A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Chemical water quality gradients in the Mongolian sub-catchments of the Selenga River basin

Even though the Selenga is the main tributary to Lake Baikal in Russia, the largest part of the Selenga River basin is located in Mongolia. It covers a region that is highly diverse, ranging from almost virgin mountain zones to densely urbanized areas and mining zones. These contrasts have a strong impact on rivers and their ecosystems. Based on two sampling campaigns (summer 2014, spring 2015), we investigated the longitudinal water quality pattern along the Selenga and its tributaries in Mongolia. While headwater regions typically had a very good water quality status, wastewater from urban areas and impacts from mining were found to be main pollution sources in the tributaries. The highest nutrient concentrations in the catchment were found in Tuul River, and severely elevated concentrations of trace elements (As, Cd, Cu, Cr, Fe, Mn, Ni, Pb, Zn), nutrients (NH₄ ⁺, NO₂ ^?, NO₃ ^?, PO₄ ^3?), and selected major ions (SO₄ ^2?) were found in main tributaries of Selenga River. Moreover, trace element concentrations during spring 2015 (a time when many mines had not yet started operation) were markedly lower than in summer 2014, indicating that the additional metal loads measured in summer 2014 were related to mining activities. Nevertheless, all taken water samples in 2014 and 2015 from the main channel of the Mongolian Selenga River complied with the Mongolian standard (MNS 1998) for the investigated parameters.     

Simplified determination of lipophilic metabolites of nonylphenol ethoxylates: method development and application in aqueous samples from Buenos Aires, Argentina

In the present work we have developed an analytical methodology for the determination of nonylphenol (NP) and nonylphenol mono- and di-ethoxylates (NP1EO and NP2EO) in water samples. The applicability of this methodology was proved by means of the analysis of environmentally relevant aqueous samples from Buenos Aires. This constitutes a starting point for a rigorous assessment of the incidence of NPnEO surfactants in Argentina, as only very few, qualitative or semi-quantitative data on the occurrence of these compounds in local systems were available up to this time. Enrichment of the analytes was carried out by solid-phase extraction on a C-18 sorbent, followed by elution with ethyl acetate. Normal-phase high performance liquid chromatography on an amino-silica column and fluorescence detection at excitation-emission wavelengths of 230-300 nm were employed for separation and quantification of the analytes. Confirmation of peak assignment in selected real samples was performed by off-line coupling HPLC with GC-MS analysis. A non-polar GC capillary column was used, and a characteristic peak pattern was obtained for the alkyl chain isomers of each ethoxylated homologue and NP. GC-MS analyses yielded in all cases purity levels higher than 80% for the HPLC collected fractions. The elevated concentrations found for the estrogenic metabolites of NPnEO are in accordance with an unrestricted use of this class of non-ionic surfactants in the country.     

Assessing benthic community condition in Chesapeake Bay: does the use of different benthic indices matter?

Federal and state environmental agencies conduct several programs to characterize the environmental condition of Chesapeake Bay. These programs use different benthic indices and survey designs, and have produced assessments that differ in the estimate of the extent of benthic community degradation in Chesapeake Bay. Provided that the survey designs are unbiased, differences may exist in the ability of these indices to identify environmental degradation. In this study we compared the results of three indices calculated on the same data, and the assessments of two programs: the Chesapeake Bay Program and the Mid-Atlantic Integrated Assessment (MAIA). We examined the level of agreement of index results using site-based measures of agreement, evaluated sampling designs and statistical estimation methods, and tested for significant differences in assessments. Comparison of ratings of individual sites was done within separate categories of water and sediment quality to identify which indices summarize best pollution problems in Chesapeake Bay. The use of different benthic indices by these programs produced assessments that differed significantly in the estimate of degradation. A larger fraction of poor sites was classified as good by the Environmental Monitoring and Assessment Program’s Virginian Province and MAIA benthic indices compared to the Chesapeake Bay benthic index of biotic integrity, although overall classification efficiencies were similar for all indices. Differences in survey design also contributed to differences in assessments. The relative difference between the indices remained the same when they were applied to an independent dataset, suggesting that the indices can be calibrated to produce consistent results.     

