Christopher T. Filstrup

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.

Approaches to advance scientific understanding of macrosystems ecology

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Watershed Sediment Losses to Lakes Accelerating Despite Agricultural Soil Conservation Efforts

Agricultural soil loss and deposition in aquatic ecosystems is a problem that impairs water quality worldwide and is costly to agriculture and food supplies. In the US, for example, billions of dollars have subsidized soil and water conservation practices in agricultural landscapes over the past decades. We used paleolimnological methods to reconstruct trends in sedimentation related to human-induced landscape change in 32 lakes in the intensively agricultural region of the Midwestern United States. Despite erosion control efforts, we found accelerating increases in sediment deposition from erosion; median erosion loss since 1800 has been 15.4 tons ha−1. Sediment deposition from erosion increased >6-fold, from 149 g m−2 yr−1 in 1850 to 986 g m−2 yr−1 by 2010. Average time to accumulate one mm of sediment decreased from 631 days before European settlement (ca. 1850) to 59 days mm−1 at present. Most of this sediment was deposited in the last 50 years and is related to agricultural intensification rather than land clearance or predominance of agricultural lands. In the face of these intensive agricultural practices, traditional soil conservation programs have not decelerated downstream losses. Despite large erosion control subsidies, erosion and declining water quality continue, thus new approaches are needed to mitigate erosion and water degradation.

Biodiversity change is uncoupled from species richness trends: consequences for conservation and monitoring

Global concern about human impact on biological diversity has triggered an intense research agenda on drivers and consequences of biodiversity change in parallel with international policy seeking to conserve biodiversity and associated ecosystem functions. Quantifying the trends in biodiversity is far from trivial, however, as recently documented by meta-analyses, which report little if any net change in local species richness through time. Here, we summarise several limitations of species richness as a metric of biodiversity change and show that the expectation of directional species richness trends under changing conditions is invalid. Instead, we illustrate how a set of species turnover indices provide more information content regarding temporal trends in biodiversity, as they reflect how dominance and identity shift in communities over time. We apply these metrics to three monitoring datasets representing different ecosystem types. In all datasets, nearly complete species turnover occurred, but this was disconnected from any species richness trends. Instead, turnover was strongly influenced by changes in species presence (identities) and dominance (abundances). We further show that these metrics can detect phases of strong compositional shifts in monitoring data and thus identify a different aspect of biodiversity change decoupled from species richness. Synthesis and applications: Temporal trends in species richness are insufficient to capture key changes in biodiversity in changing environments. In fact, reductions in environmental quality can lead to transient increases in species richness if immigration or extinction has different temporal dynamics. Thus, biodiversity monitoring programmes need to go beyond analyses of trends in richness in favour of more meaningful assessments of biodiversity change.

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes

Abstract Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states. LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.

Biomass pyramids in lake plankton: influence of Cyanobacteria size and abundance

Abstract The ratio of zooplankton to phytoplankton (Z:P) standing stock biomass in freshwater lakes has been suggested to decline in highly productive systems. An increasingly large proportion of inedible phytoplankton, especially in eutrophic systems dominated by Cyanobacteria, is one possible mechanism for declining Z:P. We tested this hypothesis by calculating the biomass in phytoplankton and zooplankton samples collected from 173 culturally eutrophic lakes and estimating the change in the functional relationship between zooplankton and phytoplankton biomass after ignoring inedible Cyanobacteria. We found up to 2 orders of magnitude less zooplankton biomass than would be predicted at a given total phytoplankton biomass and that removing Cyanobacteria led to zooplankton biomass approaching the level expected based on remaining phytoplankton biomass. Z:P increased with the percentage of edible phytoplankton biomass, indicating greater zooplankton biomass in lakes with the least Cyanobacteria. The lower Z:P found in these eutrophic lakes likely results from 89% of the phytoplankton biomass being composed of Cyanobacteria, whose cells were significantly larger than other phytoplankton. These results suggest that zooplankton biomass is limited by a declining proportion of edible phytoplankton in the most productive lakes and illustrate how eutrophication leads to declining resource use efficiency by consumers.

Phytoplankton taxonomic compositional shifts across nutrient and light gradients in temperate lakes

Abstract Nutrient and light availability, and their balance, can modify community composition and structure in pelagic communities. Previous studies have demonstrated contradictory findings about whether total phosphorus (TP) concentrations alone or the ratio of total nitrogen (TN) to TP concentrations (TN:TP) drive Cyanobacteria dominance in freshwater ecosystems, and influences of light availability are often overlooked. Here, we analyzed a 12 year, 137 lake database to test paradigms of phytoplankton compositional patterns across nutrient (TN, TP, TN:TP) and light availability gradients in an agricultural region. We hypothesized that (1) TN:TP ratios would better predict phytoplankton compositional shifts than TP concentrations alone, (2) Cyanobacteria relative abundance would increase at low TN:TP ratios, and (3) Cyanobacteria biomass fluctuations would be the primary driver of light climate. We found that TN:TP ratios better described phytoplankton compositional patterns than TP concentrations, with Cyanobacteria proportions decreasing with increasing TN:TP while other taxa increased. Contrary to expectations, Cyanobacteria always dominated community composition (≥80% biomass), regardless of TP concentrations. Despite these patterns, N-fixing Cyanobacteria proportions were not correlated to TN:TP, suggesting that shifts toward N-fixation were not solely driving phytoplankton compositional patterns. Although Cyanobacteria biomass decreased with increasing light availability, inorganic particles explained more variance in light than total phytoplankton biomass, suggesting that buoyancy-regulating Cyanobacteria may gain an initial competitive advantage in light acquisition before bloom development in turbid systems. These findings suggest that Cyanobacteria strongly influence pelagic community dynamics in nutrient-enriched lakes, and their ability to manipulate light and nutrient environments enable their persistent dominance across large environmental gradients.

Relationship of chlorophyll to phosphorus and nitrogen in nutrient-rich lakes

Abstract Nitrogen (N) and phosphorus (P) commonly co-limit primary productivity in lakes, and chlorophyll a (Chl-a) is predicted to be greatest under high N, high P regimes. Because land use practices can alter N and P biogeochemical cycles in watersheds, it is unclear whether previously documented phytoplankton–nutrient relationships apply where landscapes are highly disturbed. Here, we analyzed a lake water quality database from an agricultural region to explore relationships among Chl-a, total N (TN), and total P (TP) under extreme nutrient concentrations. Chl-a was weakly related to TN when TP was ≤100 μg L−1 but displayed a stronger response to TN at higher TP. When TP exceeded 100 μg L−1, Chl-a increased with increasing TN until reaching a TN threshold of ~3 mg L−1 and decreased thereafter, resulting in a high nutrient, low Chl-a region that did not coincide with shifts in nutrient limitation, light availability, cellular Chl-a content, phytoplankton composition, or zooplankton grazing pressure. Beyond the threshold, nitrate comprised most of TN and occurred with reduced dissolved organic matter (DOM). These observations suggest that photolysis of nitrate may produce reactive oxygen species that damage DOM and phytoplankton. Reduction in N loading at high P could therefore increase Chl-a and decrease water clarity, resulting in an apparent worsening of water quality. Our data suggest that monitoring Chl-a or Secchi depth may fail to indicate water quality degradation by extreme nutrient concentrations. These findings highlight how extreme nutrient regimes in lakes can produce novel relationships between phytoplankton and nutrients.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

Abstract Understanding broad‐scale ecological patterns and processes often involves accounting for regional‐scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional‐scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft‐ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.