Instream flow needs in streams and rivers: the importance of understanding ecological dynamics

Anderson, Kurt E.; Paul, Andrew J.; McCauley, Edward; Jackson, Leland J.; Post, John R.; Nisbet, Roger M.

doi:10.1890/1540-9295(2006)4[309:ifnisa]2.0.co;2

Cited by 169 publications

(179 citation statements)

References 20 publications

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“…The relationship between total volume (Vol) and the principal eigenvalue Λ 1 is weak relative to the other metrics, suggesting Vol is a poor persistence indicator. This agrees with more focused analytic and numerical results in Sarhad et al (2014) and empirical results from Anderson et al (2006) that habitat size alone cannot adequately characterize population persistence in a system. While R min and R max seem promising in characterizing the behavior of Λ 1 , it is CM that best predicts both qualitatively and quantitatively the principal eigenvalue.…”

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confidence: 88%

Geometric indicators of population persistence in branching continuous-space networks

2016

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We study population persistence in branching tree networks emulating systems such as river basins, cave systems, organisms on vegetation surfaces, and vascular networks. Population dynamics are modeled using a reaction-diffusion-advection equation on a metric graph which provides a continuous, spatially explicit model of network habitat. A metric graph, in contrast to a standard graph, allows for population dynamics to occur within edges rather than just at graph vertices, subsequently adding a significant level of realism. Within this framework, we stochastically generate branching tree networks with a variety of geometric features and explore the effects of network geometry on the persistence of a population which advects toward a lethal outflow boundary. We identify a metric (CM), the distance from the lethal outflow point at which half of the habitable volume of the network lies upstream of, as a promising indicator of population persistence. This metric outperforms other metrics such as the maximum and minimum distances from the lethal outflow to an upstream boundary and the total habitable volume of the network. The strength of CM as a predictor of persistence suggests that it is a proper "system length" for the branching networks we examine here that generalizes the concept of habitat length in the classical linear space models.Keywords Population dynamics · Branching networks · Reaction-diffusionadvection · Partial differential equations · (Metric) graph theory · Principal eigenvalue analysis Mathematics Subject Classification 05C12 (distance in graphs) · 35K57 (reactiondiffusion) · 58C40 (spectral theory; eigenvalue problems) · 35K20 (initial-boundary value problems for second-order parabolic equations) · 35J25 (boundary value problems for second-order elliptic equations) · 92D40 (ecology)

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confidence: 88%

Geometric indicators of population persistence in branching continuous-space networks

2016

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“…Rosenfeld and Taylor, 2009). With additional assumptions, they have been used to predict larger spatial patterns of biomass distribution or capacity (Grossman et al, 2002;Hayes et al, 2007;Hughes, 1998), but a remaining challenge is linking spatial patterns of growth and survival to population viability (Anderson et al, 2006b;Armstrong and Nislow, 2012;Frank et al, 2011;Locke et al, 2008). Individual-based modeling (IBM) approaches based on the bioenergetics of specific life stages for individual fish have been the most successful at this integration and have shown great utility in river management contexts (Van Winkle et al, 1998;Vincenzi et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…Milhous and Waddle, 2012). These methods explicitly consider only the tolerance of individuals in target populations to general flow and habitat variables (Anderson et al, 2006b), yet preserving the viability of managed populations and ecosystems is fundamental to modern EFA thinking (Arthington et al, 2006;Locke et al, 2008;Poff et al, 2010;Richter et al, 2006;Tharme, 2003). Further progress requires explicitly linking changes in the flow regime and habitat availability with population dynamics (Shenton et al, 2012), as population viability necessitates that additions of new individuals to the population exceed losses over the long term.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the influence of flow on invertebrate drift across spatial scales using a 2D hydraulic model and a 1D population model

Anderson

Harrison

Nisbet

et al. 2013

Ecological Modelling

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a b s t r a c tMethods for creating explicit links in environmental flow assessments between changes in physical habitat and the availability and delivery rate of macroinvertebrates that comprise fish diets are generally lacking. Here, we present a hybrid modelling approach to simulate the spatial dynamics of macroinvertebrates in a section of the Merced River in central California, re-engineered to improve the viability of Chinook salmon. Our efforts focused on quantifying the influence of the hydrodynamic environment on invertebrate drift dispersal, which is a key input to salmon bioenergetics models. We developed a twodimensional hydrodynamic model that represented flow dynamics well at baseflow and 75% bankfull discharges. Hydraulic predictions from the 2D model were coupled with a particle tracking algorithm to compute drift dispersal, where the settling rates of simulated macroinvertebrates were parameterized from the literature. Using the cross-sectional averaged velocities from the 2D model, we then developed a simpler 1D representation of how dispersal distributions respond to flow variability. These distributions were included in 1D invertebrate population models that represent variability in drift densities over reach scales. Dispersal distributions in the 2D simulation and 1D representation responded strongly to spatial changes in flow. When included in the 1D population model, dispersal responses to flow 'scaled-up' to yield distributions of drifting macroinvertebrates that showed a strong inverse relationship with flow velocity. The strength of the inverse relationship was influenced by model parameters, including the rate at which dispersers settle to the benthos. Finally, we explore how the scale of riffle/pool variability relative to characteristic length scales calculated from the 1D population model can be used to understand drift responses for different settling rates and at different discharges. We show that, under the range of parameter values explored, changes in velocity associated with transitions between riffles and pools produce local changes in drift density of proportional magnitude. This simple result suggests a means for confronting model predictions against field data.

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“…This assumption is not supported by ecological theory (e.g. Anderson et al, 2006), the statistical descriptions of HAMs are often incorrect and lack any causal basis (Lancaster and Belyea, 2006; in review a) and, thus, predictions based on HAMs may be wrong. Further, freshwater studies involving HAMs are carried out typically on a single, freshwater life stage whereas most freshwater species have complex life cycles (e.g.…”

Section: Introductionmentioning

confidence: 99%

Experimentation at the interface of fluvial geomorphology, stream ecology and hydraulic engineering and the development of an effective, interdisciplinary river science

Rice

Lancaster

Kemp

2009

Earth Surf Processes Landf

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One "2020 vision" for fluvial geomorphology is that it sits alongside stream ecology and hydraulic engineering as a key element of an integrated, interdisciplinary river science. A challenge to this vision is that scientists from these three communities may approach problems from different perspectives with different questions and have different methodological outlooks. Refining interdisciplinary methodology is important in this context, but raises a number of issues for geomorphologists, ecologists and engineers alike. In particular, we believe that it is important that there is greater dialogue about the nature of mutually-valued questions and the adoption of mutually-acceptable methods. As a contribution to this dialogue we examine the benefits and challenges of using physical experimentation in flume laboratories to ask interdisciplinary questions. Working in this arena presents the same challenges that experimental geomorphologists and engineers are familiar with (scaling up results, technical difficulties, realism) and some new ones including recognising the importance of biological processes, identifying hydraulically meaningful biological groups, accommodating the singular behaviour of individuals, understanding biological as well as physical stimuli, and the husbandry and welfare of live organisms. These issues are illustrated using two examples from flume experiments designed (1) to understand how the movement behaviours of aquatic insects through the near-bed flow field of gravelly river beds may allow them to survive flood events, and (2) how an understanding of the way in which fish behaviours and swimming capability are affected by flow conditions around artificial structures can lead to the design of effective fish passages. In each case, an interdisciplinary approach has been of substantial mutual benefit and led to greater insights than discipline-specific work would have produced. Looking forward to 2020, several key challenges for experimentalists working on the interface of fluvial geomorphology, stream ecology and hydraulic engineering are identified.3

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Instream flow needs in streams and rivers: the importance of understanding ecological dynamics

Cited by 169 publications

References 20 publications

Geometric indicators of population persistence in branching continuous-space networks

Geometric indicators of population persistence in branching continuous-space networks

Modeling the influence of flow on invertebrate drift across spatial scales using a 2D hydraulic model and a 1D population model

Experimentation at the interface of fluvial geomorphology, stream ecology and hydraulic engineering and the development of an effective, interdisciplinary river science

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