“New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use

Recent cyanobacterial blooms in otherwise unproductive lakes may be warning signs of impending eutrophication in lakes important for recreation and drinking water, but little is known of their historical precedence or mechanisms of regulation. Here, we examined long-term sedimentary records of both general and taxon-specific trophic proxies from seven lakes of varying productivity in the northeastern United States to investigate their relationship to historical in-lake, watershed, and climatic drivers of trophic status. Analysis of fossil pigments (carotenoids and chlorophylls) revealed variable patterns of past primary production across lakes over two centuries despite broadly similar changes in regional climate and land use. Sediment abundance of the cyanobacterium Gloeotrichia, a large, toxic, nitrogen-fixing taxon common in recent blooms in this region, revealed that this was not a new taxon in the phytoplankton communities but rather had been present for centuries. Histories of Gloeotrichia abundance differed strikingly across lakes and were not consistently associated with most other sediment proxies of trophic status. Changes in ice cover most often coincided with changes in fossil pigments, and changes in watershed land use were often related to changes in Gloeotrichia abundance, although no single climatic or land-use factor was associated with proxy changes across all seven lakes. The degree to which changes in lake sediment records co-occurred with changes in the timing of ice-out or agricultural land use was negatively correlated with the ratio of watershed area to lake area. Thus, both climate and land management appeared to play key roles in regulation of primary production in these lakes, although the manner in which these factors influenced lakes was mediated by catchment morphometry. Improved understanding of the past interactions between climate change, land use, landscape setting, and water quality underscores the complexity of mechanisms regulating lake and cyanobacterial production and highlights the necessity of considering these interactions—rather than searching for a singular mechanism—when evaluating the causes of ongoing changes in low-nutrient lakes

Networked lake science: how the Global Lake Ecological Observatory Network (GLEON) works to understand, predict and communicate lake ecosystem response to global change

The Global Lake Ecological Observatory Network (GLEON) has built an international, grassroots network of scientists and citizens, data, and lake observatories to advance understanding of lake ecosystems. Through careful attention to the professional needs and aspirations of a community, GLEON has formed as its foundation the trust and respect essential to product-based network science. As a consequence, GLEON is making significant advancements in lake ecosystem understanding through all “five legs of the table that support scientific understanding”—natural history, multiscale data, experiments, theory, and comparative studies—with particular emphasis on multiscale data and comparative studies. Technical products, such as cyberinfrastructure in support of network data and operations, software tools for calculating lake physical metrics (e.g., thermocline depth, buoyancy frequency, Schmidt stability), and lake metabolism, as well as ecosystem-scale numerical simulation software, have derived from GLEON collaborations and have become community resources catalyzing interdisciplinary science. Education and outreach initiatives have served to engage citizens from outside the traditional boundaries of academia directly in research. Moreover, these cross-boundary collaborations have provided essential links to lake and reservoir stakeholders who have informed how science is prioritized and communicated within GLEON. As a grassroots network, GLEON derives its momentum, flexibility, and impact from its talented members, who are committed to the future sustainability of lakes and reservoirs and the services they provide

Macrosystems ecology: Understanding ecological patterns and processes at continental scales

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisciplines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents

A Practical Guide for Managing Interdisciplinary Teams: Lessons Learned from Coupled Natural and Human Systems Research

Interdisciplinary team science is essential to address complex socio-environmental questions, but it also presents unique challenges. The scientific literature identifies best practices for high-level processes in team science, e.g., leadership and team building, but provides less guidance about practical, day-to-day strategies to support teamwork, e.g., translating jargon across disciplines, sharing and transforming data, and coordinating diverse and geographically distributed researchers. This article offers a case study of an interdisciplinary socio-environmental research project to derive insight to support team science implementation. We evaluate the project’s inner workings using a framework derived from the growing body of literature for team science best practices, and derive insights into how best to apply team science principles to interdisciplinary research. We find that two of the most useful areas for proactive planning and coordinated leadership are data management and co-authorship. By providing guidance for project implementation focused on these areas, we contribute a pragmatic, detail-oriented perspective on team science in an effort to support similar projects

A Global lake ecological observatory network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate processbased ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest

Coupling of fog and marine microbial content in the near-shore coastal environment

Microbes in the atmosphere (microbial aerosols) play an important role in climate and provide an ecological and biogeochemical connection between oceanic, atmospheric, and terrestrial environments. However, the sources and environmental factors controlling the concentration, diversity, transport, and viability of microbial aerosols are poorly understood. This study examined culturable microbial aerosols from a coastal environment in Maine (USA) and determined the effect of onshore wind speed and fog presence on deposition rate, source, and community composition. During fog events with low onshore winds

Interpretative Phenomenological Analysis of Soldiers’ Experiences of Being Married and Serving in the British Army

© 2016, Copyright © Taylor & Francis Group, LLC. ABSTRACT: Research suggests certain aspects of military life, especially operational deployments, may negatively impact military marriages. However, much of this research is from the United States and uses deductive quantitative methods. Qualitative research investigating the lived experiences of forming and maintaining marriages was conducted with six male U.K. Army personnel. Semistructured interviews were analyzed, using Interpretative Phenomenological Analysis, identifying five themes, each representing different dilemmas the soldiers’ had to balance to maintain successful marriages and Army careers. These five themes are best understood as practical, emotional, and cultural dilemmas that can be alleviated with practical and emotional methods; such factors could be used to build resilience in soldier’s marriages. These possible resilience factors could shape the content of interventions to increase resiliency in military marriages

Data Descriptor : Long-term chloride concentrations in North American and European freshwater lakes

Anthropogenic sources of chloride in a lake catchment, including road salt, fertilizer, and wastewater, can elevate the chloride concentration in freshwater lakes above background levels. Rising chloride concentrations can impact lake ecology and ecosystem services such as fisheries and the use of lakes as drinking water sources. To analyze the spatial extent and magnitude of increasing chloride concentrations in freshwater lakes, we amassed a database of 529 lakes in Europe and North America that had greater than or equal to ten years of chloride data. For each lake, we calculated climate statistics of mean annual total precipitation and mean monthly air temperatures from gridded global datasets. We also quantified land cover metrics, including road density and impervious surface, in buffer zones of 100 to 1,500m surrounding the perimeter of each lake. This database represents the largest global collection of lake chloride data. We hope that long-term water quality measurements in areas outside Europe and North America can be added to the database as they become available in the future.Peer reviewe

Iterative Near-Term Ecological Forecasting: Needs, Opportunities, And Challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward