Ecological Applications

Boreal and subarctic peatlands comprise a carbon pool of 455 Pg that has accumulated during the postglacial period at an average net rate of 0.096 Pg/yr (1 Pg = 10¹⁵g). Using Clymo's (1984) model, the current rate is estimated at 0.076 Pg/yr. Longterm drainage of these peatlands is estimated to be causing the oxidation to CO₂ of a little more than 0.0085 Pg/yr, with conbustion of fuel peat adding °0.026 Pg/yr. Emissions of CH₄ are estimated to release ° 0.046 Pg of carbon annually. Uncertainties beset estimates of both stocks and fluxes, particularly with regard to Soviet peatlands. The influence of water table alterations upon fluxes of both CO₂ and CH₄ is in great need of investigation over a wide range of peatland environments, especially in regions where permafrost melting, thermokarst erosion, and the development of thaw lakes are likely results of climatic warming. The role of fire in the carbon cycle of peatlands also deserves increased attention. Finally, satellite—monitoring of the abundance of open water in the peatlands of the West Siberian Plain and the Hudson/James Bay Lowland is suggested as a likely method of detecting early effects of climatic warming upon boreal and subarctic peatlands.

Most methods for modeling species distributions from occurrence records require additional data representing the range of environmental conditions in the modeled region. These data, called background or pseudo‐absence data, are usually drawn at random from the entire region, whereas occurrence collection is often spatially biased toward easily accessed areas. Since the spatial bias generally results in environmental bias, the difference between occurrence collection and background sampling may lead to inaccurate models. To correct the estimation, we propose choosing background data with the same bias as occurrence data. We investigate theoretical and practical implications of this approach. Accurate information about spatial bias is usually lacking, so explicit biased sampling of background sites may not be possible. However, it is likely that an entire target group of species observed by similar methods will share similar bias. We therefore explore the use of all occurrences within a target group as biased background data. We compare model performance using target‐group background and randomly sampled background on a comprehensive collection of data for 226 species from diverse regions of the world. We find that target‐group background improves average performance for all the modeling methods we consider, with the choice of background data having as large an effect on predictive performance as the choice of modeling method. The performance improvement due to target‐group background is greatest when there is strong bias in the target‐group presence records. Our approach applies to regression‐based modeling methods that have been adapted for use with occurrence data, such as generalized linear or additive models and boosted regression trees, and to Maxent, a probability density estimation method. We argue that increased awareness of the implications of spatial bias in surveys, and possible modeling remedies, will substantially improve predictions of species distributions.

Atmospheric nitrogen (N) deposition is a recognized threat to plant diversity in temperate and northern parts of Europe and North America. This paper assesses evidence from field experiments for N deposition effects and thresholds for terrestrial plant diversity protection across a latitudinal range of main categories of ecosystems, from arctic and boreal systems to tropical forests. Current thinking on the mechanisms of N deposition effects on plant diversity, the global distribution of G200 ecoregions, and current and future (2030) estimates of atmospheric N‐deposition rates are then used to identify the risks to plant diversity in all major ecosystem types now and in the future.

This synthesis paper clearly shows that N accumulation is the main driver of changes to species composition across the whole range of different ecosystem types by driving the competitive interactions that lead to composition change and/or making conditions unfavorable for some species. Other effects such as direct toxicity of nitrogen gases and aerosols, long‐term negative effects of increased ammonium and ammonia availability, soil‐mediated effects of acidification, and secondary stress and disturbance are more ecosystem‐ and site‐specific and often play a supporting role. N deposition effects in mediterranean ecosystems have now been identified, leading to a first estimate of an effect threshold. Importantly, ecosystems thought of as not N limited, such as tropical and subtropical systems, may be more vulnerable in the regeneration phase, in situations where heterogeneity in N availability is reduced by atmospheric N deposition, on sandy soils, or in montane areas.

