Limnology and Oceanography e-Books
Eco-DAS X Symposium Proceedings
The Ecological Dissertations in the Aquatic Sciences (Eco-DAS) symposia bring together 35-40 recent PhD recipients for one week in alternate years. Eco-DAS X was held in 2012. Eco-DAS is sponsored by the Center for Microbial Oceanography: Research and Education (C-MORE), the University of Hawai`i School of Ocean and Earth Science and Technology (SOEST) and its Department of Oceanography, and the Association for the Sciences of Limnology and Oceanography (ASLO). The Proceedings of Eco-DAS X includes six chapters published in open access.
Editor: Paul F Kemp
Eco-DAS X Manager: Lydia J. Baker
Funding provided by U.S. National Science Foundation award OCE08-12838 to Paul F. Kemp
Table of Contents
For the entire book, a suggested citation is as follows.
P.F. Kemp [ed.] 2014. Eco-DAS X Symposium Proceedings. Waco, TX: Association for the Sciences of Limnology and Oceanography. DOI: 10.4319/ecodas.2014.978-0-9845591-4-5. For an individual chapter, a suggested citation is provided in the accompanying abstract.
Quantifying co-occurrence patterns in space and time across aquatic systems with network analysis
Chapter 1, p. 1-13
Full Citation: Christopher J. Patrick, Kyle Cavanaugh, Talina Konotchick, and Hannes Peter. 2014. Quantifying co-occurrence patterns in space and time across aquatic systems with network analysis, p. 1-13. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5.1]
ABSTRACT: Network analytic techniques have been used to analyze the connections between organisms, which is a central theme in community ecology. We analyze species co-occurrence patterns from four aquatic ecosystems (the coastal ocean, kelp forest, streams, and lakes) using decadal-scale datasets. Both spatial and temporal co-occurrence networks are analyzed using a set of commonly used network metrics and compared to scale-free and random model networks. Additionally, we present a conceptual model that links increases in spatial connectivity (and species dispersal) to increases in the size and connectedness of spatial co-occurrence networks and decreases in the size and connectedness of temporal co-occurrence networks within those metacommunities. We then discuss the results from each ecosystem in relation to this conceptual model. For temporal co-occurrence networks, size metrics (i.e., diameter and average path length) were high in the stream case study, and both kelp forests and streams showed high connectivity. For spatial co-occurrence networks, the coastal ocean had the high connectivity and the lakes and streams had relatively high size metrics. Stability of spatial networks through time was variable between the four ecosystems, with kelp forests showing the most year-to-year variability across all metrics. Species co-occurrence patterns from long-term ecological datasets can yield valuable insights into spatial and temporal dynamics of ecosystems.
Temporal scales of drivers of community dynamics: from microbes to macrofauna across the salinity gradient
Chapter 2, p. 14-24
Full Citation: Beth A. Stauffer, Christopher J. Patrick, Kelly L. Robinson, and Hannes Peter. 2014. Temporal scales of drivers of community dynamics: from microbes to macrofauna across the salinity gradient, p. 14-24. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5.14]
ABSTRACT: The abundance and distribution of organisms in aquatic systems are affected by drivers operating at diverse temporal and spatial scales. Understanding interactions among organisms and with their environments is dependent on matching population and community dynamics with drivers at relevant scales, which can range from hours to decades. Here, we review how physical, chemical, and biological processes operating at these varying scales affect the abundance and the distribution of organisms in aquatic ecosystems spanning the salinity gradient: lake, stream, and coastal ocean. We highlight ecosystems that are representative of the different aquatic regimes and perform a conceptual synthesis of the similarities and differences among those systems. Our review underscores the important role drivers related to annual cycles of heat, light, and wind and water movement, for instance, play in structuring the physical, chemical, and biological constituents across fluid aquatic environments. Interannual to decadal variability in population dynamics across the salinity gradient is often related to long-term shifts in climate cycles or climate change; however, climate has differential effects in the coastal ocean (e.g. shifts in current strength), lakes (e.g. climatological variability in ice cover) and streams (e.g. decadal oscillations impacting salmon runs). We identify several potential avenues for future research, including long-term forcing in lakes and streams; the drivers and effects of high-frequency, episodic disturbance events; the influence of variability on eco-evolutionary feedbacks; and nonlinear effects of climate forces on ecosystems. We recommend maximizing the effectiveness of investigations across multiple temporal scales through programs using a variety of approaches including long-term monitoring and short-term, event-driven responses, and a new generation of tools and analytical approaches capable of resolving nonlinear dynamics over time in complex aquatic ecosystems.
