Pollution incidence and political jurisdiction: evidence from the TRI

Few issues are more contentious for local communities than industrial pollution. When local industries pollute, lawmakers and regulators must balance two primary concerns: economic prosperity and the environment. The role of political pressure is well documented in environmental policy. What is less clear is the role jurisdictional or boundary considerations play in determining the implementation of environmental laws. Anecdotal evidence suggests that local regulators are more lenient in their treatment of polluters when the incidence of pollution falls partially on those outside the state. One explanation for such behavior is that regulators take actions to maximize political support. This paper tests this jurisdictional model using toxics release inventory (TRI) data from 1987 to 1996. We find that facilities’ emissions into the air and water are systematically higher in counties that border other states. These results are consistent with the hypothesis that jurisdictional considerations are an important determinant of pollution incidence.     

State Intervention to Protect Endangered Species: Why History and Bad Luck Matter

Abstract: Illegal exploitation threatens the survival of many species, and anti-poaching legislation ("protection on paper") does not protect species. State enforcement is needed to support and supplement the formal status of endangered species, but state enforcement can be a source of instability leading to the demise of species if ad hoc rules are followed blindly. We demonstrate this with a model of poaching, wildlife, and government wildlife enforcement, but our findings apply more generally. Crucial assumptions of the dynamic model are that both poaching and enforcement effort increase or decrease whenever poaching effort and enforcement are relatively profitable or unprofitable activities, respectively. We found that multiple steady states may characterize the system's equilibrium. Depending on initial populations, the initial extent of state involvement, and random events, animal populations may be severely depleted or unexpectedly built up during transition phases. Our findings highlight the importance of history and luck in protecting endangered species.     

Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species

Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial–temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal–vertical movement model results with spatial–temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004–2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle–fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) ( https://www.upwell.org/sptw ), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial–temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.     

Lotka-Volterra competition models for sessile organisms

Markov models are widely used to describe the dynamics of communities of sessile organisms, because they are easily fitted to field data and provide a rich set of analytical tools. In typical ecological applications, at any point in time, each point in space is in one of a finite set of states (e.g., species, empty space). The models aim to describe the probabilities of transitions between states. In most Markov models for communities, these transition probabilities are assumed to be independent of state abundances. This assumption is often suspected to be false and is rarely justified explicitly. Here, we start with simple assumptions about the interactions among sessile organisms and derive a model in which transition probabilities depend on the abundance of destination states. This model is formulated in continuous time and is equivalent to a Lotka-Volterra competition model. We fit this model and a variety of alternatives in which transition probabilities do not depend on state abundances to a long-term coral reef data set. The Lotka-Volterra model describes the data much better than all models we consider other than a saturated model (a model with a separate parameter for each transition at each time interval, which by definition fits the data perfectly). Our approach provides a basis for further development of stochastic models of sessile communities, and many of the methods we use are relevant to other types of community. We discuss possible extensions to spatially explicit models.     

A framework for evaluating the impact of the IUCN Red List of threatened species

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species, a species extinction risk assessment tool, has been guiding conservation efforts for over 5 decades. It is widely assumed to have been instrumental in preventing species from moving closer to extinction and driving recoveries. However, the impact of the IUCN Red List in guiding conservation has not been evaluated. We conducted, transcribed, and coded interviews with experts who use the IUCN Red List across a range of sectors to understand how the list is used in conservation. We developed a theory of change to illustrate how and why change is expected to occur along causal pathways contributing to the long-term goal of the IUCN Red List and an evaluation framework with indicators for measuring the impact of the IUCN Red List in generating scientific knowledge, raising awareness among stakeholders, designating priority conservation sites, allocating funding and resources, influencing development of legislation and policy, and guiding targeted conservation action (key themes). Red-list assessments were the primary input leading to outputs (scientific knowledge, raised awareness), outcomes (better informed priority setting, access to funding and resource availability, improved legislation and policy), and impact (implemented conservation action leading to positive change) that have resulted in achievement of IUCN Red List goals. To explore feasibility of attributing the difference made by the IUCN Red List across themes, we studied increased scientific knowledge, raised awareness, access to funding and resource allocation, and increased conservation activity. The feasibility exploration showed increased scientific knowledge over time identified through positive trends in publications referring to the IUCN Red List in the literature; raised awareness of the list following high IUCN activity identified by peaks in online search activity; an increased proportion of conservation funding bodies requesting IUCN Red List status in the application process; and, based on interviews with Amphibian Specialist Group members, red-list assessments were essential in connecting relevant stakeholders and ensuring conservation action. Although we identified the IUCN Red List as a vital tool in global conservation efforts, it was challenging to measure specific impacts because of its ubiquitous nature. We are the first to identify the influence of the IUCN Red List on conservation.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

