Quantifying species recovery and conservation success to develop an IUCN Green List of Species

Stopping declines in biodiversity is critically important, but it is only a first step toward achieving more ambitious conservation goals. The absence of an objective and practical definition of species recovery that is applicable across taxonomic groups leads to inconsistent targets in recovery plans and frustrates reporting and maximization of conservation impact. We devised a framework for comprehensively assessing species recovery and conservation success. We propose a definition of a fully recovered species that emphasizes viability, ecological functionality, and representation; and use counterfactual approaches to quantify degree of recovery. This allowed us to calculate a set of 4 conservation metrics that demonstrate impacts of conservation efforts to date (conservation legacy); identify dependence of a species on conservation actions (conservation dependence); quantify expected gains resulting from conservation action in the medium term (conservation gain); and specify requirements to achieve maximum plausible recovery over the long term (recovery potential). These metrics can incentivize the establishment and achievement of ambitious conservation targets. We illustrate their use by applying the framework to a vertebrate, an invertebrate, and a woody and an herbaceous plant. Our approach is a preliminary framework for an International Union for Conservation of Nature (IUCN) Green List of Species, which was mandated by a resolution of IUCN members in 2012. Although there are several challenges in applying our proposed framework to a wide range of species, we believe its further development, implementation, and integration with the IUCN Red List of Threatened Species will help catalyze a positive and ambitious vision for conservation that will drive sustained conservation action.     

The Adaptation for Conservation Targets (ACT) Framework: A Tool for Incorporating Climate Change into Natural Resource Management

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)-water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.     

Measurement of Ozone Levels by Ship Along the Eastern Shore of Lake Michigan

The U.S. Environmental Protection Agency (EPA), in cooperation with the Toronto Harbour Commissioners (THC), conducted a Superfund Innovative Technology Evaluation (SITE) demonstration of the THC Soil Recycle Treatment Train. The treatment train consists of three technologies operated in sequence: a soil wash process, a metals removal process, and a biological treatment process. The THC conducted an extensive demonstration of the treatment train at a 55 tons per day pilot plant in order to evaluate an approach for remediation of industrial/commercial sites that are situated in the Toronto Port Industrial District (PID). Three soils were processed during the THC demonstration. The EPA SITE demonstration project examined, in detail, soil processing from one of the sites being evaluated as part of the overall THC project. Contaminants included organic compounds and heavy metals. It has been estimated by THC that as much as 2,200,000 tons of soil from locations within the PID may require some form of treatment due to heavy metal and/or organic contamination that resulted from various industrial processing operations. The objective of the SITE demonstration was to evaluate the technical effectiveness of the process in relation to THC’s target criteria.

Gravel and sand that met the THC target criteria for medium to fine soil suitable for industrial/commercial sites was produced. The fine soil from the biological treatment process did not meet the target level of 2.4 ppm for benzo(a)pyrene. However, there was a significant reduction in polynuclear aromatic hydrocarbon (PAH) compounds. The metals removal process achieved reductions of greater than seventy percent for copper, lead, nickel, and zinc.     

Tissue distribution, isozyme abundance and sensitivity to chlorpyrifos-oxon of carboxylesterases in the earthworm Lumbricus terrestris

A laboratory-based study was conducted to determine the basal carboxylesterase (CbE) activity in different tissues of the earthworm Lumbricus terrestris, and its sensitivity to the organophosphate (OP) pesticide chlorpyrifos-oxon (CPx). Carboxylesterase activity was found in the pharynx, crop, gizzard, anterior intestine, wall muscle and reproductive tissues of L. terrestris, and multiple tissue-specific isozymes were observed by native gel electrophoresis. Esterase activity and sensitivity to CPx inhibition varied on a tissue- and substrate-specific basis, suggesting isoforms-specific selectivity to OP-mediated inhibition. Three practical issues are recommended for the use of earthworm CbE activity as a biomarker of pesticide exposure: (i) CbE should be measured using several routine substrates, (ii) it should be determined in selected tissues instead of whole organism homogenate, and (iii) earthworm CbE activity should be used in conjuncture with other common biomarkers (e.g., ChE) within a multibiomarker approach to assess field exposure of OPs, and potentially other agrochemicals.     

