Raumbezug in der ökosystemaren Umweltbeobachtung

Using the example of the transboundary Biosphere Reserve Rhone, experiments were performed and expounded upon with regard to the concept of ‘integrated monitoring’. The paper describes the components of a step-by-step harmonisation of data sampling and analysis procedures. Special emphasis is given to topics dealing with suitable methods for a sound selection of areas and plots to be monitored, as well as on rules for the spatial integration and generalisation of sampling results. As tools for this purpose the concept of ‘integrated monitoring’ uses the federal ‘Classification System of Ecoregions’ (Standortökologische Raumgliederung) and geostatistical methods for the spatial integration of existing monitoring programmes and sampling grids. Further, the paper outlines how to judge the development of water catchment areas using existing data from hydrological analyses and by means of an ecosystem-oriented water balance model.     

Impacts of residential development on vegetation cover for a remote coastal barrier in the Outer Banks of North Carolina, USA

Coastal barrier environments are heavily influenced by human activities yet there are few examples of landscape ecological work investigating human dimensions of settlement disturbance patterns and processes. We investigated the impacts of residential development on vegetation cover for a remote roadless coastal barrier in Carova, North Carolina that is subject to policies from the federal to local levels and addressed three research questions: How has the region’s the policy history influenced patterns of residential parcel development? What are the spatial and temporal patterns of parcel development? How has development impacted patterns of barrier vegetation cover? We traced the influences of the federal 1982 Coastal Barrier Resources Act (CBRA) designed to discourage development in risky coastal areas as well as state/local coastal policies and employed remote sensing change detection, NDVI analysis and spatial analysis and regression techniques. Results showed an acceleration of new housing structures since 1990, contrary to the intended effects of CBRA. An estimated vegetation cover loss of 437 m² was associated with each newly developed parcel. NDVI varied along spatial and temporal gradients with more recent development having lower NDVI than older development. Recently developed parcels were larger in area, closer to the beach, and contained houses with larger footprints compared to older developed parcels. Our approach represents a place-based analytical framework for coastal barrier landscapes. Beyond the Carova case study, adopting such an approach coupling natural and human systems for the entire eastern US barrier system requires defining a comprehensive set of coastal barrier spatial units to enable typological classification and subsequent systematic investigation to inform debates regarding coastal ecosystem services and sustainability.     

It takes more than a village: the challenges of co-management in Uganda's fishery and forestry sectors

Decentralisation policies in least developed countries have emerged in response to failed centralised natural resource governance programmes because high-value natural resources are distributed unequally, with central governments often reaping more than local-level users. Current natural resource governance institutions have been created to remedy the problems that central governments formerly posed. Here, we argue that Uganda's forestry and fishery resources are biologically diverse and thus amenable to current decentralised management programmes, provided that there is compromise between market values and local cultural and subsistence values and uses. We observe, however, Uganda's current institutional arrangement favours the former over the latter and determine that successful natural resource decentralisation requires strengthening local-level natural resource institutions with increased fiscal flow, enforcement, monitoring and judicial powers. A strong and reliable partnership between local-level resource users and the central government is necessary for this to occur.     

The potential for citizen science to produce reliable and useful information in ecology

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.     

Monitoring of the Fate, Transport, and Effects of Sewage Sludge Disposed at the 106-Mile Deepwater Municipal Sludge Dump Site

Since 1985, the US Environmental Protection Agency (EPA) has conducted monitoring studies to determine the transport, fate, and effects of sewage sludge dumped at the 106-Mile Deepwater Municipal Sludge Dump Site (106-Mile Site). This paper describes EPA's 106-Mile Site monitoring activities and the results from six oceanographic surveys of the Site. Surveys have been conducted to track sewage sludge plumes and monitor dispersion and settling characteristics; study plume toxicity and contaminant levels; search for sludge and sludge constituents in surface waters in the area of the Site up 74 km (40 nautical miles) away; maintain a stationary real-time current meter near the Site; deploy and retrieve approximately 50 sediment traps and 17 current meters on 10 arrays from Hudson Canyon south to Delaware Canyon, at depths ranging from 1500 to 2800 m; and deploy satellite-tracked drifters. Results of studies completed to date have provided field data on the chemical and physical behaviour of sludge discharge plumes. Short-term persistence of sludge particles in surface waters above the pycnocline was observed and advection of sludge material from the Site may be rapid, in many cases on the order of hours. A suggestion that removal of sludge material from the surface mixed layer at the Site occurs more from horizontal mixing and advection than from vertical transport processes is supported by the data. Finally, monitoring results have provided data for assessment of permit compliance and for development of additional monitoring to detect far-field transport and long-term impacts - monitoring efforts relative to these concetns continue.     

