Socioeconomic correlates of global mammalian conservation status

The main causes of biodiversity decline are related to human use of resources, which is ultimately triggered by the socioeconomic decisions made by individuals and nations. Characterizing the socioeconomic attributes of areas in which biodiversity is most threatened can help us identify decisions and conditions that promote the presence or absence of threats and potentially suggest more sustainable strategies. In this study we explored how diverse indicators of social and economic development correlate with the conservation status of terrestrial mammals within countries explicitly exploring hypothesized linear and quadratic relationships. First, comparing countries with and without threatened mammals we found that those without threatened species are a disparate group formed by European countries and Small Island Developing States (SIDS) with little in common besides their slow population growth and a past of human impacts. Second, focusing on countries with threatened mammals we found that those with a more threatened mammalian biota have mainly rural populations, are predominantly exporters of goods and services, receive low to intermediate economic benefits from international tourism, and have medium to high human life expectancy. Overall, these results provide a comprehensive characterization of the socioeconomic profiles linked to mammalian conservation status of the world's nations, highlighting the importance of transborder impacts reflected by the international flux of goods, services and people. Further studies would be necessary to unravel the actual mechanisms and threats that link these socioeconomic profiles and indicators with mammalian conservation. Nevertheless, this study presents a broad and complete characterization that offers testable hypotheses regarding how socioeconomic development associates with biodiversity.

Experiences with sustainability indicators and stakeholder participation: A case study relating to a 'Blue Plan' project in Malta

The practical application of systemic sustainability analysis (SSA; Bell and Morse, 1999) as applied in-a project instigated and managed by 'Blue Plan', one of the regional activity centres of the Mediterranean Action Plan, is set out and explained in this paper. The context in which SSA was applied and adapted to SPSA (systemic and prospective sustainability analysis). is described in the Mediterranean, primarily in Malta. The SSA process is summarized, its extension and linkage to the prospective approach is described and the comments of stakeholders in the context are added. Some preliminary outcomes are suggested. The pauticular focus of the paper is on the lessons learned from doing SSA/SPSA within a classic blueprint project framework. It is-not assumed that SSA/SPSA is 'finished' or 'definitive'. Rather, we suggest that it is a developing and changing approach that practitioners can adapt and change to meet the specific needs of the circumstances that confront them. Copyright (C) 2004 John Wiley & Sons, Ltd and ERP Environment.

Microbial and biochemical soil quality indicators and their potential for differentiating areas under contrasting agricultural management regimes

The aim of this study was to examine interrelationships between functional biochemical and microbial indicators of soil quality, and their suitability to differentiate areas under contrasting agricultural management regimes. The study included five 0.8 ha areas on a sandy-loam soil which had received contrasting fertility and cropping regimes over a 5 year period. These were organically managed vegetable, vegetable -cereal and arable rotations, an organically managed grass clover ley, and a conventional cereal rotation. The organic areas had been converted from conventional cereal production 5 years prior to the start of the study. All of the biochemical analyses, including light fraction organic matter (LFOM) C and N, labile organic N (LON), dissolved organic N and water-soluble carbohydrates showed significant differences between the areas, although the nature of the relationships between the areas varied between the different parameters, and were not related to differences in total soil organic matter content. The clearest differences were seen in LFOM C and N and LON, which were higher in the organic arable area relative to the other areas. In the case of the biological parameters, there were differences between the areas for biomass-N, ATP, chitin content, and the ratios of ATP: biomass and basal respiration: biomass. For these parameters, the precise relationships between the areas varied. However, relative to the conventionally managed area, areas under organic management generally had lower biomass-N and higher ATP contents. Arbuscular mycorrhizal fungus colonization potential was extremely low in the conventional area relative to the organic areas. Further, metabolic diversity and microbial community level physiological profiles, determined by analysis of microbial community metabolism using Biolog GN plates and the activities of eight key nutrient cycling enzymes, grouped the organic areas together, but separated them from the conventional area. We conclude that microbial parameters are more effective and consistent indicators of management induced changes to soil quality than biochemical parameters, and that a variety of biochemical and microbial analyses should be used when considering the impact of management on soil quality. (C) 2004 Elsevier Ltd. All rights reserved.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

Indicators of nitrate in wetland surface and soil-waters: interactions of vegetation and environmental factors

This paper describes a new bio-indicator method for assessing wetland ecosystem health: as such, the study is particularly relevant to current legislation such as the EU Water Framework Directive, which provides a baseline of the current status Of Surface waters. Seven wetland sites were monitored across northern Britain, with model construction data for predicting, eco-hydroloplical relationships collected from five sites during 1999, Two new sites and one repeat site were monitored during 2000 to provide model test data. The main growing season for the vegetation, and hence the sampling period, was May-August during both years. Seasonal mean concentrations of nitrate (NO3-) in surface and soil water samples during 1999 ranged from 0.01 to 14.07 mg N 1(-1), with a mean value of 1.01 mg N 1(-1). During 2000, concentrations ranged from trace level (<0.01 m- N 1(-1)) to 9.43 mg N 1(-1), with a mean of 2.73 mg N 1(.)(-1) Surface and soil-water nitrate concentrations did not influence plant species composition significantly across representative tall herb fen and mire communities. Predictive relationships were found between nitrate concentrations and structural characteristics of the wetland vegetation, and a model was developed which predicted nitrate concentrations from measures of plant diversity, canopy structure and density of reproductive structures. Two further models, which predicted stem density and density of reproductive structures respectively, utilised nitrate concentration as one of the independent predictor variables. Where appropriate, the models were tested using data collected during 2000. This approach is complementary to species-based monitoring, representing a useful and simple too] to assess ecological status in target wetland systems and has potential for bio-indication purposes.

