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Results for “Ecological Complexity”

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USGS1995

Can we manage for biological diversity in the absence of science?

Conservation of biological diversity is dependent on sound scientific information about underlying ecological processes. Current knowledge of the composition, distribution, abundance and life cycles of most species of plants and animals is incomplete, insufficient, unreliable, or nonexistent. Contemporary managers are also confronted with additional levels of complexity related to varying degrees of knowledge and understanding about interactions of species and ecosystems. Consequently, traditional species-oriented management schemes may have unintended consequences and ecosystem-oriented management initiatives may fail in the face of inadequate or fragmentary information on the structure, function, and dynamics of biotic communities and ecological systems. Nevertheless, resource managers must make decisions and manage based on the best biological information currently available. Adaptive resource management may represent a management paradigm that allows managers to learn something about the species or systems that they are managing while they are managing, but potential pitfalls lurk for such approaches. In addition to lack of control over the primary physical, chemical, and ecological processes, managers also lack control over social, economic, and political parameters affecting resource management options. Moreover, appropriate goals may be difficult to identify and criteria for determining success may be elusive. Some management responsibilities do not lend themselves to adaptive strategies. Finally, the lessons learned from adaptive management are usually obtained from a highly situational context that may limit applicability in a wider range of situations or undermine confidence that problems and solutions were properly diagnosed and addressed. Several scenarios are critically examined where adaptive management approaches may be inappropriate or ineffective and where management for biological diversity may be infeasible or inefficient without a sound scientific basis. Whereas some level of management must exist to meet agency responsibilities, more research is needed to conserve biological diversity.

Wildlife Society Annual Conference↗

USGS2009

Sensitivity of system stability to model structure

A community is stable, and resilient, if the levels of all community variables can return to the original steady state following a perturbation. The stability properties of a community depend on its structure, which is the network of direct effects (interactions) among the variables within the community. These direct effects form feedback cycles (loops) that determine community stability. Although feedback cycles have an intuitive interpretation, identifying how they form the feedback properties of a particular community can be intractable. Furthermore, determining the role that any specific direct effect plays in the stability of a system is even more daunting. Such information, however, would identify important direct effects for targeted experimental and management manipulation even in complex communities for which quantitative information is lacking. We therefore provide a method that determines the sensitivity of community stability to model structure, and identifies the relative role of particular direct effects, indirect effects, and feedback cycles in determining stability. Structural sensitivities summarize the degree to which each direct effect contributes to stabilizing feedback or destabilizing feedback or both. Structural sensitivities prove useful in identifying ecologically important feedback cycles within the community structure and for detecting direct effects that have strong, or weak, influences on community stability. The approach may guide the development of management intervention and research design. We demonstrate its value with two theoretical models and two empirical examples of different levels of complexity. ?? 2009 Elsevier B.V. All rights reserved.

Ecological Modelling↗

USGS2010

Advances in the hydrogeochemistry and microbiology of acid mine waters

The last decade has witnessed a plethora of research related to the hydrogeochemistry and microbiology of acid mine waters and associated tailings and waste-rock waters. Numerous books, reviews, technical papers, and proceedings have been published that examine the complex bio-geochemical process of sulfide mineral oxidation, develop and apply geochemical models to site characterization, and characterize the microbial ecology of these environments. This review summarizes many of these recent works, and provides references for those investigating this field. Comparisons of measured versus calculated Eh and measured versus calculated pH for water samples from several field sites demonstrate the reliability of some current geochemical models for aqueous speciation and mass balances. Geochemical models are not, however, used to predict accurately time-dependent processes but to improve our understanding of these systems and to constrain possible processes that contribute to actual or potential water quality issues. Microbiological studies are demonstrating that there is much we have yet to learn about the types of different microorganisms and their function and ecology in mine-waste environments. A broad diversity of green algae, bacteria, archaea, yeasts, and fungi are encountered in acid mine waters, and a better understanding of their ecology and function may potentially enhance remediation possibilities as well as our understanding of the evolution of life.

