compare the ecological niche of species

Hutchinson's (1957; Cold Spring Harbour Symp Quant Biol 22:415-427) niche concept is being used increasingly in the context of global change, and is currently applied to many ecological issues including climate change, exotic species invasion and management of endangered species. For both the marine and terrestrial realms, there is a growing need to assess the breadth of the niches of individual species and to make comparisons among them to forecast the species' capabilities to adapt to global change. In this paper, we describe simple non-parametric multivariate procedures derived from a method originally used in climatology to (1) evaluate the breadth of the ecological niche of a species and (2) examine whether the niches are significantly separated. We first applied the statistical procedures to a simple fictive example of 3 species separated by 2 environmental factors in order to describe the technique. We then used it to quantify and compare the ecological niche of 2 key-structural marine zooplankton copepod species, Calanus finmarchicus and C. helgolandicus, in the northern part of the North Atlantic Ocean using 3 environmental factors. The test demonstrates that the niches of both species are significantly separated and that the coldwater species has a niche larger than that of its warmer-water congeneric species.

Technical Note: Ensuring consistent, global measurements of short-lived halocarbon gases in the ocean and atmosphere

Very short-lived halocarbons are significant sources of reactive halogen in the marine boundary layer, and likely in the upper troposphere and lower stratosphere. Quantifying ambient concentrations in the surface ocean and atmosphere is essential for understanding the atmospheric impact of these trace gas fluxes. Despite the body of literature increasing substantially over recent years, calibration issues complicate the comparison of results and limit the utility of building larger-scale databases that would enable further development of the science (e.g. sea-air flux quantification, model validation, etc.). With this in mind, thirty-one scientists from both atmospheric and oceanic halocarbon communities in eight nations gathered in London in February 2008 to discuss the scientific issues and plan an international effort toward developing common calibration scales (http://tinyurl.com/c9cg58). Here, we discuss the outputs from this meeting, suggest the compounds that should be targeted initially, identify opportunities for beginning calibration and comparison efforts, and make recommendations for ways to improve the comparability of previous and future measurements.

Can we trust simple marine DMS parameterisations within complex climate models?

Dimethylsulphide (DMS) is a globally important aerosol precurser. In 1987 Charlson and others proposed that an increase in DMS production by certain phytoplankton species in response to a warming climate could stimulate increased aerosol formation, increasing the lower-atmosphere's albedo, and promoting cooling. Despite two decades of research, the global significance of this negative climate feedback remains contentious. It is therefore imperative that schemes are developed and tested, which allow for the realistic incorporation of phytoplankton DMS production into Earth System models. Using these models we can investigate the DMS-climate feedback and reduce uncertainty surrounding projections of future climate. Here we examine two empirical DMS parameterisations within the context of an Earth System model and find them to perform marginally better than the standard DMS climatology at predicting observations from an independent global dataset. We then question whether parameterisations based on our present understanding of DMS production by phytoplankton, and simple enough to incorporate into global climate models, can be shown to enhance the future predictive capacity of those models. This is an important question to ask now, as results from increasingly complex Earth System models lead us into the 5th assessment of climate science by the Intergovernmental Panel on Climate Change. Comparing observed and predicted inter-annual variability, we suggest that future climate projections may underestimate the magnitude of surface ocean DMS change. Unfortunately this conclusion relies on a relatively small dataset, in which observed inter-annual variability may be exaggerated by biases in sample collection. We therefore encourage the observational community to make repeat measurements of sea-surface DMS concentrations an important focus, and highlight areas of apparent high inter-annual variability where sampling might be carried out. Finally, we assess future projections from two similarly valid empirical DMS schemes, and demonstrate contrasting results. We therefore conclude that the use of empirical DMS parameterisations within simulations of future climate should be undertaken only with careful appreciation of the caveats discussed.

Air-Sea Exchange of Marine Trace Gases

Many of the reactive trace gases detected in the atmosphere are both emitted from and deposited to the global oceans via exchange across the air–sea interface. The resistance to transfer through both air and water phases is highly sensitive to physical drivers (waves, bubbles, films, etc.), which can either enhance or suppress the rate of diffusion. In addition to outlining the fundamental processes controlling the air–sea gas exchange, the authors discuss these drivers, describe the existing parameterizations used to predict transfer velocities, and summarize the novel techniques for measuring in situ exchange rates. They review trace gases that influence climate via radiative forcing (greenhouse gases), those that can alter the oxidative capacity of the atmosphere (nitrogen- and sulfur-containing gases), and those that impact ozone levels (organohalogens), both in the troposphere and stratosphere. They review the known biological and chemical routes of production and destruction within the water column for these gases, whether the ocean acts as a source or sink, and whether temporal and spatial variations in saturation anomalies are observed. A current estimate of the marine contribution to the total atmospheric flux of these gases, which often highlights the significance of the oceans in biogeochemical cycling of trace gases, is provided, and how air–sea gas fluxes may change in the future is briefly assessed.

Simple shade plots aid better long-term choices of data pre-treatment in multivariate assemblage studies

Shade plots, simple visual representations of abundance matrices from multivariate species assemblage studies, are shown to be an effective aid in choosing an overall transformation (or other pre-treatment) of quantitative data for long-term use, striking an appropriate balance between dominant and less abundant taxa in ensuing resemblance-based multivariate analyses. Though the exposition is entirely general and applicable to all community studies, detailed illustrations of the comparative power and interpretative possibilities of shade plots are given in the case of two estuarine assemblage studies in south-western Australia: (a) macrobenthos in the upper Swan Estuary over a two-year period covering a highly significant precipitation event for the Perth area; and (b) a wide-scale spatial study of the nearshore fish fauna from five divergent estuaries. The utility of transformations of intermediate severity is again demonstrated and, with greater novelty, the potential importance seen of further mild transformation of all data after differential down-weighting (dispersion weighting) of spatially clumped' or schooled' species. Among the new techniques utilized is a two-way form of the RELATE test, which demonstrates linking of assemblage structure (fish) to continuous environmental variables (water quality), having removed a categorical factor (estuary differences). Re-orderings of sample and species axes in the associated shade plots are seen to provide transparent explanations at the species level for such continuous multivariate patterns.