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1 % of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.     

Soil response to a 3-year increase in temperature and nitrogen deposition measured in a mature boreal forest using ion-exchange membranes

The projected increase in atmospheric N deposition and air/soil temperature will likely affect soil nutrient dynamics in boreal ecosystems. The potential effects of these changes on soil ion fluxes were studied in a mature balsam fir stand (Abies balsamea [L.] Mill) in Quebec, Canada that was subjected to 3 years of experimentally increased soil temperature (+4 °C) and increased inorganic N concentration in artificial precipitation (three times the current N concentrations using NH₄NO₃). Soil element fluxes (NO₃, NH₄, PO₄, K, Ca, Mg, SO₄, Al, and Fe) in the organic and upper mineral horizons were monitored using buried ion-exchange membranes (PRS? probes). While N additions did not affect soil element fluxes, 3 years of soil warming increased the cumulative fluxes of K, Mg, and SO₄ in the forest floor by 43, 44, and 79 %, respectively, and Mg, SO₄, and Al in the mineral horizon by 29, 66, and 23 %, respectively. We attribute these changes to increased rates of soil organic matter decomposition. Significant interactions of the heating treatment with time were observed for most elements although no clear seasonal patterns emerged. The increase in soil K and Mg in heated plots resulted in a significant but small K increase in balsam fir foliage while no change was observed for Mg. A 6–15 % decrease in foliar Ca content with soil warming could be related to the increase in soil-available Al in heated plots, as Al can interfere with the root uptake of Ca.     

Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.     

Modeling kelp forest distribution and biomass along temperate rocky coastlines

We address the global deficit of data describing kelp forest distribution, relative covers and biomass by testing the ability of species distribution models to predict these attributes at locations where data are currently limited. We integrated biological ground truth data with high-resolution environmental datasets to develop generalized additive models that accurately predict the structure of Laminaria forests within the Bay of Morlaix (48°42′42″N, 3°55′40″W). Forest distribution and proportional covers were predicted using water depth, light availability, wave exposure and sediment dynamics. The biomass of individual kelp species was modeled by supplementing these same variables with measures of seafloor slope and benthic position. Biomass predictions for Laminaria digitata and Laminaria hyperborea contrast the physiological tolerances of these species to light and wave exposure gradients. As a direct management output, we produced high-resolution maps (25 m² grids) that closely match independent field data and provide vital information for marine spatial planning.     

Impacts of “metals” on human health: a comparison between nine different methodologies for Life Cycle Impact Assessment (LCIA)

This paper looks into the differences and uncertainties in determining the impact of “metals’” emissions on human health, in Life Cycle Impact Assessment (LCIA). Metals are diverse substances, with different properties and characteristics, considered important in LCIA because of their toxicity to humans and ecosystems. First, we defined a list of the most significant metals in terms of impacts on human health. This was done according to precise criteria accounting for both physical and toxic properties of the metals. Second, we performed an LCIA on different key processes using various existing LCIA methodologies and including also USEtox: the recently developed consensus-model for LCIA. Last, we compared the results in relative terms using a contribution analysis. The analysis showed poor or no agreement between the methods: the relative contribution of each metal and of the metals in total to the total impact on human health changes greatly according to the LCIA method used. These differences are due mainly to the number of metals included in each method and to the technique used to calculate the characterization factors. Results obtained with USEtox show no apparent correlation with results calculated with other methods. At present time USEtox is recommended as the best model for LCIA on human toxicity, but mainly because of the large consensus behind it, because its uncertainties regarding metals are still high. The study gives a good and simple overview regarding the way different methods address the impact assessment for metals, and helps in the interpretation of LCIA results for actual LCA studies where metal emissions are involved.