International Geology Review↗

USGS2024

Stable isotopes reveal intertidal fish and crabs use bivalve farms as foraging habitat in Puget Sound, Washington

Bivalves such as oysters and clams have been farmed in intertidal zones across the Puget Sound region of the Salish Sea for thousands of years. The variety of gear types used on bivalve farms creates complex vertical structure and attachment points for aquatic epiphytes and invertebrates which increases habitat structural complexity, but may alter eelgrass cover in areas where bivalve farms and eelgrass meadows overlap. Eelgrass meadows are highly productive and ecologically foundational nearshore habitats that provide valuable ecosystem services including the provision of nursery, refuge, and foraging habitat. Aquaculture has been a key feature of the environment in the Puget Sound for millennia, however, little is known about how well aquaculture practices are integrated into the system, and what services they provide to mobile species assemblages relative to unfarmed eelgrass meadows. We used stable isotope mixing models to estimate, for several species of nearshore fish and crab in two areas of North Puget Sound, Washington, the percent diet originating from either a natural bottom habitat (eelgrass meadows), farm habitat (oyster farms), or pelagic planktonic sources. Our results indicate that several species of nearshore fish such as surf perch and staghorn sculpin derive a significant proportion of their diets from farm areas, while crabs derive most of their diets from eelgrass habitat, and stickleback derive a significant proportion of their diets from planktonic sources. The results indicate that foraging habitat uses are species specific, and that several species that spatially overlap bivalve farms obtained a large percentage of their diets from adjacent bivalve farm habitat.

Washington↗

USGS2006

An introduced predator alters Aleutian Island plant communities by thwarting nutrient subsidies

The ramifying effects of top predators on food webs traditionally have been studied within the framework of trophic cascades. Trophic cascades are compelling because they embody powerful indirect effects of predators on primary production. Although less studied, indirect effects of predators may occur via routes that are not exclusively trophic. We quantified how the introduction of foxes onto the Aleutian Islands transformed plant communities by reducing abundant seabird populations, thereby disrupting nutrient subsidies vectored by seabirds from sea to land. We compared soil and plant fertility, plant biomass and community composition, and stable isotopes of nitrogen in soil, plants, and other organisms on nine fox-infested and nine historically fox-free islands across the Aleutians. Additionally, we experimentally augmented nutrients on a fox-infested island to test whether differences in plant productivity and composition between fox-infested and fox-free islands could have arisen from differences in nutrient inputs between island types. Islands with historical fox infestations had soils low in phosphorus and nitrogen and plants low in tissue nitrogen. Soils, plants, slugs, flies, spiders, and bird droppings on these islands had low d15N values indicating that these organisms obtained nitrogen from internally derived sources. In contrast, soils, plants, and higher trophic level organisms on fox-free islands had elevated d15N signatures indicating that they utilized nutrients derived from the marine environment. Furthermore, soil phosphorus (but not nitrogen) and plant tissue nitrogen were higher on fox-free than fox-infested islands. Nutrient subsidized fox-free islands supported lush, high biomass plant communities dominated by graminoids. Fox-infested islands were less graminoid dominated and had higher cover and biomass of low-lying forbs and dwarf shrubs. While d15N profiles of soils and plants and graminoid biomass varied with island size and distance from shore, after accounting for these effects differences between fox-infested and fox-free islands still existed. Fertilization over four years caused a 24-fold increase in graminoid biomass and a shift toward a more graminoid dominated plant community typical of fox-free islands. These results indicate that apex predators can influence plant productivity and composition through complex interaction web pathways involving both top-down forcing and bottom-up nutrient exchanges across systems. ?? 2006 by the Ecological Society of America.

Ecological Monographs↗

USGS2016

Relations between rainfall–runoff-induced erosion and aeolian deposition at archaeological sites in a semi-arid dam-controlled river corridor

Process dynamics in fluvial-based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam-building affect fluvial processes, the complexity in local response can be further increased by flood- and sediment-limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi-temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446-km-long semi-arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam-controlled fluvial sand bar deposition, aeolian sand transport, and rainfall-induced erosion. Empirical rainfall-erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration-excess overland flow and gullying govern large-scale (centimeter- to decimeter-scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic-driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four-minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short-term, storm-driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi-arid landscapes where process complexity may not be fully understood.

