Interactions between earthworms and arsenic in the soil environment: a review

Chemical pollution of the environment has become a major source of concern. In particular, many studies have investigated the impact of pollution on biota in the environment. Studies on metalliferous contaminated mine spoil wastes have shown that some soil organisms have the capability to become resistant to metal/metalloid toxicity. Earthworms are known to inhabit arsenic-rich metalliferous soils and, due to their intimate contact with the soil, in both the solid and aqueous phases, are likely to accumulate contaminants present in mine spoil. Earthworms that inhabit metalliferous contaminated soils must have developed mechanisms of resistance to the toxins found in these soils. The mechanisms of resistance are not fully understood; they may involve physiological adaptation (acclimation) or be genetic. This review discusses the relationships between earthworms and arsenic-rich mine spoil wastes, looking critically at resistance and possible mechanisms of resistance, in relation to soil edaphic factors and possible trophic transfer routes.     

Contamination of drinking water resources in the Mekong delta floodplains: arsenic and other trace metals pose serious health risks to population

This study presents a transnational groundwater survey of the 62,000 km(2) Mekong delta floodplain (Southern Vietnam and bordering Cambodia) and assesses human health risks associated with elevated concentrations of dissolved toxic elements. The lower Mekong delta generally features saline groundwater. However, where groundwater salinity is <1 g L(-)(1) Total Dissolved Solids (TDS), the rural population started exploiting shallow groundwater as drinking water in replacement of microbially contaminated surface water. In groundwater used as drinking water, arsenic concentrations ranged from 0.1-1340 microg L(-)(1), with 37% of the studied wells exceeding the WHO guidelines of 10 microg L(-)(1) arsenic. In addition, 50% exceeded the manganese WHO guideline of 0.4 mg L(-)(1), with concentrations being particularly high in Vietnam (range 1.0-34 mg L(-)(1)). Other elements of (minor) concern are Ba, Cd, Ni, Se, Pb and U. Our measurements imply that groundwater contamination is of geogenic origin and caused by natural anoxic conditions in the aquifers. Chronic arsenic poisoning is the most serious health risk for the ~2 million people drinking this groundwater without treatment, followed by malfunction in children's development through excessive manganese uptake. Government agencies, water specialists and scientists must get aware of the serious situation. Mitigation measures are urgently needed to protect the unaware people from such health problems.     

The avoidance response of fathead minnows to chemical alarm cues: understanding the effects of donor gender and breeding condition

Summary. All animals are vulnerable to predation at some point in their lives and consequently prey organisms often develop effective risk assessment systems. For many aquatic species predation risk assessment occurs through the use of olfactory cues, including predator odours and alarm cues from damaged or disturbed conspecifics. When aquatic species encounter conspecific alarm cues they may respond, or not, based on specific information including cue concentration, health and size of the conspecific donor and potentially the gender and breeding condition of the donor. Previous laboratory studies have demonstrated that fathead minnows (Pimephales promelas) fail to respond to the skin extracts of breeding male minnows. The purpose of the current study was to verify these early laboratory findings in the field as well as to further investigate the effect of female reproductive state and donor gender on the response of minnows to damage-release alarm cues. Our results indicate that male breeding condition has a significant effect on how minnows will respond to conspecific cues. Minnows showed avoidance of cues of female minnows and male minnows not in breeding condition, in comparison to cues of breeding male minnows and cues of male and female swordtails. Neither the gender of non-breeding minnows nor the reproductive state of female minnows influenced the avoidance of minnows to alarm cues.     

A general model for tagging on multiple component fisheries: an integration of age-dependent reporting rates and mortality estimation