Obligate Cave Fauna of the 48 Contiguous United States

Abstract: We assembled a list of obligate cave-dwelling species and subspecies, their county distribution, and their provisional global conservation rank. A total of 927 species and 46 additional subspecies in 96 families exclusively from cave and associated subterranean habitats have been described in the 48 contiguous states of the United States. The terrestrial (troglobitic) species are concentrated in northeast Alabama (especially Jackson County), with other concentrations in Kentucky, Texas, Virginia, and West Virginia. Only 23 counties, comprising less than 1% of the land area of the 48 contiguous states, account for over 50% of the terrestrial species and subspecies. The aquatic (stygobitic) species are concentrated in Hays County, Texas, with other concentrations in Florida, Oklahoma, Texas, Virginia, and West Virginia. Only 18 counties, comprising less than 1% of the land area, account for over 50% of the aquatic species and subspecies. Endemism is high, with 54% of the species known from a single county. Approximately 95% of the species are listed by The Nature Conservancy as vulnerable or imperiled in the United States. These cave species comprise 50% of all vulnerable or imperiled species listed in databases of the Natural Heritage Program. Less than 4% of these subterranean species have federal status. Conservation can best be accomplished through habitat protection, which must include protection of the associated surface habitat.     

Lupine calls to Texas poison control centers, 1998–2005

Many lupine species (Genus Lupinus) contain toxic compounds, although the amount of these substances varies by the plant part and species. This investigation described the epidemiology of 138 lupine exposures reported to Texas poison centers during 1998–2005. Almost 88% of the lupine exposure calls occurred in March and April, and 90% of the calls came from the central portions of the state. Sixty-one percent of the calls involved female patients, and 91% of the patients were age <6 years. The lupine exposure occurred at the patient's own residence in 79% of the cases. Of the reported lupine exposures, 93% were handled outside of health care facilities, and, of those cases with a known medical outcome, few moderate or major effects, and no deaths, were reported. The most frequently noted clinical effect among cases during 2000–2005 was vomiting, affecting 8% of the cases. In conclusion, most reported lupine exposures in Texas came from the central parts of the state, occurred in spring, and involved young children. Typical reported lupine exposures in Texas were not likely to have adverse outcomes.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.     

中国环境管理中经济手段的应用

文章在说明环境管理中经济手段的分类、选择经济手段原则的同时，着重阐述中国环境管理中经济手段的使用现状，并提出相应的建议。     

Not Knowing, Not Recording, Not Listing: Numerous Unnoticed Mollusk Extinctions

Abstract:  Mollusks are the group most affected by extinction according to the 2007 International Union for Conservation of Nature (IUCN) Red List, despite the group having not been evaluated since 2000 and the quality of information for invertebrates being far lower than for vertebrates. Altogether 302 species and 11 subspecies are listed as extinct on the IUCN Red List. We reevaluated mollusk species listed as extinct through bibliographic research and consultation with experts. We found that the number of known mollusk extinctions is almost double that of the IUCN Red List. Marine habitats seem to have experienced few extinctions, which suggests that marine species may be less extinction prone than terrestrial and freshwater species. Some geographic and ecologic biases appeared. For instance, the majority of extinctions in freshwater occurred in the United States. More than 70% of known mollusk extinctions took place on oceanic islands, and a one-third of these extinctions may have been caused precipitously by introduction of the predatory snail Euglandina rosea. We suggest that assessment of the conservation status of invertebrate species is neglected in the IUCN Red List and not managed in the same way as for vertebrate species .     