Arizona↗

USGS2011

Networks - The assessment of marine reserve networks: Guidelines for ecological evaluation

As marine ecosystems are plagued by an ever-increasing suite of threats including climate change, pollution, habitat degradation, and fisheries impacts (Roessig et al ., 2004; Lotze et al ., 2006; Jackson, 2008), there are now no ocean areas that are exempt from anthropogenic impacts (Halpern et al ., 2008). In order to preserve marine biodiversity, ecosystem function, and the goods and services provided by resistant and/or resilient systems, marine reserves have been increasingly recommended as part of an ecosystem-based approach to management (Browman and Stergiou, 2004; Levin et al ., 2009). Marine reserves are defined as “areas of the ocean completely protected from all extractive and destructive activities” (Lubchenco et al ., 2003) and can be experimental controls for evaluating the impact of these activities on marine ecosystems. Growing scientific information has shown consistent increases in species density, biomass, size, and diversity in response to full protection inside reserves of varying sizes and ages located in diverse regions (Claudet et al ., 2008; Lester et al ., 2009; Molloy et al ., 2009). However, most of these data are from individual marine reserves and therefore have inherently limited transferability to networks of marine reserves, which when properly designed can outperform single marine reserves for a variety of ecological, economic, and social management goals (Roberts et al ., 2003; Almany et al ., 2009; Gaines et al ., 2010). The concept of marine reserve networks grew out of a desire to achieve both conservation and fishery management goals by minimizing the potential negative economic, social, and cultural impacts of a single large reserve while still producing similar or even greater ecological and economic returns (Murray et al ., 1999; Gaines et al ., 2010). In addition, reserves networks can provide insurance by protecting areas across a region and spreading the risk that these sites may be impacted by localized catastrophes such as hurricanes or oil spills (Allison et al ., 2003). The World Conservation Union's Marine Programme defines a network as “a collection of individual marine protected areas (MPAs) or reserves operating co-operatively and synergistically, at various spatial scales and with a range of protection levels that are designed to meet objectives that a single reserve cannot achieve” (IUCN–WCPA, 2008). However, general terms such as “co-operatively” and “synergistically” can have myriad meanings. Without a clear definition of a network, it becomes difficult to identify attainable management goals and design a process for evaluating whether the network achieves those goals. Besides, different management goals may in turn result in the need for different types of networks. The use of MPAs with varying protection levels together with no-take zones in multiple-zoning schemes adds another layer of complexity to network design and evaluation; however, partially protected areas are generally used to manage coastal uses and avoid conflicts (rather than for strict ecological purposes) and are therefore a function of the local social, economic, and cultural context. As we are here interested in the ecological effects of networks, for the purposes of this chapter, we focus on marine reserves because these areas are no-take and therefore offer greater ecological benefits than other types of MPAs that allow some forms of extraction (Lester and Halpern, 2008).

Book chapter↗

USGS2023

Decision science as a framework for combining geomorphological and ecological modeling for the management of coastal systems

The loss of ecosystem services due to climate change and coastal development is projected to have significant impacts on local economies and conservation of natural resources. Consequently, there has been an increase in coastal management activities such as living shorelines, oyster reef restoration, marsh restoration, beach and dune nourishment, and revegetation projects. Coastal management decisions are complex and include challenging trade-offs. Decision science offers a useful framework to address such complex problems. Here, we provide a synthesis about how decision science can help to integrate research from multiple disciplines (physical and life sciences) with management of coastal and marine systems. Specifically, we discuss the importance of considering concepts and techniques from ecology, coastal geology, geomorphology, climate science, oceanography, and decision analysis when developing conservation plans for coastal restoration. We illustrate the process with several coastal restoration studies. Our capstone example is based on a recent barrier island restoration assessment project at Dauphin Island, Alabama, which included the development of geomorphological and ecological models. We show how decision science can be used as a framework to combine geomorphological and ecological modeling to help inform management decisions while considering uncertainty about system changes and risk tolerance. We also build on our examples through a review of recently developed techniques for spatial conservation planning for land acquisition decisions and the application of adaptive management for sequential decisions.