A reclamation demonstration project at an abandoned deep mine

This project involves an evaluation of the reclamation process at a typical abandoned deep coal mine in the Midwest, U.S.A. The reclamation process included determining the final land use, collection of preconstruction environmental data, development of detailed construction plans, and implementation of the construction plans. A multidisciplinary approach is being used to evaluate post-construction conditions of the site. Current investigations are monitoring groundwater, surface water quality, aquatic ecosystems, revegetation, soil characteristics, erosion and runoff, soil microbial populations, wildlife, and economic effects of the reclamation. Data collected to date indicate a significant improvement in overall environmental quality, a substantial increase in the economic potential of the site and adjacent properties, and a genuine enhancement of the entire area's aesthetic value. This project will also provide design data for future reclamation efforts of this type.This project is financially supported by the following agencies: U.S. Department of Energy, Contract No. W31-109-Eng-38; Abandoned Mined Land Reclamation Council, State of Illinois Contract No. 31-109-38-3694L; Illinois Institute of Natural Resources, Contract No. 31-109-38-3702L.     

Orchestrating Ecosystem Management: Challenges and Lessons from Sequoia National Forest

Abstract: Numerous agencies and organizations have adopted the concept of ecosystem management as a guiding principle in natural resource management. Despite this widespread interest, no single definition of ecosystem management has been accepted, and there are no specific guidelines or standards by which to apply the concept. I examined how one federal agency, the U.S. Forest Service, is applying the principles of ecosystem management at a local level. I present a case study examining management of giant sequoia (   Sequoiadendron giganteum ) in Sequoia National Forest, California, to illuminate the challenges of practicing ecosystem management by associating on-the-ground management activities with ecosystem management themes, characteristics, and mechanisms identified in academic, industry, and agency literature. Experience at Sequoia National Forest suggests that the application of ecosystem management is compromised by poor relations between managers and stakeholders, multifarious policy requirements, budgetary uncertainty, and limited ecological research on which to base management decisions. To facilitate successful application of ecosystem management in the future, I recommend that managers (1) build confidence and trust in the process, (2) acknowledge bias, (3) reconcile policy and funding constraints with long-term planning, (4) invest in scientific research, data collection, and monitoring capacity, and (5) explore the relationship between values and science. These recommendations, although based on the U.S. Forest Service experience, are relevant to natural resource management in general.     

Current Trends in Plant and Animal Population Monitoring

Abstract:  Animal and plant population monitoring programs are critical for identifying species at risk, evaluating the effects of management or harvest, and tracking invasive and pest species. Nevertheless, monitoring activities are highly decentralized, which makes it difficult for researchers or conservation planners to get a good general picture of what real-world monitoring programs actually entail. We used a Web-based survey to collect information on population monitoring programs. The survey focused on basic questions about each program, including motivations for monitoring, types of data being collected, spatiotemporal design of the program, and reasons for choosing that design. We received responses from 311 people involved in monitoring of various species and used these responses to summarize ongoing monitoring efforts. We also used responses to determine whether monitoring strategies have changed over time and whether they differed among monitoring agencies. Most commonly, monitoring entailed collection of count data at multiple sites with the primary goal of detecting trends. But we also found that goals and strategies for monitoring appeared to be diversifying, that area-occupied and presence–absence approaches appeared to be gaining in popularity, and that several other promising approaches (monitoring to reduce parameter uncertainty, risk-based monitoring, and directly linking monitoring data to management decisions) have yet to become widely established. We suggest that improved communication between researchers studying monitoring designs and those who are charged with putting these designs into practice could further improve monitoring programs and better match sampling designs to the objectives of monitoring programs.     

