Feasibility of implementing an integrated long-term database to advance ecosystem-based management in the Laurentian Great Lakes basin.

The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.

Temporal scope influences ecosystem driver-response relationships: A case study of Lake Erie with implications for ecosystem-based management.

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.

Functional traits reveal the dominant drivers of long-term community change across a North American Great Lake.

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.

Stress hormone-mediated antipredator morphology improves escape performance in amphibian tadpoles.

Complete functional descriptions of the induction sequences of phenotypically plastic traits (perception to physiological regulation to response to outcome) should help us to clarify how plastic responses develop and operate. Ranid tadpoles express several plastic antipredator traits mediated by the stress hormone corticosterone, but how they influence outcomes remains uncertain. We investigated how predator-induced changes in the tail morphology of wood frog (Rana sylvatica) tadpoles influenced their escape performance over a sequence of time points when attacked by larval dragonflies (Anax junius). Tadpoles were raised with no predator exposure, chemical cues of dragonflies added once per day, or constant exposure to caged dragonflies crossed with no exogenous hormone added (vehicle control only), exogenous corticosterone, or metyrapone (a corticosteroid synthesis inhibitor). During predation trials, we detected no differences after four days, but after eight days, tadpoles exposed to larval dragonflies and exogenous corticosterone had developed deeper tail muscles and exhibited improved escape performance compared to controls. Treatment with metyrapone blocked the development of a deeper tail muscle and resulted in no difference in escape success. Our findings further link the predator-induced physiological stress response of ranid tadpoles to the development of an antipredator tail morphology that confers performance benefits.

Projecting the effects of agricultural conservation practices on stream fish communities in a changing climate.

How anticipated climate change might affect long-term outcomes of present-day agricultural conservation practices remains a key uncertainty that could benefit water quality and biodiversity conservation planning. To explore this issue, we forecasted how the stream fish communities in the Western Lake Erie Basin (WLEB) would respond to increasing amounts of agricultural conservation practice (ACP) implementation under two IPCC future greenhouse gas emission scenarios (RCP4.5: moderate reductions; RCP8.5: business-as-usual conditions) during 2020-2065. We used output from 19 General Circulation Models to drive linked agricultural land use (APEX), watershed hydrology (SWAT), and stream fish distribution (boosted regression tree) models, subsequently analyzing how projected changes in habitat would influence fish community composition and functional trait diversity. Our models predicted both positive and negative effects of climate change and ACP implementation on WLEB stream fishes. For most species, climate and ACPs influenced species in the same direction, with climate effects outweighing those of ACP implementation. Functional trait analysis helped clarify the varied responses among species, indicating that more extreme climate change would reduce available habitat for large-bodied, cool-water species with equilibrium life-histories, many of which also are of importance to recreational fishing (e.g., northern pike, smallmouth bass). By contrast, available habitat for warm-water, benthic species with more periodic or opportunistic life-histories (e.g., northern hogsucker, greater redhorse, greenside darter) was predicted to increase. Further, ACP implementation was projected to hasten these shifts, suggesting that efforts to improve water quality could come with costs to other ecosystem services (e.g., recreational fishing opportunities). Collectively, our findings demonstrate the need to consider biological outcomes when developing strategies to mitigate water quality impairment and highlight the value of physical-biological modeling approaches to agricultural and biological conservation planning in a changing climate.

Particle backtracking improves breeding subpopulation discrimination and natal-source identification in mixed populations.

We provide a novel method to improve the use of natural tagging approaches for subpopulation discrimination and source-origin identification in aquatic and terrestrial animals with a passive dispersive phase. Our method integrates observed site-referenced biological information on individuals in mixed populations with a particle-tracking model to retrace likely dispersal histories prior to capture (i.e., particle backtracking). To illustrate and test our approach, we focus on western Lake Erie's yellow perch (Perca flavescens) population during 2006-2007, using microsatellite DNA and otolith microchemistry from larvae and juveniles as natural tags. Particle backtracking showed that not all larvae collected near a presumed hatching location may have originated there, owing to passive drift during the larval stage that was influenced by strong river- and wind-driven water circulation. Re-assigning larvae to their most probable hatching site (based on probabilistic dispersal trajectories from the particle backtracking model) improved the use of genetics and otolith microchemistry to discriminate among local breeding subpopulations. This enhancement, in turn, altered (and likely improved) the estimated contributions of each breeding subpopulation to the mixed population of juvenile recruits. Our findings indicate that particle backtracking can complement existing tools used to identify the origin of individuals in mixed populations, especially in flow-dominated systems.