Alabama↗

USGS2013

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

Conservation Biology↗

USGS2021

Temporal invariance of social-ecological catchments

Natural resources such as waterbodies, public parks, and wildlife refuges attract people from varying distances on the landscape, creating "social-ecological catchments." Catchments have provided great utility for understanding physical and social relationships within specific disciplines. Yet, catchments are rarely used across disciplines, such as its application to understand complex spatiotemporal dynamics between mobile human users and patchily distributed natural resources. We collected residence ZIP codes from 19,983 angler parties during 2014–2017 to construct seven angler–waterbody catchments in Nebraska, USA. We predicted that sizes of dense (10% utilization distribution) and dispersed (95% utilization distribution) angler–waterbody catchments would change across seasons and years as a function of diverse resource selection among mobile anglers. Contrary to expectations, we revealed that catchment size was invariant. We discuss how social (conservation actions) and ecological (low water quality, reduction in species diversity) conditions are expected to impact landscape patterns in resource use. We highlight how this simple concept and user-friendly technique can inform timely landscape-level conservation decisions within coupled social-ecological systems that are currently difficult to study and understand.

Ecological Applications↗

USGS2015

Effects of topoclimatic complexity on the composition of woody plant communities

Topography can create substantial environmental variation at fine spatial scales. Shaped by slope, aspect, hill-position and elevation, topoclimate heterogeneity may increase ecological diversity, and act as a spatial buffer for vegetation responding to climate change. Strong links have been observed between climate heterogeneity and species diversity at broader scales, but the importance of topoclimate for woody vegetation across small spatial extents merits closer examination. We established woody vegetation monitoring plots in mixed evergreen-deciduous woodlands that spanned topoclimate gradients of a topographically heterogeneous landscape in northern California. We investigated the association between the structure of adult and regenerating size classes of woody vegetation and multidimensional topoclimate at a fine scale. We found a significant effect of topoclimate on both single-species distributions and community composition. Effects of topoclimate were evident in the regenerating size class for all dominant species (four Quercus spp. , Umbellularia californica and Pseudotsuga menziesii ) but only in two dominant species ( Quercus agrifolia and Quercus garryana ) for the adult size class. Adult abundance was correlated with water balance parameters (e.g. climatic water deficit) and recruit abundance was correlated with an interaction between the topoclimate parameters and conspecific adult abundance (likely reflecting local seed dispersal). However, in all cases, the topoclimate signal was weak. The magnitude of environmental variation across our study site may be small relative to the tolerance of long-lived woody species. Dispersal limitations, management practices and patchy disturbance regimes also may interact with topoclimate, weakening its influence on woody vegetation distributions. Our study supports the biological relevance of multidimensional topoclimate for mixed woodland communities, but highlights that this relationship might be mediated by interacting factors at local scales.

California↗

USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗

USGS2022

A practical guide to understanding and validating complex models using data simulations

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4 ) and machine learning methods. These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal Nature Ecology & Evolution , and we found that the majority of published papers did not report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods. Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal Methods Ecology & Evolution . We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement. Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.

Methods in Ecology and Evolution↗

USGS2016

Surficial geological tools in fluvial geomorphology: Chapter 2

Increasingly, environmental scientists are being asked to develop an understanding of how rivers and streams have been altered by environmental stresses, whether rivers are subject to physical or chemical hazards, how they can be restored, and how they will respond to future environmental change. These questions present substantive challenges to the discipline of fluvial geomorphology, especially since decades of geomorphologic research have demonstrated the general complexity of fluvial systems. It follows from the concept of complex response that synoptic and short-term historical views of rivers will often give misleading understanding of future behavior. Nevertheless, broadly trained geomorphologists can address questions involving complex natural systems by drawing from a tool box that commonly includes the principles and methods of geology, hydrology, hydraulics, engineering, and ecology.

Book chapter↗

USGS2001

The introduction of nonnative fish into wilderness lakes: Good intentions, conflicting mandates, and unintended consequences

Because they have the potential to provide the best remaining standards of relatively unmodified landscapes, protected areas in North America (such as wilderness areas and national parks) have tremendous ecological and scientific value (Cole and Landres 1996). Although the montane ecosystems of western North America are particularly well represented in this complex of protected lands, aquatic habitats within these protected areas are often subject to management practices that are inconsistent with the goal of maintaining natural processes. The most prevalent of these practices is the introduction of salmonid fishes (such as trout) into historically fishless ecosystems to create recreational fisheries.

