Forecast-based action for conservation

Extreme weather events pose an immediate threat to biodiversity, but existing conservation strategies have limitations. Advances in meteorological forecasting and innovation in the humanitarian sector provide a possible solution—forecast-based action (FbA). The growth of ecological forecasting demonstrates the huge potential to anticipate conservation outcomes, but a lack of operational examples suggests a new approach is needed to translate forecasts into action. FbA provides such a framework, formalizing the use of meteorological forecasts to anticipate and mitigate the impacts of extreme weather. Based on experience from the humanitarian sector, I suggest how FbA could work in conservation, demonstrating key concepts using the theoretical example of heatwave impacts on sea turtle embryo mortality, and address likely challenges in realizing FbA for conservation, including establishing a financing mechanism, allocating funds to actions, and decision-making under uncertainty. FbA will demand changes in conservation research, practice, and governance. Researchers must increase efforts to understand the impacts of extreme weather at more immediate and actionable timescales and should coproduce forecasts of such impacts with practitioners. International conservation funders should establish systems to fund anticipatory actions based on uncertain forecasts.     

Designing a composite indicator for road safety

This study set out to develop a composite road safety indicator for benchmarking countries’ road safety performance, which would combine the main layers of the road safety pyramid which describes the complex nature of road safety activities, performance and outcomes. Four groups of basic safety indicators were considered, which refer to: policy performance (road safety programmes), final road safety outcomes (fatality rates, scope of traffic injury), intermediate outcomes (wearing rates of seat belts, crashworthiness and composition of vehicle fleet, alcohol-impaired driving), and background characteristics of countries (motorization level, population density). The analysis used the data collected for 27 European countries. Weights based on statistical models were used to combine the basic indicators into a composite one. Principal Component Analysis and Common Factor Analysis weighting were examined. The composite indicators, estimated by several methods, enabled us to rank and group the countries according to their safety performance.The analysis revealed that the countries’ ranking based on the composite indicators is not necessarily similar to the traditional ranking of countries based on fatality rates only. Furthermore, it was observed that the indicators belonging to the final outcomes and intermediate outcomes are not uniform in their behaviour. Indicators which were found to be more consistent and influential and termed a ‘core set of basic indicators’ are recommended for future uses. The general conclusion is that the design of a composite road safety indicator in which relevant information from the different components of the road safety pyramid has been captured and weighted is realistic and meaningful. Such an indicator gives a more enriched picture of road safety than a ranking based only on fatality rates, which is the common practice at present. Grouping countries in this process is promising and seems to be preferable to simply ranking countries.     

No net loss for people and biodiversity

Governments, businesses, and lenders worldwide are adopting an objective of no net loss (NNL) of biodiversity that is often partly achieved through biodiversity offsetting within a hierarchy of mitigation actions. Offsets aim to balance residual losses of biodiversity caused by development in one location with commensurate gains at another. Although ecological challenges to achieve NNL are debated, the associated gains and losses for local stakeholders have received less attention. International best practice calls for offsets to make people no worse off than before implementation of the project, but there is a lack of clarity concerning how to achieve this with regard to people's use and nonuse values for biodiversity, especially given the inevitable trade-offs when compensating biodiversity losses with gains elsewhere. This is particularly challenging for countries where poor people depend on natural resources. Badly planned offsets can exacerbate poverty, and development and offset impacts can vary across spatial-temporal scales and by location, gender, and livelihood. We conceptualize the no-worse-off principle in the context of NNL of biodiversity, by exploring for whom and how the principle can be achieved. Changes in the spatial and temporal distribution of biodiversity-related social impacts of a development and its associated offset can lead to social inequity and negatively impact people's well-being. The level of aggregation (regional, village, interest group, household, and individual) at which these social impacts are measured and balanced can again exacerbate inequity in a system. We propose that a determination that people are no worse off, and preferably better off, after a development and biodiversity offset project than they were before the project should be based on the perceptions of project-affected people (assessed at an appropriate level of aggregation); that their well-being associated with biodiversity losses and gains should be at least as good as it was before the project; and that this level of well-being should be maintained throughout the project life cycle. Employing this principle could help ensure people are no worse off as a result of interventions to achieve biodiversity NNL.     

Sympatric species of threespine stickleback differ in their performance in a spatial learning task

Increasing evidence suggests that cognitive function is under selection in diverse taxa and that this results in different cognitive abilities in taxa experiencing different selective environments. For example, species inhabiting spatially complex environments might be expected to have good spatial learning ability. We investigated whether local habitat conditions influence learning by comparing the performance of two recently diverged species of threespine stickleback (Gasterosteus aculeatus complex) in a spatial learning task. The two species reside sympatrically in several lakes. Benthics occupy the spatially structured vegetated littoral zone, whereas limnetics occupy the spatially homogenous open-water pelagic zone. We trained fish to locate a hidden reward in a T-maze and asked whether they did so by learning a body-centred pattern of movement (turn left or right) or by using plant landmarks. Both benthics and limnetics used turn and landmark cues, but benthics learnt the task almost twice as quickly as limnetics. This difference is consistent with the hypothesis that benthic and limnetic sticklebacks are equipped with spatial learning abilities well suited to the spatial complexity of their littoral and pelagic habitats. Our findings add to the understanding of the evolution of learning.     

