At broad spatial scales, primary productivity in lakes is known to increase in concert with nutrients, and variables that may disrupt or modify the tight coupling of nutrients and algae are of ...increasing interest, particularly for those shifting with climate change. Storms may disrupt algae–nutrient relationships, but the expected effects differ between winter and summer seasons, particularly for seasonally ice‐covered lakes. In winter, storms can dramatically change the under‐ice light environment, creating light limitation that disrupts algae–nutrient relationships. Further, storms can bring both snow that blocks light and also wind that blows snow off of ice. In open water conditions, storms may promote turbulence and external nutrient loading. Here, we test the hypotheses that winter and summer storms differentially affect algae–nutrient relationships across 84 seasonally ice‐covered lakes included in the Ecology Under Lake Ice dataset. While nutrients explained most of the variation in chlorophyll across these lakes, we found that secondary drivers differed between seasons. Under‐ice chlorophyll was higher under a variety of precipitation and wind conditions that tend to promote snow‐free clear ice, highlighting the importance of light as a limiting factor for algal growth during winter. In summer, higher water temperatures and storms corresponded with higher chlorophyll. Our study suggests that examining ice‐covered lakes in a gradient from the perennial ice cover of the poles to the intermittent ice cover of lower latitudes would yield key information on the shifts in light and nutrient limitation that control algal biomass.
Pressing environmental research questions demand the integration of increasingly diverse and large‐scale ecological datasets as well as complex analytical methods, which require specialized tools and ...resources.
Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor‐ and time‐intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies.
Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers.
Although WMS requires familiarity with function‐oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.
Increasing bee diversity promotes pollination services on farms. Yet, given the high turnover in pollinator communities, without knowledge of how pollinator communities assemble, it is difficult to ...conserve or increase bee diversity. Thus, a mechanistic understanding of factors mediating pollinator community assembly could promote pollinator conservation measures.
To assess the determinants of pollinator community assembly and structure, we surveyed bee communities and floral resources on 36 farms ranging from 0 to 43 years in organic production. We used niche‐based and stochastic species abundance models to characterise the mechanisms driving community assembly, and an additive partition of beta diversity to evaluate resource and species turnover (i.e. community structure). We then used statistical models to assess whether resource turnover or time in organic production altered community assembly and beta diversity, and a jackknife analysis to assess the sensitivity of top models to resource and species identity.
We show that bee communities on farms that practiced organic methods for longer assembled by niche‐based rather than stochastic processes and had less turnover in bee species across years. Because our model of niche‐based processes assumes resource use, these results indicate bee communities reflect underlying species‐specific resource preferences (e.g. floral and/or nesting resources) and that longer periods of organic management reduced dissimilarity mediated by species replacement. Our jackknife approach then examined the role of species identity effects in beta diversity, showing changes in floral resources increased dissimilarity driven by bee species loss, but only in landscapes simplified by urbanisation. This jackknife analysis then indicated that landscape resource replacement which was not driven by particular landscape classes, mediated bee species replacement wherein dissimilarity was driven by a generalist native bee, suggesting bee life history (e.g. flexibility in resource use) and landscape complementarity, rather than identity, underlie patterns identified using the beta diversity equations.
Our results show bee communities assemble by niche‐based processes, evidenced by collinearity in resource and bee species turnover. Because niche‐based assembly indicates ecosystem health, farmers who adopt crop diversification and practice organic methods for longer may promote pollinator diversity and stability leading to improved pollination in farms.
Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog.
Lake trophic state is a key ecosystem property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, ...standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.
The abundance and diversity of pollinator populations are in global decline. Managed pollinator species, like honey bees, and wild species are key ecosystem service providers in both natural and ...managed agroecosystems. However, relatively few studies have exhaustively characterized pollinator populations in diverse agroecosystems over multiple years, while also thoroughly documenting plant–pollinator interactions. Yet, such studies are needed to fulfill the national pollinator protection plans that have been released by the United States and other nations. Our research is among the first studies to respond to these directives by systematically documenting bee and plant biodiversity, bee–plant interactions, and bee‐mediated pollen movement in farming systems of the Pacific Northwest, USA. Our data provides insight into the processes mediating pollinator and plant community assembly, persistence, and resilience across landscapes with variable crop and landscape diversity and agroecosystem management practices. These data will also contribute to the development of a United States pollinator database, supporting the United States' plan to promote pollinators. With few publicly available data sets that systematically take account of agroecosystem practices, plant populations, and pollinators, our research will provide future users the means to conduct synesthetic studies of pollinators and ecosystem function in a period of rapid and global pollinator declines. There are no copyright or proprietary restrictions for research or teaching purposes. Usage of the data set must be cited.