Critical loads are effect thresholds for N deposition, and the critical load concept has helped European governments make progress toward reducing N loads on sensitive ecosystems. More needs to be done in Europe and North America, especially for the more sensitive ecosystem types, including several ecosystems of high conservation importance.

The results of this assessment show that the vulnerable regions outside Europe and North America which have not received enough attention are ecoregions in eastern and southern Asia (China, India), an important part of the mediterranean ecoregion (California, southern Europe), and in the coming decades several subtropical and tropical parts of Latin America and Africa. Reductions in plant diversity by increased atmospheric N deposition may be more widespread than first thought, and more targeted studies are required in low background areas, especially in the G200 ecoregions.

We offer a conceptual framework for managing forested ecosystems under an assumption that future environments will be different from present but that we cannot be certain about the specifics of change. We encourage flexible approaches that promote reversible and incremental steps, and that favor ongoing learning and capacity to modify direction as situations change. We suggest that no single solution fits all future challenges, especially in the context of changing climates, and that the best strategy is to mix different approaches for different situations. Resources managers will be challenged to integrate adaptation strategies (actions that help ecosystems accommodate changes adaptively) and mitigation strategies (actions that enable ecosystems to reduce anthropogenic influences on global climate) into overall plans. Adaptive strategies include resistance options (forestall impacts and protect highly valued resources), resilience options (improve the capacity of ecosystems to return to desired conditions after disturbance), and response options (facilitate transition of ecosystems from current to new conditions). Mitigation strategies include options to sequester carbon and reduce overall greenhouse gas emissions. Priority‐setting approaches (e.g., triage), appropriate for rapidly changing conditions and for situations where needs are greater than available capacity to respond, will become increasingly important in the future.

