Exploring new ways of assessing the effect of regulation on environmental management

Studies indicate that while a variety of factors positively influence voluntary environmental management, regulatory pressures are among the most important. However, most research examines samples representing large manufacturers or single industries, essentially assuming a level of regulatory constraint. Using a sample of heterogeneous facilities, this study finds that facilities can be classified according to the level of regulatory constraint, and that group membership impacts the choice of environmental management strategy when assessed within a utility maximization framework. More extensively regulated facilities implement more individual environmental management practices, but participate in fewer formal voluntary environmental programs (VEPs), compared to other facilities.     

Distinguishing Between Interference and Exploitation Competition for Shelter in a Mobile Fish Population

Understanding the functional significance of shelter for animal populations requires knowledge of the behavioural mechanisms that govern the dynamics of shelter use. Exploitation of shelters may be impeded by mutual interference, yet interference competition can be difficult to distinguish from exploitation competition. We used bullheads (Cottus gobio) as a model system of mobile fish to investigate the effect of intraspecific competition on shelter use. A series of field experiments was conducted under controlled conditions of shelter availability and population density. For each experiment, the location of each individual fish was observed over a period of 10 days. We then constructed a continuous-time Markov-chain model for the movement of fish between shelters and the open stream, which explicitly parameterised exploitation competition and interference competition for shelter and which accounted for two different size-classes of fish. By using a stochastic rather than a deterministic model, we were able to account for the distribution of fish across shelters, and not just the average occupation. Analysis of the model showed strong evidence of exploitation competition, which was highly dependent on body size, and an increased departure rate from shared shelters. Over and above exploitation, interference competition limited the ability of unsheltered fish to colonise vacant shelters at high population densities. Different formulations of the interference competition were compared using the Akaike Information Criterion. The formulation that best fitted the observations modelled interference competition as an increasing function of average shelter occupancy rather than population density per se.     

Vulnerability of exporting nations to the development of a carbon label in the United Kingdom

Carbon labels inform consumers about the amount of greenhouse gases (GHGs) released during the production and consumption of goods, including food. In the future consumer and legislative responses to carbon labels may favour goods with lower emissions, and thereby change established supply chains. This may have unintended consequences.We present the carbon footprint of three horticultural goods of different origins supplied to the United Kingdom market: lettuce, broccoli and green beans. Analysis of these footprints enables the characterisation of three different classes of vulnerability which are related to: transport, national economy and supply chain specifics.There is no simple relationship between the characteristics of an exporting country and its vulnerability to the introduction of a carbon label. Geographically distant developing countries with a high level of substitutable exports to the UK are most vulnerable. However, many developing countries have low vulnerability as their main exports are tropical crops which would be hard to substitute with local produce.In the short term it is unlikely that consumers will respond to carbon labels in such a way that will have major impacts in the horticultural sector. Labels which require contractual reductions in GHG emissions may have greater impacts in the short term.     

Challenges and opportunities for sustainability in regional universities: a case study in Mytilene,Greece

Regional Higher Education Institutions (HEIs) may contribute significantly to the promotion of sustainability through several means connected with their functioning. Nevertheless, several challenges can present themselves during the planning and implementation of such initiatives. The aim of this paper is to underline these limitations through the relevant literature and highlight their main consequences on the achievement of sustainability. An empirical study, investigating the perception of students regarding the constraints to achieving sustainability in a regional university of Greece, was conducted and is discussed in relation to the university's specific characteristics – its fragmented nature with campuses situated on five Aegean islands, its public status as well as its role in creating and dispersing knowledge in less developed areas of the country.     

Population and seasonal variation in response to prey calls by an eavesdropping bat

The fringe-lipped bat, Trachops cirrhosus, is an eavesdropping predator that hunts frogs and katydids by approaching these preys' sexual advertisement calls. In captivity, bats can rapidly learn to associate novel acoustic stimuli with food rewards. It is unknown how this learning ability is related to foraging behavior in the wild where prey and the calls that identify them vary over space and time. In two bat populations that differ in available prey species (Soberanía, Panama, and La Selva, Costa Rica), we presented wild-caught bats with frog calls, katydid calls, and control stimuli. Bats in Soberanía were significantly more responsive to complex calls and choruses of the túngara frog, Physalaemus pustulosus, than were bats in La Selva. La Selva bats were significantly more responsive to katydid calls (Steirodon sp.) than Soberanía bats. We also examined seasonal variation in bat response to prey cues. Bats were captured in Soberanía in dry and wet seasons and presented with the calls of a dry season breeding frog (Smilisca sila), a wet season breeding frog (P. pustulosus), and four katydid species. Bats captured in the dry season were significantly more responsive to the calls of S. sila than bats captured in the wet season, but there were no seasonal differences in response to the calls of P. pustulosus or the katydid calls. We demonstrate plasticity in the foraging behavior of this eavesdropping predator but also show that response to prey cues is not predicted solely by prey availability.     

Empirical realised niche models for British coastal plant species

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels.     

The species awareness index as a conservation culturomics metric for public biodiversity awareness

Although threats to global biodiversity are well known, slowing current rates of biodiversity loss remains a challenge. The Aichi targets set out 20 goals on which the international community should act to alleviate biodiversity decline, 1 of which (Target 1) aims to raise public awareness of the importance of biodiversity. Although conventional indicators for Target 1 are of low spatial and temporal coverage, conservation culturomics metrics show how biodiversity awareness can be quantified at the global scale. Following methods used for the Living Planet Index, we devised a species awareness index (SAI) to measure change in species awareness based on Wikipedia views. We calculated this index at the page level for 41,197 species listed by the International Union for Conservation of Nature (IUCN) across 10 Wikipedia languages and >2 billion views from 1 July 2015 to 30 March 2020. Bootstrapped indices for the page-level SAI showed that overall awareness of biodiversity increased marginally over time, although there were differences among taxonomic classes and languages. Among taxonomic classes, overall awareness increased fastest for reptiles and slowest for amphibians. Among languages, overall species awareness increased fastest for Japanese and slowest for Chinese and German users. Although awareness of species as a whole increased and was significantly higher for traded species, from January 2016 through January 2020, change in awareness appeared not to be strongly related to whether the species is traded or is a pollinator. As a data source for public biodiversity awareness, the SAI could be integrated into the Conservation International Biodiversity Engagement Indicator.