A creative collaboration between the science of ecosystem restoration and art for sustainable stormwater management on an urban college campus

This article presents an interdisciplinary, on‐campus, student project, titled “The Rain Project” that I designed as an urban ecosystem restoration model as well as a collaborative pedagogical approach between ecological science and art at George Mason University (GMU), Virginia, U.S.A. A group of students from several disciplines (e.g. environmental science, art, civil engineering, biology, communication, and film/media) participated in designing and constructing a floating wetland for a campus stormwater pond as part of sustainable stormwater management. The Rain Project has numerous implications for college education, scholarship, and service while presenting a novel way of building a sense of community among undergraduate students for ecological awareness and literacy. The work of Jackie Brookner, a renowned eco‐artist who worked extensively on stormwater, and its relevance to the project is discussed. I strongly suggest the need for linking art and the science of ecosystem restoration to best obtain improvements in much‐needed communication for the success of community participatory restoration projects. I also believe that this kind of interdisciplinary, campus project can facilitate the changes we need to train higher education students to be able to both think differently and communicate effectively. The Rain Project introduced students to new learning strategies that connected “systems thinking” with art, ecological science, and restoration practices.     

From forest fires to fisheries management: Anthropology,conservation biology,and historical ecology

Human‐environmental relationships have long been of interest to a variety of scientists, including ecologists, biologists, anthropologists, and many others. 1 , 2 In anthropology, this interest was especially prevalent among cultural ecologists of the 1970s and earlier, who tended to explain culture as the result of techno‐environmental constraints. 3 More recently researchers have used historical ecology, an approach that focuses on the long‐term dialectical relationship between humans and their environments, as well as long‐term prehuman ecological datasets. 4 - 7 An important contribution of anthropology to historical ecology is that anthropological datasets dealing with ethnohistory, traditional ecological knowledge, and human skeletal analysis, as well as archeological datasets on faunal and floral remains, artifacts, geochemistry, and stratigraphic analysis, provide a deep time perspective (across decades, centuries, and millennia) on the evolution of ecosystems and the place of people in those larger systems. Historical ecological data also have an applied component that can provide important information on the relative abundances of flora and fauna, changes in biogeography, alternations in food webs, landscape evolution, and much more.     

Mapping urban ecology education in the UK

Abstract

Urban ecology has matured as a field of investigation. This paper explores how well it has transitioned into the educational curricula of UK Higher Education Institutions (HEIs) by mapping the presence of urban ecological or environmental topics across undergraduate and postgraduate programmes. The prevalence of different topics, the level at which they are taught, and the disciplinary areas in which they are housed, are quantified. Urban ecological topics are found in programmes across 50 of 147 HEIs (34%), mainly taught in ancillary fashion to support wider subjects, though some specialist modules and even programmes do exist. Only one HEI incorporates a compulsory (core) dedicated urban ecology module at undergraduate level. Much urban ecology teaching takes place at advanced undergraduate and postgraduate levels. Applied topics are usually taught from an environmental science perspective, with common examples including urban hydrology, climate, and green infrastructure; probably to address global concerns about urban sustainability and resilience. In particular there is scope for greater incorporation of urban ecology topics and themes into biological and ecological programmes, and utilising cities as labs to explore these topics. The paper concludes with a discussion of some of these possibilities.     

Developing a flexible learning activity on biodiversity and spatial scale concepts using open‐access vegetation datasets from the National Ecological Observatory Network

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.     

Value of long‐term ecological studies

Long‐term ecological studies are critical for providing key insights in ecology, environmental change, natural resource management and biodiversity conservation. In this paper, we briefly discuss five key values of such studies. These are: (1) quantifying ecological responses to drivers of ecosystem change; (2) understanding complex ecosystem processes that occur over prolonged periods; (3) providing core ecological data that may be used to develop theoretical ecological models and to parameterize and validate simulation models; (4) acting as platforms for collaborative studies, thus promoting multidisciplinary research; and (5) providing data and understanding at scales relevant to management, and hence critically supporting evidence‐based policy, decision making and the management of ecosystems. We suggest that the ecological research community needs to put higher priority on communicating the benefits of long‐term ecological studies to resource managers, policy makers and the general public. Long‐term research will be especially important for tackling large‐scale emerging problems confronting humanity such as resource management for a rapidly increasing human population, mass species extinction, and climate change detection, mitigation and adaptation. While some ecologically relevant, long‐term data sets are now becoming more generally available, these are exceptions. This deficiency occurs because ecological studies can be difficult to maintain for long periods as they exceed the length of government administrations and funding cycles. We argue that the ecological research community will need to coordinate ongoing efforts in an open and collaborative way, to ensure that discoverable long‐term ecological studies do not become a long‐term deficiency. It is important to maintain publishing outlets for empirical field‐based ecology, while simultaneously developing new systems of recognition that reward ecologists for the use and collaborative sharing of their long‐term data sets. Funding schemes must be re‐crafted to emphasize collaborative partnerships between field‐based ecologists, theoreticians and modellers, and to provide financial support that is committed over commensurate time frames.     

