Patricia A. Soranno

Macrosystems ecology: understanding ecological patterns and processes at continental scales

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisci- plines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents.

Plant architecture and epiphytic macroinvertebrate communities: the role of an exotic dissected macrophyte

The abundance of epiphytic macroinvertebrates on aquatic macrophytes can be influenced by different plant architecture types. For example, dissected plants can provide epiphytic macroinvertebrates more substrate for foraging and more cover from predators than undissected plants. Large changes in macrophyte community composition have the potential to strongly influence whole-lake macroinvertebrate abundance if overall plant architecture changes. For example, when the exotic macrophyte Eurasian watermilfoil (Myriophyllum spicatum L., EWM), a dissected plant, invades a lake and becomes dominant, fundamental changes in lake-wide plant architecture occur. We conducted a 6-lake field study and a meta-analysis to examine whether macroinvertebrate density and biomass varies predictably with plant architecture and, if so, whether these relationships are evident at the whole-lake scale when EWM dominates the plant community. We found that higher macroinvertebrate densities and biomass per g of plant were associated with dissected plants than undissected plants in both our field study and our meta-analysis of published studies. However, in our field study, macroinvertebrate densities and biomass per g of plant decreased as the % of EWM cover increased across lakes, although not always significantly. This result suggests that EWM provides different habitat for macroinvertebrates than native dissected plants. Therefore, the macrophyte community may support lower densities and biomass of macroinvertebrates when EWM is dominant at the whole-lake scale. Reduced abundance of macroinvertebrates could have strong impacts on other components of lake food webs.

Food Web Structure and Littoral Zone Coupling to Pelagic Trophic Cascades

Lake productivity ultimately depends on phosphorus (P) supply rates (Schindler, 1977). Community interactions, especially size-selective predation by fishes and size-dependent rates of grazing and nutrient recycling by zooplankton, determine the efficiency and rate with which P inputs are translated to ecosystem productivity (Carpenter and Kitchell, 1993). Limnologists are now trying to determine how trophic cascades interact with the P cycle to influence lake productivity (McQueen et al., 1986; Elser and Goldman, 1991; Carpenter et al., 1991). One informative approach analyzes food web interactions in P currency, thereby integrating the direct and indirect effects of fishes on lake P cycles.

Linking Landscapes and Food Webs: Effects of Omnivorous Fish and Watersheds on Reservoir Ecosystems

Abstract Ecologists increasingly recognize the need to understand how landscapes and food webs interact. Reservoir ecosystems are heavily subsidized by nutrients and detritus from surrounding watersheds, and often contain abundant populations of gizzard shad, an omnivorous fish that consumes plankton and detritus. Gizzard shad link terrestrial landscapes and pelagic reservoir food webs by consuming detritus, translocating nutrients from sediment detritus to the water column, and consuming zooplankton. The abundance of gizzard shad increases with watershed agriculturalization, most likely through a variety of mechanisms operating on larval and adult life stages. Gizzard shad have myriad effects on reservoirs, including impacts on nutrients, phytoplankton, zooplankton, and fish, and many of their effects vary with ecosystem productivity (i.e., watershed land use). Interactive feedbacks among watersheds, gizzard shad populations, and reservoir food webs operate to maintain dominance of gizzard shad in highly productive systems. Thus, effective stewardship of reservoir ecosystems must incorporate both watershed and food-web perspectives.

Creating and maintaining high‐performing collaborative research teams: the importance of diversity and interpersonal skills

Collaborative research teams are a necessary and desirable component of most scientific endeavors. Effective collaborative teams exhibit important research outcomes, far beyond what could be accomplished by individuals working independently. These teams are made up of researchers who are committed to a common purpose, approach, and performance goals for which they hold themselves mutually accountable. We call such collaborations “high-performing collaborative research teams”. Here, we share lessons learned from our collective experience working with a wide range of collaborative teams and structure those lessons within a framework developed from literature in business, education, and a relatively new discipline, “science of team science”. We propose that high-performing collaborative research teams are created and maintained when team diversity (broadly defined) is effectively fostered and interpersonal skills are taught and practiced. Finally, we provide some strategies to foster team functioning and make recommendations for improving the collaborative culture in ecology.

Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled problems such as climate change, land-use/land-cover change, and invasive species.

Improving the culture of interdisciplinary collaboration in ecology by expanding measures of success

Interdisciplinary collaboration is essential to understand ecological systems at scales critical to human decision making. Current reward structures are problematic for scientists engaged in interdisciplinary research, particularly early career researchers, because academic culture tends to value only some research outputs, such as primary-authored publications. Here, we present a framework for the costs and benefits of collaboration, with a focus on early career stages, and show how the implementation of novel measures of success can help defray the costs of collaboration. Success measures at team and individual levels include research outputs other than publications, including educational outcomes, dataset creation, outreach products (eg blogs or social media), and the application of scientific results to policy or management activities. Promotion and adoption of new measures of success will require concerted effort by both collaborators and their institutions. Expanded measures should better reflect an...

Using Landscape Limnology to Classify Freshwater Ecosystems for Multi-ecosystem Management and Conservation

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

Macroinvertebrates associated with submerged macrophytes: sample size and power to detect effects

When planning and conducting ecological experiments, it is important to consider how many samples are necessary to detect differences among treatments with acceptably high statistical power. An analysis of statistical power is especially important when studying epiphytic macroinvertebrate colonization of submerged plants because they exhibit large plant-to-plant variability. Despite this variability, many studies have suggested that epiphytic macroinvertebrates preferentially colonize plants based on plant architecture type (broad versus dissected leaves). In this study, we calculated the power and number of samples necessary to detect differences in epiphytic macroinvertebrate abundance (numbers and biomass) among five species and two architecture types of macrophytes in a lake in MI, U.S.A. Using power analysis, we found that we had very high power to detect the differences present between macroinvertebrate abundance by architecture type and by macrophyte species (power = 1.000 and 0.994; effect sizes = 0.872 and 0.646, respectively. However, to detect very small differences between the two architecture types and the five plant species, we determined that many more samples were necessary to achieve similar statistical power (effect size = 0.1–0.3, number of samples = 60–527 and 36–310, respectively; power = 0.9). Our results suggest that macroinvertebrate abundance does in fact vary predictably with plant architecture. Dissected-leaf plants harbored higher abundances of macroinvertebrates than broad-leaf plants (ANOVA, density p = 0.001, biomass p < 0.001). This knowledge should allow us to better design future studies of epiphytic macroinvertebrates.

It's Good to Share: Why Environmental Scientists’ Ethics Are Out of Date

Although there have been many recent calls for increased data sharing, the majority of environmental scientists do not make their individual data sets publicly available in online repositories. Current data-sharing conversations are focused on overcoming the technological challenges associated with data sharing and the lack of rewards and incentives for individuals to share data. We argue that the most important conversation has yet to take place: There has not been a strong ethical impetus for sharing data within the current culture, behaviors, and practices of environmental scientists. In this article, we describe a critical shift that is happening in both society and the environmental science community that makes data sharing not just good but ethically obligatory. This is a shift toward the ethical value of promoting inclusivity within and beyond science. An essential element of a truly inclusionary and democratic approach to science is to share data through publicly accessible data sets.