Multi-decadal improvements in the ecological quality of European rivers are not consistently reflected in biodiversity metrics.

Humans impact terrestrial, marine and freshwater ecosystems, yet many broad-scale studies have found no systematic, negative biodiversity changes (for example, decreasing abundance or taxon richness). Here we show that mixed biodiversity responses may arise because community metrics show variable responses to anthropogenic impacts across broad spatial scales. We first quantified temporal trends in anthropogenic impacts for 1,365 riverine invertebrate communities from 23 European countries, based on similarity to least-impacted reference communities. Reference comparisons provide necessary, but often missing, baselines for evaluating whether communities are negatively impacted or have improved (less or more similar, respectively). We then determined whether changing impacts were consistently reflected in metrics of community abundance, taxon richness, evenness and composition. Invertebrate communities improved, that is, became more similar to reference conditions, from 1992 until the 2010s, after which improvements plateaued. Improvements were generally reflected by higher taxon richness, providing evidence that certain community metrics can broadly indicate anthropogenic impacts. However, richness responses were highly variable among sites, and we found no consistent responses in community abundance, evenness or composition. These findings suggest that, without sufficient data and careful metric selection, many common community metrics cannot reliably reflect anthropogenic impacts, helping explain the prevalence of mixed biodiversity trends.

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.

The International Vertebrate Pet Trade Network and Insights from US Imports of Exotic Pets.

The international trade in exotic vertebrate pets provides key social and economic benefits but also drives associated ecological, ethical, and human health impacts. However, despite its clear importance, we currently lack a full understanding of the structure of the pet trade, hampering efforts to optimize its benefits while mitigating its negative effects. In the present article, we represent and review the structure of the pet trade as a network composed of different market actors (nodes) and trade flows (links). We identify key data gaps in this network that, if filled, would enable network analyses to pinpoint targets for management. As a case study of how data-informed networks can realize this goal, we quantified spatial and temporal patterns in pets imported to the United States. Our framework and case study illustrate how network approaches can help to inform and manage the effects of the growing demand for exotic pets.

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.

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.

Stormwater ponds: An overlooked but plentiful urban designer ecosystem provides invasive plant habitat in a subtropical region (Florida, USA).

Designed ecosystems are built as part of ongoing urban expansion, providing a suite of valued ecosystem services. However, these new ecosystems could also promote disservices by facilitating the colonization and spread of invasive species. We conduct the first assessment of the quantity and invasion of an overlooked designed ecosystem: stormwater ponds. These ponds are commonly recommended for managing urban hydrology, but little is known about their ecology or extent of proliferation. Using a broad-scale survey of pond coverage in Florida, USA, we found that over 76,000 stormwater ponds have been built just in this state, forming 2.7% of total urban land cover. This extensive pondscape of manufactured habitats could facilitate species spread throughout urban areas and into nearby natural waterbodies. We also conducted a survey of the severity of plant invasion in 30 ponds in Gainesville, FL, US across two pond types (dry vs. wet), and a gradient of management intensities (low, medium, high) and pond ages. We unexpectedly found a high number of invasive plant species (28 in just 30 ponds). Ninety-six percent of surveyed ponds contained from one to ten of these species, with ponds exhibiting high turnover in invader composition (i.e., high beta diversity). The bank sections of dry unmanaged ponds exhibited the highest mean invasive species richness (5.8 ± 1.3) and the inundated centers of wet medium managed ponds exhibited the highest mean invasive species cover (34 ± 12%). Invasive plant richness and cover also tended to be greater in dry ponds with higher soil nutrient levels, and in older wet ponds. Therefore, we found that highly maintained and younger wet ponds were the least invaded. Nevertheless, common management practices that limit plant invasions may also limit native species establishment and invasion may increase in the decades following pond construction.

Developing a direct rating behavior scale for depression in middle school students.

Research has supported the applied use of Direct Behavior Rating Single-Item Scale (DBR-SIS) targets of "academic engagement" and "disruptive behavior" for a range of purposes, including universal screening and progress monitoring. Though useful in evaluating social behavior and externalizing problems, these targets have limited utility in evaluating emotional behavior and internalizing problems. Thus, the primary purpose of this study was to support the initial development and validation of a novel DBR-SIS target of "unhappy," which was intended to tap into the specific construct of depression. A particular focus of this study was on the novel target's utility within universal screening. A secondary purpose was to further validate the aforementioned existing DBR-SIS targets. Within this study, 87 teachers rated 1,227 students across two measures (i.e., DBR-SIS and the Teacher Observation of Classroom Adaptation-Checklist [TOCA-C]) and time points (i.e., fall and spring). Correlational analyses supported the test-retest reliability of each DBR-SIS target, as well as its convergent and discriminant validity across concurrent and predictive comparisons. Receiver operating characteristic (ROC) curve analyses further supported (a) the overall diagnostic accuracy of each target (as indicated by the area under the curve [AUC] statistic), as well as (b) the selection of cut scores found to accurately differentiate at-risk and not at-risk students (as indicated by conditional probability statistics). A broader review of findings suggested that across the majority of analyses, the existing DBR-SIS targets outperformed the novel "unhappy" target. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Relative importance of colonist quantity, quality, and arrival frequency to the extinction of two zooplankton species.

Colonist quantity, quality, and arrival frequency can all individually drive the dynamics and extinction of new populations. However, we do not understand which has the strongest influence, nor the circumstances under which their relative importance may change. We conducted a field mesocosm experiment that manipulated colonist quantity, quality, and arrival frequency in two zooplankton species (Daphnia pulicaria and Skistodiaptomus oregonensis). Individuals of each species were cultured under either high or low food concentrations to produce, respectively, 'good' and 'poor' quality colonists. Each species was then introduced at either small (2 individuals) or large introduction quantities (8 individuals) divided over single or multiple introduction events. We found that the extinction of Daphnia pulicaria was not particularly affected by any of our treatments. Introductions of just two individuals performed as well as larger or more frequent introductions, regardless of quality. Conversely, Skistodiaptomus oregonensis extinction was strongly driven by arrival frequency. Populations that arrived in a single event exhibited high rates of extinction (75-83%), with this probability declining dramatically when colonists were introduced over multiple events (33% extinction). Our results show that other less studied aspects of the colonist pool, such as arrival frequency, could be as important to population persistence as the initial quantity of arriving colonists. Additionally, there are potentially numerous species that are well suited to succeeding with a small number of founders, and whose success is therefore not necessarily dependent upon colonist quantity, quality, or arrival frequency.