Ecological monitoring to support Water Sharing Plan evaluation and protect wetlands of inland New South Wales,Australia

Government‐funded flow response monitoring and modelling programmes (flow science) provided by the New South Wales Office of Water (NOW) have supported water resource management since 1997. Flow science has a core technical component defined by hypothesis‐driven long‐term monitoring and analysis, but it also represents many activities that support committees involved in environmental flow management. This is done through collaborations and contracting and has fostered considerable research and analysis into flow ecology, including modelling for the recent Murray–Darling Basin Plan. We describe the performance of environmental flows against legislated wetland objectives to improve wetland function and diversity using flow science. On‐ground monitoring at wetland sites has largely ceased but the flow science done so far indicates that the environmental flow rules written into Water Sharing Plans improve wetland diversity and function. Determination of the long‐term flow needs of NSW wetlands, including how well current Water Sharing Plans aid the delivery of environmental flows, requires finding the means to build on current flow science knowledge from across Australia.     

The predictability of a lake phytoplankton community,over time‐scales of hours to years

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time‐scales. Communities were highly predictable over hours to months: model R² decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long‐term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model‐inferred environmental growth dependencies matched laboratory studies, and suggested novel trade‐offs governing their competition. High‐frequency monitoring and machine learning can set prediction targets for process‐based models and help elucidate the mechanisms underlying ecological dynamics.     

Demystifying computer science for molecular ecologists

In this age of data‐driven science and high‐throughput biology, computational thinking is becoming an increasingly important skill for tackling both new and long‐standing biological questions. However, despite its obvious importance and conspicuous integration into many areas of biology, computer science is still viewed as an obscure field that has, thus far, permeated into only a few of the biology curricula across the nation. A national survey has shown that lack of computational literacy in environmental sciences is the norm rather than the exception [Valle & Berdanier (2012) Bulletin of the Ecological Society of America, 93, 373–389]. In this article, we seek to introduce a few important concepts in computer science with the aim of providing a context‐specific introduction aimed at research biologists. Our goal was to help biologists understand some of the most important mainstream computational concepts to better appreciate bioinformatics methods and trade‐offs that are not obvious to the uninitiated.     

Combining contemporary ecology and palaeolimnology to understand shallow lake ecosystem change

1. Palaeolimnology and contemporary ecology are complementary disciplines but are rarely combined. By reviewing the literature and using a case study, we show how linking the timescales of these approaches affords a powerful means of understanding ecological change in shallow lakes. 2. Recently, palaeolimnology has largely been pre‐occupied with developing transfer functions which use surface sediment‐lake environment datasets to reconstruct a single environmental variable. Such models ignore complex controls over biological structure and can be prone to considerable error in prediction. Furthermore, by reducing species assemblage data to a series of numbers, transfer functions neglect valuable ecological information on species’ seasonality, habitat structure and food web interactions. These elements can be readily extracted from palaeolimnological data with the interpretive assistance of contemporary experiments and surveys. For example, for one shallow lake, we show how it is possible to infer long‐term seasonality change from plant macrofossil and fossil diatom data with the assistance of seasonal datasets on macrophyte and algal dynamics. 3. On the other hand, theories on shallow lake functioning have generally been developed from short‐term (<1–15 years) studies as opposed to palaeo‐data that cover the actual timescales (decades–centuries) of shallow lake response to stressors such as eutrophication and climate change. Palaeolimnological techniques can track long‐term dynamics in lakes whilst smoothing out short‐term variability and thus provide a unique and important means of not only developing ecological theories, but of testing them. 4. By combining contemporary ecology and palaeolimnology, it should be possible to gain a fuller understanding of changing ecological patterns and processes in shallow lakes on multiple timescales.     