Migration of Cs in tributaries,lake water and sediment of Lago Maggiore (Italy,Switzerland) – analysis and comparison with Lago di Lugano and other lakes

This paper describes the behaviour of ¹³⁷Cs in Lago Maggiore and other pre-alpine lakes as a consequence of atmospheric nuclear weapons testing fallout and the fallout from the nuclear accident in Chernobyl. It presents data on the ¹³⁷Cs distribution in tributaries, lake water, bottom sediments and reveals the role of ¹³⁷Cs as a marker of the sedimentation processes. The run-off of ¹³⁷Cs from the watershed to the lake is described with a simple compartment model. Measurements of the activity concentration of ¹³⁷Cs in sediments are compared with the output of a model (diffusion–convection type) which describes the input of ¹³⁷Cs into and its vertical distribution within the sediment. Varying sedimentation rates (0.05–0.90 g (cm² y)⁻¹) in Lago Maggiore are compared with data of other authors. Sedimentation rates and total distribution coefficients (of about 10⁵ L kg⁻¹) in Lago Maggiore are discussed and compared with those of Lago di Lugano, Lake Constance, and Lake Vorsee.     

Gene expression of heat shock protein 70, interleukin-1β and tumor necrosis factor α as tools to identify immunotoxic effects on Xenopus laevis: a dose-response study with benzo[a]pyrene and its degradation products

The exposure to benzo[a]pyrene (B[a]P) results in an alteration of immune function in mammals and fish, and the analysis of cytokine mRNA levels has been suggested for predicting the immunomodulatory potential of chemicals. To obtain evidence of the innate immune responses to B[a]P in Xenopus laevis, the present study monitored the mRNA expression of interleukin 1-β (IL-1β), tumor necrosis factor α (TNF-α) and heat shock protein 70 (HSP70) in a laboratorial exposure. Tadpoles exposed to 8.36, 14.64, 89.06 and 309.47 μg/L of B[a]P,were used for detecting hsp70, IL-1β and TNF-α mRNA induction. A dose-response increase in the expression of hsp70 and IL-1β mRNA was found. The results of this study confirmed the use of hsp70 and IL-1β, but not TNF-α, as sensitive indicators of immunotoxic effect of B[a]P in X. laevis. Further research would be required for the validation of these endpoints.     

Pharmaceuticals on a sewage impacted section of a Mediterranean River (Llobregat River,NE Spain) and their relationship with hydrological conditions

Introduction  

Mediterranean rivers are characterized by a high flow variability, which is strongly influenced by the seasonal rainfall. When water scarcity periods occur, water flow, and dilution capacity of the river is reduced, increasing the potential environmental risk of pollutants. On the other hand, floods contribute to remobilization of pollutants from sediments. Contamination levels in Mediterranean rivers are frequently higher than in other European river basins, including pollution by pharmaceutical residues. Little attention has been paid to the transport behavior of emerging contaminants in surface waters once they are discharged from WWTP into a river. In this context, this work aimed to relate presence and fate of emerging contaminants with hydrological conditions of a typical Mediterranean River (Llobregat, NE Spain).     

A Risk-Based Approach to Evaluating Wildlife Demographics for Management in a Changing Climate: A Case Study of the Lewis’s Woodpecker

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species’ response to climate into conservation decisions. This is shown by taking advantage of species’ response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis’s Woodpecker (Melanerpes lewis) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis’s Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.     

Images of Environmental Management: Competing Metaphors in Focus Group Discussions of Swedish Environmental Quality Objectives

In managing environmental problems, several countries have chosen the management by objectives (MBO) approach. This paper investigates how focus group participants from the Swedish environmental administration used metaphors to describe the mode of organization needed to attain environmental objectives. Such analysis can shed light on how an MBO system is perceived by actors and how it works in practice. Although the Swedish government intended to stimulate broad-based cooperation among many actors, participants often saw themselves as located at a certain “level,” i.e., “higher” or “lower,” in the MBO system—that is, their conceptions corresponded to a traditional, hierarchical interpretation of MBO. Prepositions such as “in” and “out” contributed to feelings of inclusion and exclusion on the part of MBO actors. However, horizontal metaphors merged with vertical ones, indicating ongoing competition for the right to interpret how the system of environmental objectives should best be managed. The paper concludes that any organization applying MBO could benefit from discussing alternate ways of talking and thinking about its constituent “levels.”     

Characterization of spatially homogeneous regions based on temporal patterns of fine particulate matter in the continental United States

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.