Linking the bottom to the top in aquatic ecosystems: mechanisms and stressors of benthic-pelagic coupling
Chapter 3, p. 25-47
Full Citation: Melissa M. Baustian, Gretchen J. A. Hansen, Anna de Kluijver, Kelly Robinson, Emily N. Henry, Lesley B. Knoll, Kevin C. Rose, and Cayelan C. Carey. 2014. Linking the bottom to the top in aquatic ecosystems: mechanisms and stressors of benthic-pelagic coupling, p. 25-47. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5.25]
ABSTRACT: Linkages between benthic and pelagic habitats occur in both freshwater and marine systems across multiple spatial and temporal scales, and are influenced by a number of chemical, biological, and physical forces. We identified three major mechanisms of benthic-pelagic coupling: (1) organism movement, (2) trophic interactions, and (3) biogeochemical cycling. We also explore the implications of several stressors, including invasive species and climate change that will inevitably impact the linkages between benthic and pelagic habitats. We identify critical research gaps that need to be addressed to quantify the habitat coupling of these ecosystems. We advocate for more collaboration among scientists with expertise in benthic and pelagic habitats in both freshwater and marine ecosystems to fully understand the cycles, interactions, processes, and functions of benthic-pelagic coupling in ecosystems. Finally, we suggest targeted research needs for better capturing of cross-ecosystem linkages in aquatic ecology.
A more inclusive loop: Examining the contribution of five bacterial specialists to nutrient cycling and the microbial loop
Chapter 4, p. 48-68
Full Citation: Erin R. Graham, Huan Chen, Claudia Dziallas, Beatriz Fernández-Gómez, and John B. Kirkpatrick. 2014. A more inclusive loop: Examining the contribution of five bacterial specialists to nutrient cycling and the microbial loop, p. 48-68. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5-48]
ABSTRACT: Marine microbes have been studied for centuries. However, only in the past four decades have microbes been recognized as drivers of energy and nutrient cycles in the ocean. Several pivotal publications in the mid- to late-twentieth century affirmed the role of microbes in primary production and consumption of dissolved organic matter. These findings supported the hypothesis that microbes provide a link in the food web between phytoplankton, dissolved nutrients, and zooplankton. This concept became known as the microbial loop. More recent discoveries have identified additional contributors to the loop, such as novel phototrophic bacteria, archaea and viruses, yet the role of many microbial specialists in nutrient cycling remains unclear. In this chapter, we summarize the history and development of the microbial loop concept, and discuss five bacterial groups whose contribution to the microbial loop has largely been overlooked in the literature. We propose a modified loop that integrates processes performed by nitrogen-fixing bacteria, particle- and organism- associated bacteria, bacterial symbionts, Flavobacteria, and predatory bacteria, and conclude that the microbial loop must continue to evolve as the ecology of additional microbial specialists is revealed.
How extreme is extreme?
Chapter 5, p. 69-87
Full Citation: Brandi Kiel Reese, Julie A Koester, John Kirkpatrick, Talina Konotchick, Lisa Zeigler Allen, and Claudia Dziallas. 2014. How extreme is extreme?, p. 69-87. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5-69]
ABSTRACT:A vast majority of Earth's aquatic ecosystems are considered to be extreme environments by human standards, yet they are inhabited by a wide diversity of organisms. This review explores ranges of temperature, pH, and salinity that are exploited by the three domains of life and viruses in aquatic systems. Four Eukarya subgroups are considered: microalgae, fungi, macroalgae, and protozoa. The breadth of environmental ranges decreases with increasing cellular complexity. Bacteria and Archaea can live in environments that are not physiologically accessible to the macroalgae. Common strategies of adaptation across domains are discussed; for example, organisms in all three domains similarly alter cellular lipid saturation in membranes in response to temperature. Unique adaptations of each group are highlighted. This review challenges the use of the word "extreme" to describe many ecosystems, as the title is applied in relation to human habitability, yet a majority of life on the planet exists outside our habitable zone. Examining traits of the boundary lineages, those that exist at the physiological edge of the entire biome, or within a specific group, will provide a better understanding of life on Earth and provide a starting point to advance future detection of life on Earth and elsewhere.
Taking the pulse of the ecosystem: progress in quantifying aquatic ecosystem health
Chapter 6, p. 88-105
Full Citation: Sarah S. Roley, Jennifer R. Griffiths, Peter S. Levi, Christopher J. Patrick, Steven Sadro, and Jay P. Zarnetske. 2014. Taking the pulse of the ecosystem: progress in quantifying aquatic ecosystem health, p. 88-105. In P.F. Kemp [ed.], Eco-DAS X Symposium Proceedings. ASLO. [doi:10.4319/ecodas.2014.978-0-9845591-4-5-88]
ABSTRACT: Ecosystem health metrics quantify the cumulative effects of stressors on ecosystem structure and function, and inform management, restoration, and policy decisions. Freshwater ecosystems, in particular, face numerous stressors, and as a result, there is an increasing array of health metrics applied to their management. In this chapter, we review the current use of ecosystem health metrics, develop a preliminary framework for metric selection, and identify gaps in the current suite of metrics. The existing metrics typically characterize the biological, physical, or chemical attributes of ecosystems, whereas a few additional metrics integrate across these categories. Metrics vary in complexity, ranging from simple, visual assessments that can be completed by volunteers, to complex numerical models with extensive data and expert input requirements. Overall, ecosystem health metrics are well developed and useful with metrics available to fit both general and specialized management needs. However, common challenges include difficulty in establishing suitable reference conditions, a lack of uncertainty estimates, and a lack of inter-metric comparisons. Recent technological improvements, such as remote sensing, computational models, and new genetic sequencing techniques, are facilitating the development of novel and more holistic metrics, including early warning metrics, coupled complex systems models, and the inclusion of public input data.