A major objective of analyzing multiple year tag return data in fisheries is to estimate fishing and natural mortality rates which may vary by age class and calendar year. To do this one needs to be able to estimate the reporting rates for the tags recovered. Some fisheries such as that for Southern Bluefin Tuna (Thunnus maccoyii) have multiple components with potentially different reporting rates for the tag returns. In this paper we develop a general model for multi-cohort, multi-year tag return analyses where there are multiple components to the fishery with potentially different reporting rates. We require the assumption that one component has a reporting rate of 100% (i.e., this could be the component of a boat based fishery where scientific observers are present). We show further how it is possible to partition the overall likelihood developed into two conditionally independent components. The first component of the likelihood is the standard multinomial likelihood that allows estimation of fishing and natural mortality rates. It uses the tag return matrix summed over all the components of the fishery. It requires an average reporting rate for the tag returns (where the average reporting rate is a weighted average of the individual reporting rates of the different components). The second component is also multinomial for the individual component tag returns and allows us to estimate individual component reporting rates. However, this requires that we augment our second component tag return likelihood with a catch data likelihood for the corresponding components. The methodology is illustrated on some Southern Bluefin Tuna tagging and catch data. We also discuss important model assumptions and give suggestions for future research including the integration of tag-return and catch at age data analyses.     

Minimum viable metapopulation size, extinction debt, and the conservation of a declining species.

A key question facing conservation biologists is whether declines in species' distributions are keeping pace with landscape change, or whether current distributions overestimate probabilities of future persistence. We use metapopulations of the marsh fritillary butterfly Euphydryas aurinia in the United Kingdom as a model system to test for extinction debt in a declining species. We derive parameters for a metapopulation model (incidence function model, IFM) using information from a 625-km2 landscape where habitat patch occupancy, colonization, and extinction rates for E. aurinia depend on patch connectivity, area, and quality. We then show that habitat networks in six extant metapopulations in 16-km2 squares were larger, had longer modeled persistence times (using IFM), and higher metapopulation capacity (lambdaM) than six extinct metapopulations. However, there was a > 99% chance that one or more of the six extant metapopulations would go extinct in 100 years in the absence of further habitat loss. For 11 out of 12 networks, minimum areas of habitat needed for 95% persistence of metapopulation simulations after 100 years ranged from 80 to 142 ha (approximately 5-9% of land area), depending on the spatial location of habitat. The area of habitat exceeded the estimated minimum viable metapopulation size (MVM) in only two of the six extant metapopulations, and even then by only 20%. The remaining four extant networks were expected to suffer extinction in 15-126 years. MVM was consistently estimated as approximately 5% of land area based on a sensitivity analysis of IFM parameters and was reduced only marginally (to approximately 4%) by modeling the potential impact of long-distance colonization over wider landscapes. The results suggest a widespread extinction debt among extant metapopulations of a declining species, necessitating conservation management or reserve designation even in apparent strongholds. For threatened species, metapopulation modeling is a potential means to identify landscapes near to extinction thresholds, to which conservation measures can be targeted for the best chance of success.     

Book reviews

Ecological Economics: The Science and Management of Sustainability

R. Costanza (Ed.)

New York, Columbia, 1991, 515 pp.

Environmental Auditing: The Challenge of the 1990s

Banff Centre for Management

Calgary, University of Calgary Press, 1992, 236 pp, pb.

Interpreting Nature: Cultural Constructions of the Environment

I. G. Simmons

London, Routledge, 1993, 200 pp., £40 hb, £12.99 pb     

Iowa Statewide Stream Nitrate Load Calculated Using In Situ Sensor Network

Various techniques exist to estimate stream nitrate loads when measured concentration data are sparse. The inherent uncertainty associated with load estimation, however, makes tracking progress toward water quality goals more difficult. We used high‐frequency, in situ nitrate sensors strategically deployed across the agricultural state of Iowa to evaluate 2016 stream concentrations at 60 sites and loads at 35 sites. The generated data, collected at an average of 225 days per site, show daily average nitrate‐N yields ranging from 12 to 198 g/ha, with annual yields as high as 53 kg/ha from the intensely drained Des Moines Lobe. Thirteen of the sites that capture water from 82.5% of Iowa's area show statewide nitrate‐N loading in 2016 totaled 477 million kg, or 41% of the load delivered to the Mississippi–Atchafalaya River Basin (MARB). Considering the substantial private and public investment being made to reduce nitrate loading in many states within the MARB, networks of continuous, in situ measurement devices as described here can inform efforts to track year‐to‐year changes in nitrate load related to weather and conservation implementation. Nitrate and other data from the sensor network described in this study are made publicly available in real time through the Iowa Water Quality Information System.