Coastal zone management challenges in Ghana: issues associated with coastal sediment mining

Coastal erosion is a serious environmental problem that has caused the loss of private infrastructure and national assets along Ghana’s coast. Several hard engineering measures have thus been used to protect some communities and vital state assets when they became threatened. Regardless of this problem, sediment mining activities are increasingly practiced along most of Ghana’s coast, further exacerbating coastal erosion intensity and degrading coastal ecosystems. This paper provides an overview of the activities of coastal sediment miners along four administrative Districts in the Central Region of Ghana and identifies how issues arising from the practice are managed at the local community level as well as by state environmental regulators. The study uses a mixed-method approach, involving individual and group interviews, administration of a set of structured questionnaire and field observations, to identify coastal sediment mining and emerging management issues. Overall, three main categories of coastal sediment mining activities were identified in the area. Results indicate that coastal sediment mining is widely practiced by both commercial contractors and community members, giving rise to the high perception among residents that it is the reason for the degradation of the coastline in the studied areas. The study also established that state environmental regulators have weak inter-agency cooperation leading to poor enforcement of environmental laws and non-prosecution of offending individuals. The paper suggests that since each identified sediment mining activity has its own peculiar issues and mode of operation, coastal managers should address each category independently in order to derive lasting impacts in curtailing the practice.     

Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (Athene cunicularia hypugaea) as a case study

We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls (Athene cunicularia hypugaea) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals.     

Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters

Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently reencountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.     

Extinction risk of the endemic vascular flora of Kauai,Hawaii, based on IUCN assessments

The International Union for Conservation of Nature's Red List of Threatened Species (IUCN Red List) is the world's most comprehensive information source on the global conservation status of species. Governmental agencies and conservation organizations increasingly rely on IUCN Red List assessments to develop conservation policies and priorities. Funding agencies use the assessments as evaluation criteria, and researchers use meta-analysis of red-list data to address fundamental and applied conservation science questions. However, the circa 143,000 IUCN assessments represent a fraction of the world's biodiversity and are biased in regional and organismal coverage. These biases may affect conservation priorities, funding, and uses of these data to understand global patterns. Isolated oceanic islands are characterized by high endemicity, but the unique biodiversity of many islands is experiencing high extinction rates. The archipelago of Hawaii has one of the highest levels of endemism of any floristic region; 90% of its 1367 native vascular plant taxa are classified as endemic. We used the IUCN's assessment of the complete single-island endemic (SIE) vascular plant flora of Kauai, Hawaii, to assess the proportion and drivers of decline of threatened plants in an oceanic island setting. We compared the IUCN assessments with federal, state, and other local assessments of Kauai species or taxa of conservation concern. Finally, we conducted a preliminary assessment for all 1044 native vascular plants of Hawaii based on IUCN criterion B by estimating area of occupancy, extent of occurrence, and number of locations to determine whether the pattern found for the SIE vascular flora of Kauai is comparable to the native vascular flora of the Hawaiian Islands. We compared our results with patterns observed for assessments of other floras. According to IUCN, 256 SIE vascular plant taxa are threatened with extinction and 5% are already extinct. This is the highest extinction risk reported for any flora to date. The preliminary assessment of the native vascular flora of Hawaii showed that 72% (753 taxa) is threatened. The flora of Hawaii may be one of the world's most threatened; thus, increased and novel conservation measures in the state and on other remote oceanic islands are urgently needed.     

Indicators of ecosystem function identify alternate states in the sagebrush steppe

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.     