Ecosystem management is management driven by explicit goals, executed by policies, protocols, and practices, and made adaptable by monitoring and research based on our best understanding of the ecological interactions and processes necessary to sustain ecosystem composition, structure, and function. In recent years, sustainability has become an explicitly stated, even legislatively mandated, goal of natural resource management agencies. In practice, however, management approaches have often focused on maximizing short‐term yield and economic gain rather than long‐term sustainability. Several obstacles contribute to this disparity, including: (1) inadequate information on the biological diversity of environments; (2) widespread ignorance of the function and dynamics of ecosystems; (3) the openness and interconnectedness of ecosystems on scales that transcend management boundaries; (4) a prevailing public perception that the immediate economic and social value of supposedly renewable resources outweighs the risk of future ecosystem damage or the benefits of alternative management approaches. The goal of ecosystem management is to overcome these obstacles. Ecosystem management includes the following elements: (1) Sustainability. Ecosystem management does not focus primarily on deliverables" but rather regards intergenerational sustainability as a precondition. (2) Goals. Ecosystem management establishes measurable goals that specify future processes and outcomes necessary for sustainability. (3) Sound ecological models and understanding. Ecosystem management relies on research performed at all levels of ecological organization. (4) Complexity and connectedness. Ecosystem management recognizes that biological diversity and structural complexity strengthen ecosystems against disturbance and supply the genetic resources necessary to adapt to long‐term change. (5) The dynamic character of ecosystems. Recognizing that change and evolution are inherent in ecosystem sustainability, ecosystem management avoids attempts to freeze" ecosystems in a particular state or configuration. (6) Context and scale. Ecosystem processes operate over a wide range of spatial and temporal scales, and their behavior at any given location is greatly affected by surrounding systems. Thus, there is no single appropriate scale or time frame for management. (7) Humans as ecosystem components. Ecosystem management values the active role of humans in achieving sustainable management goals. (8) Adaptability and accountability. Ecosystem management acknowledges that current knowledge and paradigms of ecosystem function are provisional, incomplete, and subject to change. Management approaches must be viewed as hypotheses to be tested by research and monitoring programs. The following are fundamental scientific precepts for ecosystem management. (1) Spatial and temporal scale are critical. Ecosystem function includes inputs, outputs, cycling of materials and energy, and the interactions of organisms. Boundaries defined for the study or management of one process are often inappropriate for the study of others; thus, ecosystem management requires a broad view. (2) Ecosystem function depends on its structure, diversity, and integrity. Ecosystem management seeks to maintain biological diversity as a critical component in strengthening ecosystems against disturbance. Thus, management of biological diversity requires a broad perspective and recognition that the complexity and function of any particular location is influenced heavily by the surrounding system. (3) Ecosystems are dynamic in space and time. Ecosystem management is challenging in part because ecosystems are constantly changing. Over time scales of decades or centuries, many landscapes are altered by natural disturbances that lead to mosaics of successional patches of different ages. Such patch dynamics are critical to ecosystem structure and function. (4) Uncertainty, surprise, and limits to knowledge. Ecosystem management acknowledges that, given sufficient time and space, unlikely events are certain to occur. Adaptive management addresses this uncertainty by combining democratic principles, scientific analysis, education, and institutional learning to increase our understanding of ecosystem processes and the consequences of management interventions, and to improve the quality of data upon which decisions must be made. Ecosystem management requires application of ecological science to natural resource actions. Moving from concepts to practice is a daunting challenge and will require the following steps and actions. (1) Defining sustainable goals and objectives. Sustainable strategies for the provision of ecosystem goods and services cannot take as their starting points statements of need or want such as mandated timber supply, water demand, or arbitrarily set harvests of shrimp or fish. Rather, sustainability must be the primary objective, and levels of commodity and amenity provision must be adjusted to meet that goal. (2) Reconciling spatial scales. Implementation of ecosystem management would be greatly simplified if management jurisdictions were spatially congruent with the behavior of ecosystem processes. Given the variation in spatial domain among processes, one perfect fit for all processes is virtually impossible; rather, ecosystem management must seek consensus among the various stakeholders within each ecosystem. (3) Reconciling temporal scales. Whereas management agencies are often forced to make decisions on a fiscal‐year basis, ecosystem management must deal with time scales that transcend human lifetimes. Ecosystem management requires long‐term planning and commitment. (4) Making the system adaptable and accountable. Successful ecosystem management requires institutions that are adaptable to changes in ecosystem characteristics and in our knowledge base. Adaptive management by definition requires the scientist's ongoing interaction with managers and the public. Communication must flow in both directions, and scientists must be willing to prioritize their research with regard to critical management needs. Scientists have much to offer in the development of monitoring programs, particularly in creating sampling approaches, statistical analyses, and scientific models. As our knowledge base evolves, scientists must develop new mechanisms to communicate research and management results. More professionals with an understanding of scientific, management, and social issues, and the ability to communicate with scientists, managers, and the public are needed. Ecosystem management is not a rejection of an anthropocentric for a totally biocentric worldview. Rather it is management that acknowledges the importance of human needs while at the same time confronting the reality that the capacity of our world to meet those needs in perpetuity has limits and depends on the functioning of ecosystems.

I examined the distribution and abundance of bird species across an urban gradient, and concomitant changes in community structure, by censuring summer resident bird populations at six sites in Santa Clara County, California (all former oak woodlands). These sites represented a gradient of urban land use that ranged from relatively undisturbed to highly developed, and included a biological preserve, recreational area, golf course, residential neighborhood, office park, and business district. The composition of the bird community shifted from predominantly native species in the undisturbed area to invasive and exotic species in the business district. Species richness, Shannon diversity, and bird biomass peaked at moderately disturbed sites. One or more species reached maximal densities in each of the sites, and some species were restricted to a given site. The predevelopment bird species (assumed to be those found at the most undisturbed site) dropped out gradually as the sites became more urban. These patterns were significantly related to shifts in habitat structure that occurred along the gradient, as determined by canonical correspondence analysis (CCA) using the environmental variables of percent land covered by pavement, buildings, lawn, grasslands, and trees or shrubs. I compared each formal site to four additional sites with similar levels of development within a two‐country area to verify that the bird communities at the formal study sites were representative of their land use category.