A Landscape and Systems Ecology Approach for Predicting Fish Concentration in Seasonally Pulsed and Spatially Heterogeneous Wetlands

Seasonal pulsing of hydrology in the Greater Everglades watershed produces dynamic, annual cycles of wetland flooding and drying, and of environmental conditions. Biota have adapted to exploit these pulses through movement and foraging behaviors. A primary ecological concern, pertinent to Everglades restoration, is to understand how sufficient concentration of aquatic biomass, particularly that of small fish and invertebrates, is produced under nutrient limited conditions, to support diverse and abundant communities of piscivorous predators, such as wading birds and herpetofauna. This question is investigated through computer simulation modeling of small−bodied fishes in the freshwater Everglades, and analyses of empirical monitoring data of mangrove−associated fishes along the shoreline of southern Florida. In the freshwater Everglades, concentration of biomass, through interactions between movement behaviors, spatial heterogeneity of the landscape, and declining water levels, has been hypothesized to be a key function for making biomass available in useable densities. Fish avoid drying conditions by moving to adjacent refugia, and in the process become highly concentrated in localized areas. Although this conceptual picture is well known, spatially explicit prediction of the timing, magnitude, and duration of fish concentration across the landscape has not been possible. Here, a computer modeling approach, aimed at complementing monitoring, is developed for simulating and analyzing landscape and food web dynamics of pulsed wetland ecosystems, by explicitly tracking growth and concentration of fish biomass, and accounting for dynamic movement behaviors in response to spatiotemporally shifting environmental conditions. In coastal mangrove habitats, fluctuating and extreme salinity conditions have been hypothesized to constrain fish populations, and avoidance of hypersaline areas through movement is possible. Fish densities were related to frequency of hypersalinity over defined periods preceding surveys. Complementary quantile regression techniques were applied to make inferences on behavioral, population, and predator−prey dynamics, which can be tested with modeling. Ecological responses at multiples spatial and temporal scales were investigated in both the empirical and simulation studies. Spatially explicit maps of biomass concentrations, across these scales, were generated from simulation models, and effects of hydrology and landscape connectivity on fish biomass were shown. This methodology offers a new approach for using empirical analyses to generate hypotheses and theory which can be investigated with computer simulation modeling, and for using computer modeling to inform decisions on monitoring strategy and resource management.</p

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to the risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application of risk management theory to conservation emphasizes the diversification of a portfolio of assets, with the goal of reducing the impact of system volatility on investment return.We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate-driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio trade-offs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea-level rise projections, conversion of habitat to open water (14–180%) and wetland loss (1–7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to the risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application of risk management theory to conservation emphasizes the diversification of a portfolio of assets, with the goal of reducing the impact of system volatility on investment return.We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate-driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio trade-offs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea-level rise projections, conversion of habitat to open water (14–180%) and wetland loss (1–7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate

Estimating the Influence of Oyster Reef Chains on Freshwater Detention at the Estuary Scale Using Landsat-8 Imagery

Oyster reef chains grow in response to local hydrodynamics and can redirect flows, particularly when reef chains grow perpendicular to freshwater flow paths. Singularly, oyster reef chains can act as porous dams that may facilitate nearshore accumulation of fresh or low-salinity water, in turn creating intermediate salinities that support oyster growth and estuarine conditions. However, oyster-driven freshwater detention has only been confirmed by limited, point-scale observational data, and simplified models. Oyster reef-driven freshwater detention in real ecosystems at the estuary scale remains largely unexplored. In this study, we analyzed the visible bands in 30-m resolution remote sensing (RS) images recorded by the Operational Land Imager aboard Landsat-8 to characterize the freshwater detention effect of oyster reef chains across a set of hydrologic conditions. Our results support prior findings indicating that 30-m resolution RS images recorded by the Operational Land Imager aboard Landsat-8 are useful for analyzing coastal dynamics after atmospheric correction, despite having been originally designed for terrestrial studies. Statistical models of water-leaving reflectance revealed that freshwater detention by oyster reefs was evident across the estuary, with the greatest effect occurring in the region closest to shore. Additionally, statistical modeling results and spatial patterns apparent in the satellite images suggested that reef-driven freshwater detention occurred under high riverine discharge conditions, but was less evident when flow was low. Beyond offering insight on the potential role of oyster reefs as mediators of estuarine hydrology, this study presents a transferable methodological framework for exploring estuarine biophysical feedbacks in blackwater river estuaries using satellite remote sensing

Simulating Mechanisms for Dispersal, Production and Stranding of Small Forage Fish in Temporary Wetland Habitats