Multi-decadal changes in tundra environments and ecosystems: synthesis of the International Polar Year-Back to the Future project (IPY-BTF)

Understanding the responses of tundra systems to global change has global implications. Most tundra regions lack sustained environmental monitoring and one of the only ways to document multi-decadal change is to resample historic research sites. The International Polar Year (IPY) provided a unique opportunity for such research through the Back to the Future (BTF) project (IPY project #512). This article synthesizes the results from 13 papers within this Ambio Special Issue. Abiotic changes include glacial recession in the Altai Mountains, Russia; increased snow depth and hardness, permafrost warming, and increased growing season length in sub-arctic Sweden; drying of ponds in Greenland; increased nutrient availability in Alaskan tundra ponds, and warming at most locations studied. Biotic changes ranged from relatively minor plant community change at two sites in Greenland to moderate change in the Yukon, and to dramatic increases in shrub and tree density on Herschel Island, and in subarctic Sweden. The population of geese tripled at one site in northeast Greenland where biomass in non-grazed plots doubled. A model parameterized using results from a BTF study forecasts substantial declines in all snowbeds and increases in shrub tundra on Niwot Ridge, Colorado over the next century. In general, results support and provide improved capacities for validating experimental manipulation, remote sensing, and modeling studies.     

Physical characterization of the fine particle emissions from commercial aircraft engines during the Aircraft Particle Emissions eXperiment (APEX) 1–3

The fine particulate matter (PM) emissions from nine commercial aircraft engine models were determined by plume sampling during the three field campaigns of the Aircraft Particle Emissions Experiment (APEX). Ground-based measurements were made primarily at 30 m behind the engine for PM mass and number concentration, particle size distribution, and total volatile matter using both time-integrated and continuous sampling techniques. The experimental results showed a PM mass emission index (EI) ranging from 10 to 550 mg kg^?1 fuel depending on engine type and test parameters as well as a characteristic U-shaped curve of the mass EI with increasing fuel flow for the turbofan engines tested. Also, the Teflon filter sampling indicated that ～40–80% of the total PM mass on a test-average basis was comprised of volatile matter (sulfur and organics) for most engines sampled. The number EIs, on the other hand, varied from ～10¹⁵ to 10¹⁷ particles kg^?1 fuel with the turbofan engines exhibiting a logarithmic decay with increasing fuel flow. Finally, the particle size distributions of the emissions exhibited a single primary mode that were lognormally distributed with a minor accumulation mode also observed at higher powers for all engines tested. The geometric (number) mean particle diameter ranged from 9.4 to 37 nm and the geometric standard deviation ranged from 1.3 to 2.3 depending on engine type, fuel flow, and test conditions.     

Species abundance distributions result from body size-energetics relationships

Abundance distributions are a central characteristic of ecosystems. Certain distributions have been derived from theoretical models of community organization, and therefore the fit of data to these distributions has been proposed as a test of these theories. However, it is shown here that the geometric sequence distribution can be derived directly from the empirical relationship between population density and body size, with the assumption of random or uniform body size distributions on a log scale (as holds at local scales). The geometric sequence model provides a good to excellent fit to empirical data. The presence of noise in the relationship between population density and body size creates a curve that begins to approximate a lognormal species abundance distribution as the noise term increases. For continental-scale data in which the body size distribution is not flat, the result of sampling tends again toward the lognormal. Repeat sampling over time smooths out species population fluctuations and damps out the noise, giving a more precise geometric sequence abundance distribution. It is argued that the direct derivation of this distribution from empirical relationships gives it priority over distributions derived from complex theoretical community models.     

A Bayesian approach to retransformation bias in transformed regression

Ecological data analysis often involves fitting linear or nonlinear equations to data after transforming either the response variable, the right side of the equation, or both, so that the standard suite of regression assumptions are more closely met. However, inference is usually done in the natural metric and it is well known that retransforming back to the original metric provides a biased estimator for the mean of the response variable. For the normal linear model, fit under a log-transformation, correction factors are available to reduce this bias, but these factors may not be generally applicable to all model forms or other transformations. We demonstrate that this problem is handled in a straightforward manner using a Bayesian approach, which is general for linear and nonlinear models and other transformations and model error structures. The Bayesian framework provides a predictive distribution for the response variable so that inference can be made at the mean, or over the entire distribution to incorporate the predictive uncertainty.     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.