Putting the pieces back together again: an illustration of the problem of interpreting development indicators using an African case study

Indicators are commonly recommended as tools for assessing the attainment of development, and the current vogue is for aggregating a number of indicators together into a single index. It is claimed that such indices of development help facilitate maximum impact in policy terms by appealing to those who may not necessarily have technical expertise in data collection, analysis and interpretation. In order to help counter criticisms of over-simplification, those advocating such indices also suggest that the raw data be provided so as to allow disaggregation into component parts and hence facilitate a more subtle interpretation if a reader so desires. This paper examines the problems involved with interpreting indices of development by focusing on the United Nations Development Programmes (UNDP) Human Development Index (HDI) published each year in the Human Development Reports (HDRs). The HDI was intended to provide an alternative to the more economic based indices, such as GDP, commonly used within neo-liberal development agendas. The paper explores the use of the HDI as a gauge of human development by making comparisons between two major political and economic communities in Africa (ECOWAS and SADC). While the HDI did help highlight important changes in human development as expressed by the HDI over 10 years, it is concluded that the HDI and its components are difficult to interpret as methodologies have changed significantly and the 'averaging' nature of the HDI could hide information unless care is taken. The paper discusses the applicability of alternative models to the HDI such as the more neo-populist centred methods commonly advocated for indicators of sustainable development. (C) 2003 Elsevier Ltd. All rights reserved.

The geography of tyranny and despair: development indicators and the hypothesis of genetic inevitability of national inequality

Development geography has long sought to understand why inequalities exist and the best ways to address them. Dependency theory sets out an historical rationale for under development based on colonialism and a legacy of developed core and under-developed periphery. Race is relevant in this theory only insofar that Europeans are white and the places they colonised were occupied by people with darker skin colour. There are no innate biological reasons why it happened in that order. However, a new theory for national inequalities proposed by Lynn and Vanhanen in a series of publications makes the case that poorer countries have that status because of a poorer genetic stock rather than an accident of history. They argue that IQ has a genetic basis and IQ is linked to ability. Thus races with a poorer IQ have less ability, and thus national IQ can be positively correlated with performance as measured by an indicator like GDP/capita. Their thesis is one of despair, as little can be done to improve genetic stock significantly other than a programme of eugenics. This paper summarises and critiques the Lynn and Vanhanen hypothesis and the assumptions upon which it is based, and uses this analysis to show how a human desire to simplify in order to manage can be dangerous in development geography. While the attention may naturally be focused on the 'national IQ' variables as a proxy measure of 'innate ability', the assumption of GDP per capita as an indicator of 'success' and 'achievement' is far more readily accepted without criticism. The paper makes the case that the current vogue for indicators, indices and cause-effect can be tyrannical.

Integrating methods for developing sustainability indicators that can facilitate learning and action

Bossel's (2001) systems-based approach for deriving comprehensive indicator sets provides one of the most holistic frameworks for developing sustainability indicators. It ensures that indicators cover all important aspects of system viability, performance, and sustainability, and recognizes that a system cannot be assessed in isolation from the systems upon which it depends and which in turn depend upon it. In this reply, we show how Bossel's approach is part of a wider convergence toward integrating participatory and reductionist approaches to measure progress toward sustainable development. However, we also show that further integration of these approaches may be able to improve the accuracy and reliability of indicators to better stimulate community learning and action. Only through active community involvement can indicators facilitate progress toward sustainable development goals. To engage communities effectively in the application of indicators, these communities must be actively involved in developing, and even in proposing, indicators. The accuracy, reliability, and sensitivity of the indicators derived from local communities can be ensured through an iterative process of empirical and community evaluation. Communities are unlikely to invest in measuring sustainability indicators unless monitoring provides immediate and clear benefits. However, in the context of goals, targets, and/or baselines, sustainability indicators can more effectively contribute to a process of development that matches local priorities and engages the interests of local people.

Negative correlations between control performance and verbalizable knowledge: indicators for implicit learning in process control tasks?

Negative correlations between task performance in dynamic control tasks and verbalizable knowledge, as assessed by a post-task questionnaire, have been interpreted as dissociations that indicate two antagonistic modes of learning, one being “explicit”, the other “implicit”. This paper views the control tasks as finite-state automata and offers an alternative interpretation of these negative correlations. It is argued that “good controllers” observe fewer different state transitions and, consequently, can answer fewer post-task questions about system transitions than can “bad controllers”. Two experiments demonstrate the validity of the argument by showing the predicted negative relationship between control performance and the number of explored state transitions, and the predicted positive relationship between the number of explored state transitions and questionnaire scores. However, the experiments also elucidate important boundary conditions for the critical effects. We discuss the implications of these findings, and of other problems arising from the process control paradigm, for conclusions about implicit versus explicit learning processes.

Grassland leafhoppers (Hemiptera: Auchenorrhyncha) as indicators of habitat condition - a comparison of between-site and between-year differences in assemblage composition

The Auchenorrhyncha (leafhoppers) show great potential as indicators of grassland habitat quality, which would make them useful as a conservation tool. However, they are known to have labile populations. The relative importance of site identity and the year of sampling in the composition of leafhopper assemblages on chalk grassland are assessed for two sets of sites sampled twice. The study included a total of 95 sites (one set of 54, the other of 41), and demonstrated that for both sets the vegetation community and geographical location had high explanatory value, while the influence of year was small. The conclusion is that, notwithstanding population fluctuations, the leafhopper assemblages are a good indicator of habitat quality, and represent a potentially valuable tool in grassland conservation and restoration.