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.     

Sampling animal association networks with the gambit of the group

Ecologists increasingly use network theory to examine animal association patterns. The gambit of the group (GoG) is a simple and useful assumption for accumulating the data necessary for a network analysis. The gambit of the group implies that each animal in a group is associating with every other individual in that group. Sampling is an important issue for networks in wild populations collected assuming GoG. Due to time, effort, and resource constraints and the difficulty of tracking animals, sampled data are usually a subset of the actual network. Ecologists often use association indexes to calculate the frequency of associations between individuals. These indexes are often transformed by applying a filter to produce a binary network. We explore GoG sampling using model networks. We examine assortment at the level of the group by a single dichotomous trait, along with many other network measures, to examine the effect of different sampling regimes, and choice of filter on the accuracy and precision with which measures are estimated. We find strong support for the use of weighted, rather than filtered, network measures and show that different filters have different effects depending on the nature of the sampling. We make several practical recommendations for ecologists planning GoG sampling.     

Biodegradation of carbofuran in soils within Nzoia River Basin,Kenya

Carbofuran (2,3-dihydro-2,2-dimethylbenzofuran-7-yl methylcarbamate) has been used within the Nzoia River Basin (NRB), especially in Bunyala Rice Irrigation Schemes, in Kenya for the control of pests. In this study, the capacity of native bacteria to degrade carbofuran in soils from NRB was investigated. A gram positive, rod-shaped bacteria capable of degrading carbofuran was isolated through liquid cultures with carbofuran as the only carbon and nitrogen source. The isolate degraded 98% of 100-μg mL^?1 carbofuran within 10 days with the formation of carbofuran phenol as the only detectable metabolite. The degradation of carbofuran was followed by measuring its residues in liquid cultures using high performance liquid chromatography (HPLC). Physical and morphological characteristics as well as molecular characterization confirmed the bacterial isolate to be a member of Bacillus species. The results indicate that this strain of Bacillus sp. could be considered as Bacillus cereus or Bacillus thuringiensis with a bootstrap value of 100% similar to the 16S rRNA gene sequences. The biodegradation capability of the native strains in this study indicates that they have great potential for application in bioremediation of carbofuran-contaminated soil sites.     

Development of a real-time immuno-PCR assay for the quantification of 17β-estradiol in water

A competitive real-time (RT) immuno-polymerase chain reaction (iPCR) (RT-iPCR) assay was developed for the sensitive quantification of 17β-estradiol in water. Using a universal iPCR method and polyclonal antibodies, 17β-estradiol was accurately quantified at concentrations ranging from 1 pg mL^?1 to 10 µg mL^?1. The RT-iPCR assay's limit of detection was 0.7 pg mL^?1. The RT-iPCR assay provided an 800-fold increase in sensitivity as well as an expanded working range compared with the corresponding enzyme-linked immunosorbent assay. Assay cross-reactivity to estrone and estriol, two structurally related estrogens, was below 8%. Water samples spiked with 17β-estradiol were analyzed by RT-iPCR to determine the assay's potential as a rapid screen for the monitoring of manure-borne estrogens in the environment. The assay showed recoveries of 82, 102 and 103% for Milli-Q, tap, and irrigation water, respectively, without requiring sample extraction or concentration prior to analysis.     

Defending the scientific integrity of conservation‐policy processes

Government agencies faced with politically controversial decisions often discount or ignore scientific information, whether from agency staff or nongovernmental scientists. Recent developments in scientific integrity (the ability to perform, use, communicate, and publish science free from censorship or political interference) in Canada, Australia, and the United States demonstrate a similar trajectory. A perceived increase in scientific‐integrity abuses provokes concerted pressure by the scientific community, leading to efforts to improve scientific‐integrity protections under a new administration. However, protections are often inconsistently applied and are at risk of reversal under administrations publicly hostile to evidence‐based policy. We compared recent challenges to scientific integrity to determine what aspects of scientific input into conservation policy are most at risk of political distortion and what can be done to strengthen safeguards against such abuses. To ensure the integrity of outbound communications from government scientists to the public, we suggest governments strengthen scientific integrity policies, include scientists’ right to speak freely in collective‐bargaining agreements, guarantee public access to scientific information, and strengthen agency culture supporting scientific integrity. To ensure the transparency and integrity with which information from nongovernmental scientists (e.g., submitted comments or formal policy reviews) informs the policy process, we suggest governments broaden the scope of independent reviews, ensure greater diversity of expert input and transparency regarding conflicts of interest, require a substantive response to input from agencies, and engage proactively with scientific societies. For their part, scientists and scientific societies have a responsibility to engage with the public to affirm that science is a crucial resource for developing evidence‐based policy and regulations in the public interest.