Ecosystems↗

USGS2005

Assessing uncertainty in ecological systems using global sensitivity analyses: A case example of simulated wolf reintroduction effects on elk

Often landmark conservation decisions are made despite an incomplete knowledge of system behavior and inexact predictions of how complex ecosystems will respond to management actions. For example, predicting the feasibility and likely effects of restoring top-level carnivores such as the gray wolf ( Canis lupus ) to North American wilderness areas is hampered by incomplete knowledge of the predator-prey system processes and properties. In such cases, global sensitivity measures, such as Sobol’ indices, allow one to quantify the effect of these uncertainties on model predictions. Sobol’ indices are calculated by decomposing the variance in model predictions (due to parameter uncertainty) into main effects of model parameters and their higher order interactions. Model parameters with large sensitivity indices can then be identified for further study in order to improve predictive capabilities. Here, we illustrate the use of Sobol’ sensitivity indices to examine the effect of parameter uncertainty on the predicted decline of elk ( Cervus elaphus ) population sizes following a hypothetical reintroduction of wolves to Olympic National Park, Washington, USA. The strength of density dependence acting on survival of adult elk and magnitude of predation were the most influential factors controlling elk population size following a simulated wolf reintroduction. In particular, the form of density dependence in natural survival rates and the per-capita predation rate together accounted for over 90% of variation in simulated elk population trends. Additional research on wolf predation rates on elk and natural compensations in prey populations is needed to reliably predict the outcome of predator–prey system behavior following wolf reintroductions.

Ecological Modelling↗

USGS2010

Conceptual ecological models to guide integrated landscape monitoring of the Great Basin

The Great Basin Integrated Landscape Monitoring Pilot Project was developed in response to the need for a monitoring and predictive capability that addresses changes in broad landscapes and waterscapes. Human communities and needs are nested within landscapes formed by interactions among the hydrosphere, geosphere, and biosphere. Understanding the complex processes that shape landscapes and deriving ways to manage them sustainably while meeting human needs require sophisticated modeling and monitoring. This document summarizes current understanding of ecosystem structure and function for many of the ecosystems within the Great Basin using conceptual models. The conceptual ecosystem models identify key ecological components and processes, identify external drivers, develop a hierarchical set of models that address both site and landscape attributes, inform regional monitoring strategy, and identify critical gaps in our knowledge of ecosystem function. The report also illustrates an approach for temporal and spatial scaling from site-specific models to landscape models and for understanding cumulative effects. Eventually, conceptual models can provide a structure for designing monitoring programs, interpreting monitoring and other data, and assessing the accuracy of our understanding of ecosystem functions and processes.

Scientific Investigations Report↗

USGS2019

Ecosystem size predicts social dynamics in recreational fisheries

Recreational fisheries are complex adaptive systems that are inherently difficult to manage due to a heterogeneous user group (consumptive vs. non-consumptive) that utilize patchily distributed resources on the landscape (lakes, rivers, coastlines). There is a need to identify which system components can effectively predict and be used to manage nonlinear and cross-scale dynamics within these systems. We examine how ecosystem size or waterbody size can be used to explain complicated and elusive angler-resource dynamics in recreational fisheries. Waterbody size determined angler behavior among 48 Nebraska, U.S.A. waterbodies during an 11-year study period. Angler behavior was often unique and nonlinear across waterbody sizes. For example, anglers spent more time fishing and harvested more fish at larger waterbodies compared to smaller waterbodies. Time fished increased across smaller waterbodies but reached a threshold at larger waterbodies. The number of fish released increased as a function of waterbody size across smaller waterbodies but then plateaued. Subtle changes in waterbody size caused abrupt changes in angler behavior—that is, waterbody size structures angler-resource dynamics in recreational fisheries. We believe that including waterbody size, a simple and easily measured metric, in fisheries management will increase effectiveness of cross-scale actions and minimize unintended consequences for recreational fisheries. Applying uniform management actions (e.g., harvest regulations) across small and large waterbodies may elicit contrasting angler-resource responses. Waterbody size may also be useful for understanding angler typologies. Based on our findings, we expect that ecosystem size is a prominent and valuable system component that will determine and explain coupled user-resource dynamics in other complex adaptive systems.

Ecology and Society↗