Voluntary environmental regulation in developing countries: Mexico’s Clean Industry Program

Because conventional command-and-control environmental regulation often performs poorly in developing countries, policymakers are increasingly experimenting with alternatives, including voluntary regulatory programs. Research in industrialized countries suggests that such programs are sometimes ineffective, because they mainly attract relatively clean participants free-riding on unrelated pollution control investments. We use plant-level data on more than 100,000 facilities to analyze the Clean Industry Program, Mexico’s flagship voluntary regulatory initiative. We seek to identify the drivers of participation and to determine whether the program improves participants’ environmental performance. Using data from the program’s first decade, we find that plants recently fined by environmental regulators were more likely to participate, but that after graduating from the program, participants were not fined at a substantially lower rate than nonparticipants. These results suggest that although the Clean Industry Program attracted dirty plants under pressure from regulators, it did not have a large, lasting impact on their environmental performance.     

Ten years of contested enforcement of the Forest Law in Salta,Argentina. The role of land-change science and political ecology

ABSTRACT

In this study, we present a critical account of the enforcement of the Forest Law in the Province of Salta, Argentina. We discuss whether the objectives of this law were accomplished and we analyze the role that some technical tools, coupled with specific theoretical approaches, could play in its future enforcement. We illustrate our analysis with data from a case study in the Chaco region of this Province. We identified, mapped and analyzed land claims by indigenous communities and small-scale agricultural producers, and large-scale land acquisitions, and we discuss how these two variables could be used to improve the technical accuracy and the social legitimacy of the zoning map required by the Forest Law. We conclude that a balanced combination of land-change science methods and political ecology can be useful to improve the fairness of decision-making processes and the sustainability of social-environmental governance in agricultural frontiers.     

An environmental assessment of enhanced oil recovery

The objective of this assessment is to quantify some of the environmental effects of a significant increase in United States oil production by tertiary or enhanced oil recovery (EOR) methods. The problems associated with each EOR technology are discussed and controls and regulations are briefly summarised. A tertiary oil production scenario for the United States was developed focussing only on mainland fields in the lower 48 states. It included all of the EOR methods expected to be in use during the next two decades. The environmental impacts, including water requirements, air emissions and generation of solid wastes, are then scaled to this scenario. The effects of control technologies and state regulations are considered. A comparison is also made between the impacts of EOR as an energy source and impacts associated with coal and synthetic fuels which concludes that EOR is preferable in many respects. There are environmental risks associated with EOR technologies, specific projects and specific fields in the production scenario; however, most problems are solvable by responsible regulation, enforcement of regulations and application of the best professional engineering by project operators.     

A 200-year perspective on alternative stable state theory and lake management from a biomanipulated shallow lake

Multiple stressors to a shallow lake ecosystem have the ability to control the relative stability of alternative states (clear, macrophyte-dominated or turbid, algal-dominated). As a consequence, the use of remedial biomanipulations to induce trophic cascades and shift a turbid lake to a clear state is often only a temporary solution. Here we show the instability of short-term manipulations in the shallow Lake Christina (Minnesota, USA) is governed by the long-term state following a regime shift in the lake. During the modern, managed period of the lake, three top-down manipulations (fish kills) were undertaken inducing temporary (5-10 years) unstable clear-water states. Paleoecological remains of diatoms, along with proxies of primary production (total chlorophyll a and total organic carbon accumulation rate) and trophic state (total P) from sediment records clearly show a single regime shift in the lake during the early 1950s; following this shift, the functioning of the lake ecosystem is dominated by a persistent turbid state. We find that multiple stressors contributed to the regime shift. First, the lake began to eutrophy (from agricultural land use and/or increased waterfowl populations), leading to a dramatic increase in primary production. Soon after, the construction of a dam in 1936 effectively doubled the depth of the lake, compounded by increases in regional humidity; this resulted in an increase in planktivorous and benthivorous fish reducing phytoplankton grazers. These factors further conspired to increase the stability of a turbid regime during the modern managed period, such that switches to a clear-water state were inherently unstable and the lake consistently returned to a turbid state. We conclude that while top-down manipulations have had measurable impacts on the lake state, they have not been effective in providing a return to an ecosystem similar to the stable historical period. Our work offers an example of a well-studied ecosystem forced by multiple stressors into a new long-term managed period, where manipulated clear-water states are temporary, managed features.