Envisioning ecological engineering education: An international survey of the educational and professional community

Nearly half a century ago, H.T. Odum envisioned a sustainable approach to systems design where human intervention would be supplementary to nature. He referred to this concept as ecological engineering and suggested that practitioners should receive an education beyond the rigors of engineering. To understand natural processes needed to design, develop, and restore natural systems successfully, Odum suggested ecological engineers should have an expanded knowledge of environmental systems and ecology. Furthermore, he recommended broadening educational exposure to social science and liberal arts. The field of ecological engineering has blossomed in the years since Odum expressed his vision, but universities have not adopted his suggested curriculum, and undergraduate engineering students have generally seen a reduction in social science and liberal arts courses. This paper compares Odum's vision with the surveyed visions of an international group of ecological engineers, who assessed the value and characteristics of an ecological engineering undergraduate education. The respondents’ perspectives vary with their location, education, and profession; however, most participants in this survey share Odum's vision, and are dissatisfied with existing curricula. Participants outside of the United States were more confident that something approaching Odum's vision for a program in ecological engineering could be delivered at the undergraduate level.     

Long-term studies of freshwater macroinvertebrates: a review of the frequency, duration and ecological significance

1. The importance of a long‐term ecological perspective is well documented, yet the availability of long‐term data remains limited. This paper highlights the value of long‐term ecological studies of freshwater macroinvertebrates by reviewing both the availability of long‐term data and recent ecological contributions based on them. 2. A survey of recent literature on stream macroinvertebrates identified 46 papers published between 1987 and 2004 that included long‐term (i.e. ≥5 years) data. Most recently published long‐term studies of stream macroinvertebrates began collecting data in the 1970s and 1980s and their duration (time between first and last year sampled) was relatively brief (median = 9 years, maximum = 96 years). Most studies did not expand their temporal perspective by incorporating older data collected by other researchers. 3. Recent long‐term studies of macroinvertebrates have made major contributions to our understanding of interannual variation and cycles, complex abiotic and biotic interactions, and natural and anthropogenic disturbance and recovery. Without these studies, we would know much less about the magnitude of natural temporal variation, the importance of physical and biological disturbance and interactions, the role of pathogens and introduced species, the overall impact of pollution and the effectiveness of protection and remediation efforts. 4. If we are to encourage long‐term perspectives in our science, we need to facilitate the transfer of individual studies, as well as knowledge and data, among scientists. This includes efforts to archive and annotate data more effectively, so that they can be more easily incorporated into future research.     

Citizen science in schools: Engaging students in research on urban habitat for pollinators

Citizen science can play an important role in school science education. Citizen science is particularly relevant to addressing current societal environmental sustainability challenges, as it engages the students directly with environmental science and gives students an understanding of the scientific process. In addition, it allows students to observe local representations of global challenges. Here, we report a citizen science programme designed to engage school‐age children in real‐world scientific research. The programme used standardized methods deployed across multiple schools through scientist–school partnerships to engage students with an important conservation problem: habitat for pollinator insects in urban environments. Citizen science programmes such as the programme presented here can be used to enhance scientific literacy and skills. Provided key challenges to maintain data quality are met, this approach is a powerful way to contribute valuable citizen science data for understudied, but ecologically important study systems, particularly in urban environments across broad geographical areas.     

Combining field experiments and individual-based modeling to identify the dynamically relevant organizational scale in a field system

Community ecologists continually strive to build analytical models that realistically describe long‐term dynamics of the systems they study. A key step in this process is identifying which details are relevant for predicting dynamics. Currently, this remains a limiting step in development of analytical theory because experimental field ecology, which provides the key empirical insight, and theoretical ecology, which translates empirical knowledge into analytical theory, remain weakly linked. I illustrate how an individual‐based computational model of species interactions is a useful way to bridge the gulf between empirical research and theory development. I built a computational model that reproduced key natural history and biological detail of an old‐field interaction web composed of a predator species, a herbivore species and two plant groups that had been the subject of extensive previous field research. I examined, using simulation experiments, how individual behavior of herbivores in response to changing resource and predator abundance scaled to long‐term population‐level and community‐level dynamics. The simulation experiments revealed that the long‐term community dynamics could be highly predictable because of two counterintuitive reasons. First, seasonality was a strong forcing variable on the system that removed the possibility of serial dependence in population abundance over time. Second, because of seasonality, short‐term behavioral responses of herbivores played a much stronger role in shaping community structure than longer‐term processes such as density responses. So, simply knowing the short‐term responses of herbivores at the evolutionary ecological level was sufficient to forecast the long‐term outcome of experimental manipulations. This study shows that an individual‐based model, once it is calibrated to the real‐world field system, can provide key insight into the biological detail that analytical models should include to predict long‐term dynamics.     