A Bayesian hierarchical framework for calibrating aquatic biogeochemical models

Model practitioners increasingly place emphasis on rigorous quantitative error analysis in aquatic biogeochemical models and the existing initiatives range from the development of alternative metrics for goodness of fit, to data assimilation into operational models, to parameter estimation techniques. However, the treatment of error in many of these efforts is arguably selective and/or ad hoc. A Bayesian hierarchical framework enables the development of robust probabilistic analysis of error and uncertainty in model predictions by explicitly accommodating measurement error, parameter uncertainty, and model structure imperfection. This paper presents a Bayesian hierarchical formulation for simultaneously calibrating aquatic biogeochemical models at multiple systems (or sites of the same system) with differences in their trophic conditions, prior precisions of model parameters, available information, measurement error or inter-annual variability. Our statistical formulation also explicitly considers the uncertainty in model inputs (model parameters, initial conditions), the analytical/sampling error associated with the field data, and the discrepancy between model structure and the natural system dynamics (e.g., missing key ecological processes, erroneous formulations, misspecified forcing functions). The comparison between observations and posterior predictive monthly distributions indicates that the plankton models calibrated under the Bayesian hierarchical scheme provided accurate system representations for all the scenarios examined. Our results also suggest that the Bayesian hierarchical approach allows overcoming problems of insufficient local data by “borrowing strength” from well-studied sites and this feature will be highly relevant to conservation practices of regions with a high number of freshwater resources for which complete data could never be practically collected. Finally, we discuss the prospect of extending this framework to spatially explicit biogeochemical models (e.g., more effectively connect inshore with offshore areas) along with the benefits for environmental management, such as the optimization of the sampling design of monitoring programs and the alignment with the policy practice of adaptive management.     

Bayesian entropy for spatial sampling design of environmental data

We develop a spatial statistical methodology to design national air pollution monitoring networks with good predictive capabilities while minimizing the cost of monitoring. The underlying complexity of atmospheric processes and the urgent need to give credible assessments of environmental risk create problems requiring new statistical methodologies to meet these challenges. In this work, we present a new method of ranking various subnetworks taking both the environmental cost and the statistical information into account. A Bayesian algorithm is introduced to obtain an optimal subnetwork using an entropy framework. The final network and accuracy of the spatial predictions is heavily dependent on the underlying model of spatial correlation. Usually the simplifying assumption of stationarity, in the sense that the spatial dependency structure does not change location, is made for spatial prediction. However, it is not uncommon to find spatial data that show strong signs of nonstationary behavior. We build upon an existing approach that creates a nonstationary covariance by a mixture of a family of stationary processes, and we propose a Bayesian method of estimating the associated parameters using the technique of Reversible Jump Markov Chain Monte Carlo. We apply these methods for spatial prediction and network design to ambient ozone data from a monitoring network in the eastern US.     

Uncovering the evolution of tin use in the United States and its implications

• US tin use decreases as the GDP value added by manufacturing sector increases. • Global and China’s tin use increases as the GDP added by manufacturing increases. • A sigmoid curve can fit the US tin use data well. • US tin use patterns is not due to the finite tin reserves or resources. • Policies, substitutions, etc. play key roles in the changing tin use patterns. Tin is of key importance to daily life and national security; it is considered an essential industrial metal. The United States (US) is the world’s largest economy and consumer of natural resources. Therefore, the analysis of historical tin use in the US is helpful for understanding future tin use trends in the world as a whole and in developing countries. Time series analysis, regression analysis with GDP or GDP/capita, and historical data fitted with logistic and Gompertz models are employed in this study. Historical tin use in the US shows three stages—increase-constant-decrease, as GDP per capita has increased. Tin use in the US is negatively correlated with the GDP value added by the manufacturing sector, while the use of tin worldwide and in China continues to increase along with the GDP value added by the manufacturing sector. Although a sigmoid curve can fit the US tin use data well, that use is not directly related to the limited tin reserves or resources. Rather, policies, economic restructuring, substitutions, new end-use markets, etc. have played key roles in the changing tin use patterns. This work contributes to understanding future tin use at both the global and national levels: tin use will continue to increase with GDP at the global level, but use patterns of tin at the national level can be changed through human intervention.     

Efficient species-level monitoring at the landscape scale

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance.     

Multi-lag cluster designs for estimating the semivariogram for sediments affected by effluent discharges offshore in San Diego

Maps are useful tools for understanding, managing, and protecting the marine environment, yet few useful and statistically defensible maps of environmental quality and aquatic resources have been developed in near-coastal regions. Current environmental management efforts, such as ocean monitoring by sewage dischargers, routinely sample areas of potential impact using sparse sampling grids. Heterogeneous oceanic conditions often make extrapolation from these grids to non-sampled locations questionable. Although rarely applied in coastal monitoring, kriging offers a more rigorous statistical approach to mapping and allows confidence intervals to be calculated for predictions. Its usefulness relies on accurate models of the spatial variability through estimating the semivariogram. Many optimal designs for estimating the semivariogram have been proposed, but these designs are often difficult to implement in practice. In this paper, we present simple design strategies for augmenting existing monitoring designs with the goal of estimating the semivariogram. In particular, we investigate a multi-lag cluster design strategy, where clusters of sites, spaced at various lag distances, are placed around fixed stations on an existing sampling grid. We find that these multi-lag cluster designs provide improved accuracy in estimating the parameters of the semivariogram. Based on simulation study findings, we apply a multi-lag cluster enhancement to the monitoring grid for the City of San Diego’s Point Loma Wastewater Treatment Plant as part of a special study to map chemical contaminants in sediments around its sewage outfall.     