Characterization of an alarm pheromone secreted by amphibian tadpoles that induces behavioral inhibition and suppression of the neuroendocrine stress axis.

Many species assess predation risk through chemical cues, but the tissue source, chemical nature, and mechanisms of production or action of these cues are often unknown. Amphibian tadpoles show rapid and sustained behavioral inhibition when exposed to chemical cues of predation. Here we show that an alarm pheromone is produced by ranid tadpole skin cells, is released into the medium via an active secretory process upon predator attack, and signals predator presence to conspecifics. The pheromone is composed of two components with distinct biophysical properties that must be combined to elicit the behavioral response. In addition to the behavioral response, exposure to the alarm pheromone caused rapid and strong suppression of the hypothalamo-pituitary-adrenal (HPA) axis, as evidenced by a time and dose-dependent decrease in whole body corticosterone content. Reversing the decline in endogenous corticosterone caused by exposure to the alarm pheromone through addition of corticosterone to the aquarium water (50 nM) partially blocked the anti-predator behavior, suggesting that the suppression of the HPA axis promotes the expression and maintenance of a behaviorally quiescent state. To our knowledge this is the first evidence for aquatic vertebrate prey actively secreting an alarm pheromone in response to predator attack. We also provide a neuroendocrine mechanism by which the behavioral inhibition caused by exposure to the alarm pheromone is maintained until the threat subsides.

The effect of prior experience on a prey's current perceived risk.

The prior experience of prey may influence how they assess the level of predation risk associated with an information source. Here, I present the results from a set of experiments that demonstrate how the prior experience of green frog (Rana clamitans) tadpoles can influence their risk assessment during exposure to the chemical cue of predatory larval dragonflies (Anax spp.) consuming conspecific tadpoles. At the short-term scale, green frog tadpoles perceived a higher level of risk when consecutive cue exposures overlapped, but only when the total chemical cue concentration was weak. Weaker chemical cue concentrations may be less reliable than stronger cue concentrations, and overlapping cue exposures may increase the degree of certainty that tadpoles have in their perceived risk. When consecutive cue exposures did not overlap, tadpoles assessed the risk associated with each cue exposure independently. Predator-conditioned tadpoles responded longer during exposure to the Anax chemical cue than nonconditioned tadpoles, which suggests that a tadpole's long-term experience eventually does influence its risk assessment. In general, the results suggest that a prey's prior experience may influence its current perceived risk by influencing either the degree of certainty in or the level of its perceived risk. Understanding how the prior experience of prey influences their current risk assessment requires that the rate of decay of the value of prior experience should be identified at two timescales as an indicator of the current level of predation risk.

The dynamics of predation risk assessment: responses of anuran larvae to chemical cues of predators.

1. While the antipredator behaviour of prey has been well studied, little is known about the rules governing the predation risk assessment of prey. In this study, I measured the activity levels of predator-naive green frog (Rana clamitans) tadpoles during and after exposures to the chemical cue of predatory larval dragonflies (Anax spp.). I then used the lengths of the time lags from the end of the cue exposures until the tadpoles returned to a control level of activity as an index of the perceived risk of the tadpoles. 2. While tadpoles always responded upon exposure to the Anax chemical cue by strongly reducing their activity level, their perceived risk increased asymptotically over time during the initial period of the cue exposure. Tadpoles of all size classes perceived increasing risk in proportion to chemical cue concentration, but the length of time that tadpoles responded during cue exposure and the length of their post-exposure time lags decreased with increasing body mass. 3. The results suggest that the perceived risk of green frog tadpoles varies over time and does not correspond directly to their behavioural response (i.e. activity level). However, their perceived risk does appear to vary in accordance with the predation risk associated with the Anax chemical cue and the reliability of the information from the cue, and therefore may be predictable.

The influence of the circadian rhythm of green frog (Rana clamitans) tadpoles on their antipredator behavior and the strength of the nonlethal effects of predators.

Prey trade off predation risk and foraging gain in their activity level. Their response to this trade-off mediates direct and indirect interactions between predators and the community (i.e., nonlethal effects). A prey's activity level may also vary independently because of circadian rhythms. I tested how the antipredator behavior of green frog (Rana clamitans) tadpoles can be influenced by their circadian rhythm (primarily nocturnal feeding) and how the strengths of nonlethal effects vary in turn. Tadpoles exhibited stronger activity reductions when under predation risk during the day (which may result in stronger resource depression). However, when predation risk was high and persistent, tadpoles remained inactive during both day and night. Consequently, the nonlethal effect on tadpoles (growth rate reduction) was more negative at night. Predicting prey behavior and its effects requires identifying how their perceived risk interacts with and is limited by all factors that can influence their response.