Using model‐data fusion to interpret past trends,and quantify uncertainties in future projections,of terrestrial ecosystem carbon cycling

Uncertainties in model projections of carbon cycling in terrestrial ecosystems stem from inaccurate parameterization of incorporated processes (endogenous uncertainties) and processes or drivers that are not accounted for by the model (exogenous uncertainties). Here, we assess endogenous and exogenous uncertainties using a model‐data fusion framework benchmarked with an artificial neural network (ANN). We used 18 years of eddy‐covariance carbon flux data from the Harvard forest, where ecosystem carbon uptake has doubled over the measurement period, along with 15 ancillary ecological data sets relative to the carbon cycle. We test the ability of combinations of diverse data to constrain projections of a process‐based carbon cycle model, both against the measured decadal trend and under future long‐term climate change. The use of high‐frequency eddy‐covariance data alone is shown to be insufficient to constrain model projections at the annual or longer time step. Future projections of carbon cycling under climate change in particular are shown to be highly dependent on the data used to constrain the model. Endogenous uncertainties in long‐term model projections of future carbon stocks and fluxes were greatly reduced by the use of aggregated flux budgets in conjunction with ancillary data sets. The data‐informed model, however, poorly reproduced interannual variability in net ecosystem carbon exchange and biomass increments and did not reproduce the long‐term trend. Furthermore, we use the model‐data fusion framework, and the ANN, to show that the long‐term doubling of the rate of carbon uptake at Harvard forest cannot be explained by meteorological drivers, and is driven by changes during the growing season. By integrating all available data with the model‐data fusion framework, we show that the observed trend can only be reproduced with temporal changes in model parameters. Together, the results show that exogenous uncertainty dominates uncertainty in future projections from a data‐informed process‐based model.     

Science, Art, or Application—the "Karma" of Restoration Ecology

The present state of restoration ecology is far away from Bradshaw’s “acid test for ecology.” The conclusions drawn from the series of papers in this issue and from the Jena workshop suggest some directions in which the field may progress. More attention must be paid to the degraded state, which should be evaluated by its specific features and carefully analyzed before any restoration plan is laid down. Restoration goals have to be realistic, which includes the appreciation of globally changing conditions, resulting in a paradigm‐shift toward “forward‐restoration.” Basically, the transition from the degraded state conditions to the target state is a kind of succession that is manipulated by the application of goal‐orientated and system‐specific disturbances. Whenever possible, restorationists should step back and make use of naturally occurring succession, which requires a sophisticated restoration strategy, involving flexible management responses, multiple alternative target states, robust measurements for the restoration progress, and careful long‐term monitoring. The unique feature of restoration ecology is the involvement of socioeconomic decisions, and conceptual frameworks for ecological restoration have to implement the specific links to natural succession. To bridge the gap between ecological theory and on the ground restoration, it is essential that restoration practice is translated into the vocabulary and thinking of basic ecology. If all these aspects are integrated, ecological restoration as an application—and restoration ecology as an applied science—may develop into an acid test for our understanding of interactions between people and their environment, rather than for pure ecology.     

Historical foundations and future directions in macrosystems ecology

Macrosystems ecology is an effort to understand ecological processes and interactions at the broadest spatial scales and has potential to help solve globally important social and ecological challenges. It is important to understand the intellectual legacies underpinning macrosystems ecology: How the subdiscipline fits within, builds upon, differs from and extends previous theories. We trace the rise of macrosystems ecology with respect to preceding theories and present a new hypothesis that integrates the multiple components of macrosystems theory. The spatio‐temporal anthropogenic rescaling (STAR) hypothesis suggests that human activities are altering the scales of ecological processes, resulting in interactions at novel space–time scale combinations that are diverse and predictable. We articulate four predictions about how human actions are “expanding”, “shrinking”, “speeding up” and “slowing down” ecological processes and interactions, and thereby generating new scaling relationships for ecological patterns and processes. We provide examples of these rescaling processes and describe ecological consequences across terrestrial, freshwater and marine ecosystems. Rescaling depends in part on characteristics including connectivity, stability and heterogeneity. Our STAR hypothesis challenges traditional assumptions about how the spatial and temporal scales of processes and interactions operate in different types of ecosystems and provides a lens through which to understand macrosystem‐scale environmental change.     