Resource use conflicts in Usangu Plains,Mbarali District,Tanzania

Conflicts over natural resources such as land, water, and forests are ubiquitous. People everywhere have competed for natural resources to enhance their livelihoods. However, the dimensions, level and intensity of conflict vary greatly from one place to another. This study was conducted in Usangu plains, Mbarali district, Tanzania, to investigate resource use conflicts and their underlying causes. Participatory Rural Appraisal (PRA) and household survey using a structured questionnaire were the major tools for data collection. Participant observation and secondary data sources were also used to supplement information. The study revealed the existence of resource use conflicts in the area. About 50% of respondents argued that relationships between the various ethnic groups in Usangu plains were bad. Conflicts were centred on competition for water and land. Crop damage was ranked highest (25% of respondents) as a cause behind many conflicts in the area. The study recommends that the government should redefine land tenure and land rights, enhance crop-livestock linkages and carry out a stakeholder analysis in the Usangu plains.     

Long-Term Ecosystem Dynamics in the Serengeti: Lessons for Conservation

Abstract:  Data from long-term ecological studies further understanding of ecosystem dynamics and can guide evidence-based management. In a quasi-natural experiment we examined long-term monitoring data on different components of the Serengeti-Mara Ecosystem to trace the effects of disturbances and thus to elucidate cause-and-effect connections between them. The long-term data illustrated the role of food limitation in population regulation in mammals, particularly in migratory wildebeest and nonmigratory buffalo. Predation limited populations of smaller resident ungulates and small carnivores. Abiotic events, such as droughts and floods, created disturbances that affected survivorship of ungulates and birds. Such disturbances showed feedbacks between biotic and abiotic realms. Interactions between elephants and their food allowed savanna and grassland communities to co-occur. With increased woodland vegetation, predators' capture of prey increased. Anthropogenic disturbances had direct (hunting) and indirect (transfer of disease to wildlife) effects. Slow and rapid changes and multiple ecosystem states became apparent only over several decades and involved events at different spatial scales. Conservation efforts should accommodate both infrequent and unpredictable events and long-term trends. Management should plan on the time scale of those events and should not aim to maintain the status quo. Systems can be self-regulating through food availability and predator-prey interactions; thus, culling may not be required. Ecosystems can occur in multiple states; thus, there may be no a priori need to maintain one natural state. Finally, conservation efforts outside protected areas must distinguish between natural change and direct human-induced change. Protected areas can act as ecological baselines in which human-induced change is kept to a minimum     

Opportunities for better use of collective action theory in research and governance for invasive species management

Controlling invasive species presents a public-good dilemma. Although environmental, social, and economic benefits of control accrue to society, costs are borne by only a few individuals and organizations. For decades, policy makers have used incentives and sanctions to encourage or coerce individual actors to contribute to the public good, with limited success. Diverse, subnational efforts to collectively manage invasive plants, insects, and animals provide effective alternatives to traditional command-and-control approaches. Despite this work, there has been little systematic evaluation of collective efforts to determine whether there are consistent principles underpinning success. We reviewed 32 studies to identify the extent to which collective-action theories from related agricultural and environmental fields explain collaborative invasive species management approaches; describe and differentiate emergent invasive species collective-action efforts; and provide guidance on how to enable more collaborative approaches to invasive species management. We identified 4 types of collective action aimed at invasive species—externally led, community led, comanaged, and organizational coalitions—that provide blueprints for future invasive species management. Existing collective-action theories could explain the importance attributed to developing shared knowledge of the social-ecological system and the need for social capital. Yet, collection action on invasive species requires different types of monitoring, sanctions, and boundary definitions. We argue that future government policies can benefit from establishing flexible boundaries that encourage social learning and enable colocated individuals and organizations to identify common goals, pool resources, and coordinate efforts.