Human sewage can introduce pollutants into food webs and threaten ecosystem integrity. Among the many sewage-associated pollutants, pharmaceuticals and personal care products (PPCPs) are consistent ...indicators of sewage in ecosystems and can also cause potent ecological consequences, even at minute concentrations (e.g., ng/L). Despite increased study over the past three decades, PPCPs in terrestrial ecosystems have been less studied than those in aquatic ecosystems. To evaluate PPCP prevalence and drivers in a terrestrial ecosystem, we analyzed managed and native bees collected from agroecosystems in Washington State (USA) for PPCPs. Caffeine, paraxanthine, cotinine, and acetaminophen were detected in all three evaluated taxa (
Bombus vosnesenskii
,
Agapostemon texanus
, and
Apis mellifera
), with
B. vosnesenskii
and
A. texanus
having a higher probability of PPCP detection relative to
A. mellifera
. The probability of PPCP presence in all three taxa increased in landscapes with more human development and greater plant abundance, with significant but negative interactions among these factors. These results suggest that human activity, availability of resources, and species-specific pollinator traits affect the introduction and mobilization of PPCPs in terrestrial ecosystems. Consequently, monitoring PPCPs and their ecological responses in terrestrial ecosystems creates opportunities to synthesize effects of sewage pollution across terrestrial and aquatic ecosystem types and organisms.
An increasing population in conjunction with a changing climate necessitates a detailed understanding of water abundance at multiple spatial and temporal scales. Remote sensing has provided massive ...data volumes to track fluctuations in water quantity, yet contextualizing water abundance with other local, regional, and global trends remains challenging by often requiring large computational resources to combine multiple data sources into analytically-friendly formats. To bridge this gap and facilitate future freshwater research opportunities, we harmonized existing global datasets to create the Global Lake area, Climate, and Population (GLCP) dataset. The GLCP is a compilation of lake surface area for 1.42 + million lakes and reservoirs of at least 10 ha in size from 1995 to 2015 with co-located basin-level temperature, precipitation, and population data. The GLCP was created with FAIR (findable, accessible, interoperable, reusable) data principles in mind and retains unique identifiers from parent datasets to expedite interoperability. The GLCP offers critical data for basic and applied investigations of lake surface area and water quantity at local, regional, and global scales.
Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on ...the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice.
Plain Language Summary
Lakes are experiencing accelerated rates of warming, including shorter seasonal duration of ice cover, later ice‐on, earlier ice‐off, and in some years no ice cover at all. Lake ice has been historically studied independently by four subdisciplines: observations by in situ and remote sensing scientists, controlled mesocosm experiments by limnologists, and process‐based models by physical modelers. Here, we highlight opportunities for collaboration between disciplines and provide guidelines to successfully integrate the disciplines to tackle the most urgent questions surrounding lake ice loss in warming climates.
Key Points
Ripe opportunity to merge disciplines and harmonize data streams to further understand lake ice dynamics in changing winters
Develop integrated plans for future data collection by moving from ice cover and phenology to multifaceted descriptions of ice conditions
Operationalize development of skill sets to work in multidisciplinary teams by constructing a workforce and developing a common language
Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world's most ancient, biodiverse, and voluminous ...freshwater lake, has been experiencing localized sewage pollution from lakeside settlements. Nearby increasing filamentous algal abundance suggests benthic communities are responding to localized pollution. We surveyed 40‐km of Lake Baikal's southwestern shoreline from 19 to 23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics, with colocated periphyton, macroinvertebrate, stable isotope, and fatty acid samplings. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage reuse. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset's 150+ variables. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales.
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