Ecology,Environmental Impact Statements,and Ecological Risk Assessment: A Brief Historical Perspective

Ecological risk assessment will continue to increase in importance as a conceptual and methodological basis for evaluating environmental impacts as required by the National Environmental Policy Act. Understanding the historical strengths and limitations of more traditional environmental assessments performed in support of the NEPA can facilitate the effective incorporation of ecological risk assessment into the NEPA process. Such integration will also benefit from a knowledge of the historical and continuing development of the ecological risk assessment process, as well as from a recognition of the contri butions from modern quantitative ecology and ecosystem science. Adopting a risk-based approach can improve the NEPA process by providing a framework for consistent and comprehensive ecological assessment and by providing a conceptual and methodological basis for addressing the varied uncertainties attendant to environmental assessments. The primary concern in integrating ecological risk assessment into the NEPA process is that ecological risk assessment not merely become a new name for traditional environmental impact assessments. While the integration of ecological risk assessment into the NEPA process occurs, it is important to begin to outline the next transition in environmental assessment capabilities. Operationally linking ecological risk assessment methods with formal decision models appears as a worthwhile objective in beginning this transition.     

Integrating trait‐based empirical and modeling research to improve ecological restoration

A global ecological restoration agenda has led to ambitious programs in environmental policy to mitigate declines in biodiversity and ecosystem services. Current restoration programs can incompletely return desired ecosystem service levels, while resilience of restored ecosystems to future threats is unknown. It is therefore essential to advance understanding and better utilize knowledge from ecological literature in restoration approaches. We identified an incomplete linkage between global change ecology, ecosystem function research, and restoration ecology. This gap impedes a full understanding of the interactive effects of changing environmental factors on the long‐term provision of ecosystem functions and a quantification of trade‐offs and synergies among multiple services. Approaches that account for the effects of multiple changing factors on the composition of plant traits and their direct and indirect impact on the provision of ecosystem functions and services can close this gap. However, studies on this multilayered relationship are currently missing. We therefore propose an integrated restoration agenda complementing trait‐based empirical studies with simulation modeling. We introduce an ongoing case study to demonstrate how this framework could allow systematic assessment of the impacts of interacting environmental factors on long‐term service provisioning. Our proposed agenda will benefit restoration programs by suggesting plant species compositions with specific traits that maximize the supply of multiple ecosystem services in the long term. Once the suggested compositions have been implemented in actual restoration projects, these assemblages should be monitored to assess whether they are resilient as well as to improve model parameterization. Additionally, the integration of empirical and simulation modeling research can improve global outcomes by raising the awareness of which restoration goals can be achieved, due to the quantification of trade‐offs and synergies among ecosystem services under a wide range of environmental conditions.     

Environmental weeds in Australia and New Zealand: issues and approaches to management

Environmental weeds are plants that invade natural ecosystems and are considered to be a serious threat to nature conservation. Australia and New Zealand, where biota with a high degree of endemism have evolved, are particularly susceptible to environmental weeds. Environmental weeds have been implicated in the extinction of several indigenous plant species, and they also threaten ecosystem stability and functional complexity. Historically, emphasis has been placed on the chemical or manual ‘control’ of weed infestations, often with little consideration of the long‐term effectiveness or the ecological consequences of such an approach. As the threat from environmental weeds is becoming more fully recognized, an integrated, strategic and ecological approach to weed management is being recommended. In both countries, systems for screening new plants before allowing entry for cultivation have been developed. For already established plants, management is conducted within a legislative and policy framework such as the Regional Pest Management Strategies that operate through the Biosecurity Act 1993 in New Zealand. Noxious weed legislation in Australia has historically focused on agricultural weeds, but some Acts are (or have recently been) undergoing revision to give greater emphasis to environmental weeds and the involvement of the community in weed management. Quarantine, legislation, research and on‐ground management are complemented by education programmes about the impact and control of environmental weeds. This paper provides an overview of the ‘tool‐kit’ needed to manage environmental weeds in Australia and New Zealand, comparing and contrasting the approaches taken in the two countries. It also provides a broad framework for the case studies that make up this special issue on the ecology and management of environmental weeds in both countries.