Movement strategies of small forage fish (\u3c8 cm total length) between temporary and permanent wetland habitats affect their overall population growth and biomass concentrations, i.e., availability to predators. These fish are often the key energy link between primary producers and top predators, such as wading birds, which require high concentrations of stranded fish in accessible depths. Expansion and contraction of seasonal wetlands induce a sequential alternation between rapid biomass growth and concentration, creating the conditions for local stranding of small fish as they move in response to varying water levels. To better understand how landscape topography, hydrology, and fish behavior interact to create high densities of stranded fish, we first simulated population dynamics of small fish, within a dynamic food web, with different traits for movement strategy and growth rate, across an artificial, spatially explicit, heterogeneous, two-dimensional marsh slough landscape, using hydrologic variability as the driver for movement. Model output showed that fish with the highest tendency to invade newly flooded marsh areas built up the largest populations over long time periods with stable hydrologic patterns. A higher probability to become stranded had negative effects on long-term population size, and offset the contribution of that species to stranded biomass. The model was next applied to the topography of a 10 km × 10 km area of Everglades landscape. The details of the topography were highly important in channeling fish movements and creating spatiotemporal patterns of fish movement and stranding. This output provides data that can be compared in the future with observed locations of fish biomass concentrations, or such surrogates as phosphorus ‘hotspots’ in the marsh

Persistence and diversity of directional landscape connectivity improves biomass pulsing in simulations of expanding and contracting wetlands

In flood-pulsed ecosystems, hydrology and landscape structure mediate transfers of energy up the food chain by expanding and contracting in area, enabling spatial expansion and growth of fish populations during rising water levels, and subsequent concentration during the drying phase. Connectivity of flooded areas is dynamic as waters rise and fall, and is largely determined by landscape geomorphology and anisotropy. We developed a methodology for simulating fish dispersal and concentration on spatially-explicit, dynamic floodplain wetlands with pulsed food web dynamics, to evaluate how changes in connectivity through time contribute to the concentration of fish biomass that is essential for higher trophic levels. The model also tracks a connectivity index (DCI) over different compass directions to see if fish biomass dynamics can be related in a simple way to topographic pattern. We demonstrate the model for a seasonally flood-pulsed, oligotrophic system, the Everglades, where flow regimes have been greatly altered. Three dispersing populations of functional fish groups were simulated with empirically-based dispersal rules on two landscapes, and two twelve-year time series of managed water levels for those areas were applied. The topographies of the simulations represented intact and degraded ridge-and-slough landscapes (RSL). Simulation results showed large pulses of biomass concentration forming during the onset of the drying phase, when water levels were falling and fish began to converge into the sloughs. As water levels fell below the ridges, DCI declined over different directions, closing down dispersal lanes, and fish density spiked. Persistence of intermediate levels of connectivity on the intact RSL enabled persistent concentration events throughout the drying phase. The intact landscape also buffered effects of wet season population growth. Water level reversals on both landscapes negatively affected fish densities by depleting fish populations without allowing enough time for them to regenerate. Testable, spatiotemporal predictions of the timing, location, duration, and magnitude of fish concentration pulses were produced by the model, and can be applied to restoration planning

Quantifying uncertainty in coastal salinity regime for biological application using quantile regression

Abstract Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at time scales relevant to ecology (e.g., daily, monthly, and seasonally). Here, we propose a framework for modeling coastal salinity with these overall goals: (1) quantify uncertainty in salinity associated with important terrestrial and oceanographic drivers, (2) examine time scales of salinity response to river streamflow events, and (3) predict salinity continuously over space at key time scales. Salinity is modeled as quantile surfaces related to river discharge, tidal dynamics, wind, and spatial location, applied to Suwannee Sound estuary, FL, USA, where salinity has been monitored spatially since 1981. Each quantile level is regressed independently, and together they comprise a distribution of salinity uncertainty across space, with upper and lower quantiles describing salinity extremes. Effects of physical drivers on salinity are compared through four base models with various combinations of tide and wind variables, each including spatial coordinates and a single streamflow metric (in cubic meters per second). Multiple time scales of streamflow are considered by taking means across various periods, from 1 to 12 days, and at various lagged intervals prior to salinity sample, totaling 144 streamflow metrics. We found that the Suwannee coastal salinity regime is dynamic at multiple time scales and varies nonlinearly across space from the river effluence outward. Salinity increases nonlinearly with decreasing river flow rates below 200 m3/s, most prominently in the lower quantiles of salinity (τ = 0.05–0.25). Wind appears to have a stronger influence on salinity than astronomic tides for this estuary. The regression approach developed here can be applied to any coastal system that has sufficient spatial and temporal monitoring coverage to capture multiple flood and drought events. It is implemented with a simple R routine, and is less computationally‐intensive than finite difference hydrodynamic modeling. The characterizations of salinity uncertainty developed in these analyses can be directly applied to future studies of fish and wildlife responses to changes in watershed management

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to the risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application of risk management theory to conservation emphasizes the diversification of a portfolio of assets, with the goal of reducing the impact of system volatility on investment return.We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate-driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio trade-offs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea-level rise projections, conversion of habitat to open water (14–180%) and wetland loss (1–7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to the risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application of risk management theory to conservation emphasizes the diversification of a portfolio of assets, with the goal of reducing the impact of system volatility on investment return.We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate-driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio trade-offs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea-level rise projections, conversion of habitat to open water (14–180%) and wetland loss (1–7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate