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Understanding environmental driver-response relationships is critical to the implementation of effective ecosystem-based management. Ecosystems are often influenced by multiple drivers that operate on different timescales and may be nonstationary. In turn, contrasting views of ecosystem state and structure could arise depending on the temporal perspective of analysis. Further, assessment of multiple ecosystem components (e.g., biological indicators) may serve to identify different key drivers and connections. To explore how the timescale of analysis and data richness can influence the identification of driver-response relationships within a large, dynamic ecosystem, this study analyzed long-term (1969-2018) data from Lake Erie (USA-Canada). Data were compiled on multiple biological, physical, chemical, and socioeconomic components of the ecosystem to quantify trends and identify potential key drivers during multiple time intervals (20 to 50 years duration), using zooplankton, bird, and fish community metrics as indicators of ecosystem change. Concurrent temporal shifts of many variables occurred during the 1980s, but asynchronous dynamics were evident among indicator taxa. The strengths and rank orders of predictive drivers shifted among intervals and were sometimes taxon-specific. Drivers related to nutrient loading and lake trophic status were consistently strong predictors of temporal patterns for all indicators; however, within the longer intervals, measures of agricultural land use were the strongest predictors, whereas within shorter intervals, the stronger predictors were measures of tributary or in-lake nutrient concentrations. Physical drivers also tended to increase in predictive ability within shorter intervals. The results highlight how the time interval examined can filter influences of lower-frequency, slower drivers and higher-frequency, faster drivers. Understanding ecosystem change in support of ecosystem-based management requires consideration of both the temporal perspective of analysis and the chosen indicators, as both can influence which drivers are identified as most predictive of ecosystem trends at that timescale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Ecosystems worldwide have been impacted by multiple anthropogenic stressors, yet efforts to understand and manage these impacts have been hindered by difficulties in disentangling relative stressor effects. Theoretically, the actions of individual stressors can be delineated based on associated changes in functional traits and these relationships should be generalizable across communities comprised of different species. Thus, combining trait perspectives with community composition data could help to identify the relative influence of different stressors. We evaluated the utility of this combined approach by quantifying shifts in fish species and trait composition in Lake Erie during the past 50 years (1969-2018) in relation to human-driven changes in nutrient inputs, climate warming, and biological invasions. Species and trait shifts were also compared between two Lake Erie basins, which differ in their environmental and biological characteristics, to identify trait responses that were generalizable across different ecosystems versus those that were context dependent. Our analyses revealed consistent species changes across basins, and shifts in feeding and thermal traits, that were primarily associated with altered nutrient inputs (oligotrophication followed by eutrophication). We found no or inconsistent trait-based evidence for the effects of warming and two invasive fishes. Context-dependent trait responses were also evident; nutrient inputs were related to shifts in species tolerant of turbidity in the shallow, eutrophic western basin, which contrasted to shifts between benthopelagic and benthic species in the deeper central basin. Our results reveal the dominant effects of specific stressors on a large freshwater lake and offer a framework for combining species-based and trait-based approaches to delineate the impacts of simultaneous stressors on communities of perturbed natural ecosystems., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Aim: Inferences of the predominant processes that structure communities are commonly based on single 'snapshots' in time, which may miss temporally transient but important mechanisms. In this study, we compared key environmental and spatial drivers of zooplankton composition across multiple years to quantify shifts in their relative importance through time, and to identify any drivers of temporal change. Location: Southern Ontario, Canada. Taxon: Zooplankton. Methods: Zooplankton were collected from 29 lakes in southern Ontario, Canada over four years (2013–2016). Variation partitioning was used to quantify the relative importance of independent and covarying components of local environmental conditions, regional east‐west and north‐south compositional trends, and inter‐lake geographic distance in each year. Measured environmental metrics included aspects of lake morphology and chemistry, and spatial relationships were quantified using lake latitude/longitude coordinates and Moran's Eigenvector Maps (MEMs). Redundancy analyses (RDAs) were also used to compare the influence of individual environmental and spatial variables across years. Results: Most local‐scale and regional‐scale community processes were consistently important across all surveyed years, but some were less consistent. Specifically, geomorphology was always an important driver of local environmental and regional spatial community patterns. This occurred because local community composition was strongly affected by whether a lake was shallower versus deeper, and due to spatial clusters of shallow and deep lakes that produced negative spatial autocorrelation in community composition. Conversely, the individual influences of lake chemistry and spatial east‐west compositional trends were important in some years and not in others, potentially due to inter‐annual shifts in the predominant environmental variables and extreme weather events. Main conclusions: A single‐year community snapshot can provide insight into consistent or slowly changing community structuring processes, such as those driven by geomorphology, but may not completely capture temporally transient mechanisms. Furthermore, snapshots collected during anomalous seasons or years may misrepresent which mechanisms are predominantly determining community composition. Future efforts to understand local and regional community drivers would therefore benefit from considering which processes are likely temporally 'consistent' versus 'transient', and studies with more variable components would benefit from considering or controlling for temporal shifts in their importance. [ABSTRACT FROM AUTHOR]