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Results for “Ecological Modelling”

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At least 379 records · Page 21Linked to original sources
USGS2010

Hydraulic modeling of mussel habitat at a bridge-replacement site, Allegheny River, Pennsylvania, USA

The Allegheny River in Pennsylvania supports a large and diverse freshwater-mussel community, including two federally listed endangered species, Pleurobema clava (Clubshell) and Epioblasma torulosa rangiana (Northern Riffleshell). It is recognized that river hydraulics and morphology play important roles in mussel distribution. To assess the hydraulic influences of bridge replacement on mussel habitat, metrics such as depth, velocity, and their derivatives (shear stress, Froude number) were collected or computed. The objectives of the project were to evaluate mussel and hydraulic data at a reference site and to compare those findings to a bridge-replacement site. The findings were used to support a statistical analysis, which establishes correlations between mussel count and hydraulics, and a numerical model to forecast habitat based on the statistics. ArcGIS was selected to manage the data and generate a grid to compute area statistics for 3319, 4.9-m × 4.9-m cells (cell) for total mussel count, depth, velocity, shear stress, and Froude number. The Wilcoxon Rank Sum test indicated no statistical significance between the total mussel count and the hydraulic variables; however, trellis graphs were used to account for the spatial variability in the data set. For the flow conditions measured, the total mussel count per cell is greatest at sections where (1) velocities range from 0.061 to 0.21 m/s, (2) shear stresses range from 0.48 to 3.8 dyne/cm 2 , and (3) Froude numbers range from 0.006 to 0.04. Based on the statistical targets established, the hydraulic model results suggest that an additional 2428 m 2 or a 30-percent increase in suitable mussel habitat could be generated at the replacement-bridge site when compared to the baseline condition associated with the existing bridge at that same location. The study did not address the influences of substrate, acid mine drainage, sediment loads from tributaries, and surface-water/ground-water exchange on mussel habitat. Future studies could include methods for quantifying (1) channel–substrate composition and distribution using tools such as hydroacoustic echosounders specifically designed and calibrated to identify bed composition and mussel populations, (2) surface-water and ground-water interactions, and (3) a high-streamflow event.

Pennsylvania↗
USGS2019

Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification

Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca ( Melaleuca quinquenervia ) and Old World climbing fern ( Lygodium microphyllum ), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).

Ecological Modelling↗
USGS2021

Modeling opportunistic exploitation: Increased extinction risk when targeting more than one species

Extinction rates are increasing globally, and direct exploitation is an important driver. Many pathways have been proposed to explain how exploitation can lead to extinction. One of these proposed but understudied multispecies pathways is opportunistic exploitation, which occurs when a highly valuable but rare species is encountered and targeted during exploitation of a less valuable, but more common, target species. Using individual-based simulations of exploiters in a two-species spatial model, we contribute evidence which supports that opportunistic exploitation increases depletion when compared to single-species exploitation, and is as detrimental to the more valuable, rare species as the anthropogenic Allee effect (where price increases with rarity) and the Allee effect (where population growth declines at low abundance). The most important factors affecting the impact of opportunistic exploitation are gross revenue and abundance of the more common, less valuable species, while ease of capture and growth rate of the more common, less valuable species are less important. Thus, valuable but rare species are most at risk when harvested alongside low-value abundant species; this information is relevant for managers focused on protection of rare species in multispecies systems.

Ecological Modelling↗
USGS2015

Proposed best modeling practices for assessing the effects of ecosystem restoration on fish

Large-scale aquatic ecosystem restoration is increasing and is often controversial because of the economic costs involved, with the focus of the controversies gravitating to the modeling of fish responses. We present a scheme for best practices in selecting, implementing, interpreting, and reporting of fish modeling designed to assess the effects of restoration actions on fish populations and aquatic food webs. Previous best practice schemes that tended to be more general are summarized, and they form the foundation for our scheme that is specifically tailored for fish and restoration. We then present a 31-step scheme, with supporting text and narrative for each step, which goes from understanding how the results will be used through post-auditing to ensure the approach is used effectively in subsequent applications. We also describe 13 concepts that need to be considered in parallel to these best practice steps. Examples of these concepts include: life cycles and strategies; variability and uncertainty; nonequilibrium theory; biological, temporal, and spatial scaling; explicit versus implicit representation of processes; and model validation. These concepts are often not considered or not explicitly stated and casual treatment of them leads to mis-communication and mis-understandings, which in turn, often underlie the resulting controversies. We illustrate a subset of these steps, and their associated concepts, using the three case studies of Glen Canyon Dam on the Colorado River, the wetlands of coastal Louisiana, and the Everglades. Use of our proposed scheme will require investment of additional time and effort (and dollars) to be done effectively. We argue that such an investment is well worth it and will more than pay back in the long run in effective and efficient restoration actions and likely avoided controversies and legal proceedings.

Ecological Modelling↗
USGS2003

Modeling white sturgeon movement in a reservoir: The effect of water quality and sturgeon density

We developed a movement model to examine the distribution and survival of white sturgeon (Acipenser transmontanus) in a reservoir subject to large spatial and temporal variation in dissolved oxygen and temperature. Temperature and dissolved oxygen were simulated by a CE-QUAL-W2 model of Brownlee Reservoir, Idaho for a typical wet, normal, and dry hydrologic year. We compared current water quality conditions to scenarios with reduced nutrient inputs to the reservoir. White sturgeon habitat quality was modeled as a function of temperature, dissolved oxygen and, in some cases, suitability for foraging and depth. We assigned a quality index to each cell along the bottom of the reservoir. The model simulated two aspects of daily movement. Advective movement simulated the tendency for animals to move toward areas with high habitat quality, and diffusion simulated density dependent movement away from areas with high sturgeon density in areas with non-lethal habitat conditions. Mortality resulted when sturgeon were unable to leave areas with lethal temperature or dissolved oxygen conditions. Water quality was highest in winter and early spring and lowest in mid to late summer. Limiting nutrient inputs reduced the area of Brownlee Reservoir with lethal conditions for sturgeon and raised the average habitat suitability throughout the reservoir. Without movement, simulated white sturgeon survival ranged between 45 and 89%. Allowing movement raised the predicted survival of sturgeon under all conditions to above 90% as sturgeon avoided areas with low habitat quality. ?? 2003 Elsevier B.V. All rights reserved.

Ecological Modelling↗
USGS2002

Carbon isotope composition of ambient CO 2 and recycling: a matrix simulation model

The relationship between isotopic composition and concentration of ambient CO 2 in a canopy and its associated convective boundary layer was modeled. The model divides the canopy and convective boundary layer into several layers. Photosynthesis, respiration, and exchange between each layer can be simulated by matrix equations. This simulation can be used to calculate recycling; defined here as the amount of respired CO 2 re-fixed by photosynthesis relative to the total amount of respired CO 2 . At steady state the matrix equations can be solved for the canopy and convective boundary layer CO 2 concentration and isotopic profile, which can be used to calculate a theoretical recycling index according to a previously developed equation. There is complete agreement between simulated and theoretical recycling indices for different exchange scenarios. Recycling indices from a simulation of gas exchange between a heterogeneous vegetation canopy and the troposphere also agreed with a more generalized form of the theoretical recycling equation developed here.

Ecological Modelling↗
USGS2010

Fish population dynamics in a seasonally varying wetland

Small fishes in seasonally flooded environments such as the Everglades are capable of spreading into newly flooded areas and building up substantial biomass. Passive drift cannot account for the rapidity of observed population expansions. To test the reaction-diffusion mechanism for spread of the fish, we estimated their diffusion coefficient and applied a reaction-diffusion model. This mechanism was also too weak to account for the spatial dynamics. Two other hypotheses were tested through modeling. The first--the 'refuge mechanism--hypothesizes that small remnant populations of small fishes survive the dry season in small permanent bodies of water (refugia), sites where the water level is otherwise below the surface. The second mechanism, which we call the 'dynamic ideal free distribution mechanism' is that consumption by the fish creates a prey density gradient and that fish taxis along this gradient can lead to rapid population expansion in space. We examined the two alternatives and concluded that although refugia may play an important role in recolonization by the fish population during reflooding, only the second, taxis in the direction of the flooding front, seems capable of matching empirical observations. This study has important implications for management of wetlands, as fish biomass is an essential support of higher trophic levels.

Florida↗
USGS2022

Modeling the impact of invasive species litter on conditions affecting its spread and potential regime shift

Many introduced plants pose invasion risks globally and threaten the biodiversity of native ecosystems. Such non-native plants can become invasive when they have advantages over native plants, such as having fewer natural enemies. Invasive plants often have the ability to alter ecosystem properties after they have become established, which can make it difficult to eliminate the invasive. In principle, this can cause a regime shift that may not be reversed through intense control efforts that increase mortality and reduce growth of the invasive species. Here we use spatially explicit agent-based modeling to simulate the invasion of an introduced tree species into a habitat occupied by a native species. The model describes an invasive tree with fast growth and high seed production and, in addition, produces litter that has a suppressive effect on native seedlings. These are properties, for example, shared by the invasive Melaleuca quinquenervia in southern Florida habitats. We use simulation modeling to test the following logical hypotheses: Partial suppression of native tree seedlings by the invasive tree's litter (1) will accelerate the spread of the invasive tree into native vegetation, (2) will impede efforts to control invasive spread through biocontrol, and (3) can cause a regime shift that is not reversed even if the biocontrol lowers invasive growth and reproduction to levels substantially lower than those of the native species. Additionally, (4) the earlier in the invasion biocontrol is introduced, the more effective it will be in reversing the invasion. The simulations support all four hypotheses. While these results highlight the potential for biocontrol of invasive tree species, our findings also suggest that successful elimination of positive litter feedbacks and invasive spread may critically depend on the timing of control efforts within the invasion process.

Ecological Modelling↗
USGS2001

Applying linear programming to estimate fluxes in ecosystems or food webs: An example from the herpetological assemblage of the freshwater Everglades

We present the application of Linear Programming for estimating biomass fluxes in ecosystem and food web models. We use the herpetological assemblage of the Everglades as an example. We developed food web structures for three common Everglades freshwater habitat types: marsh, prairie, and upland. We obtained a first estimate of the fluxes using field data, literature estimates, and professional judgment. Linear programming was used to obtain a consistent and better estimate of the set of fluxes, while maintaining mass balance and minimizing deviations from point estimates. The results support the view that the Everglades is a spatially heterogeneous system, with changing patterns of energy flux, species composition, and biomasses across the habitat types. We show that a food web/ecosystem perspective, combined with Linear Programming, is a robust method for describing food webs and ecosystems that requires minimal data, produces useful post-solution analyses, and generates hypotheses regarding the structure of energy flow in the system.

Ecological Modelling↗
USGS2011

Evaluating the effects of future climate change and elevated CO 2 on the water use efficiency in terrestrial ecosystems of China

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO 2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO 2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO 2 concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO 2 concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.

Ecological Modelling↗
USGS2018

Quantifying population-level effects of water temperature, flow velocity and chemical-induced reproduction depression: A simulation study with smallmouth bass

Evaluating stochastic abiotic factors and their combined effects on fish and wildlife populations have been challenging in environmental sciences. Contributing to this challenge is the paucity of data describing how observations made on individuals related to exposure to chemical compounds ultimately effect population vital rates, and how this exposure interacts with other abiotic drivers. Using three smallmouth bass populations in Pennsylvania as a case study, we explored both single-factor and combined effects of water temperature, flow velocity and chemical exposure on populations through a model simulation. Although there are many pathways through which chemicals can affect population vital rates, we focused on one where chemical exposure leads to reduced reproduction. Among the three populations considered, two (the Juniata and Susquehanna populations) have experienced adverse health, including the potential adverse effects of environmental stress and chemical contamination that may cause disease and mortality of young-of-year (YOY), various skin lesions and a high prevalence of intersex or testicular oocytes in adults. The third population (The Alleghany population) has not encountered mortality events of YOY and intersex prevalence is much lower. The simulation involved projecting populations using a length-based model under different environmental conditions. In the simulations, abiotic factors influenced population dynamics through their impacts on growth, survival and recruitment. Response to the same environmental stress varied by population and life-stage of the species. Factors affecting young adult and adult life-stages had great influence on proportional stock density (PSD) and the probability of having PSD within the suggested range (PSD probability). Increases in water temperature had a negative effect and dominant role in the combined effect on population size structure (e.g., PSD and PSD probability) – increases in flow velocity during the spring season also had a negative effect on abundance. Populations with high recruitment rates sustained relatively large population size, even under high water temperature and/or high flow velocity, which suggests that factors and management strategies that benefit recruitment (such as reduced chemical contaminants) may compensate for the negative effects of warming water temperatures and high spring flow velocity on population size.

Ecological Modelling↗
USGS2025

Sediment transport modeling in Lake Ontario embayments: Impacts on fish spawning substrates

Anthropogenically-driven sedimentation changes have had adverse environmental impacts on aquatic environments, including reductions in fish spawning habitats in embayments worldwide. This study was motivated by the need to understand the impacts of waves and current-driven sedimentation patterns on traditional spawning areas and their effect on sustainable fish reproduction in the Great Lakes. Coupled hydrodynamic, wave, and sediment transport models were developed within the Delft3D-SWAN (DS) framework to predict sedimentation patterns in two embayments in Lake Ontario, Sodus Bay and Chaumont Bay, that have been historically important fish spawning habitats. These bays, with distinct geomorphic characteristics and connectivity to Lake Ontario, offer an opportunity to examine how wind-generated waves and currents impact bed shear stress and subsequent sedimentation patterns. Areas experiencing greater wave-induced bed shear stress were identified and compared between the two bays. Simulated sediment transport patterns showed notable erosion near the lake-bay connections and increased deposition in the inner areas of both embayments. Observed Cisco embryo deposition corresponded to regions of high sheer stress and lower sedimentation, indicating physical attributes in those areas that are important for embryo survival. These results show where sediment settling and erosion occur in the two bays and highlight potential impacts on traditional spawning areas.

New York↗
USGS2017

Predicting the impacts of Mississippi River diversions and sea-level rise on spatial patterns of eastern oyster growth rate and production

There remains much debate regarding the perceived tradeoffs of using freshwater and sediment diversions for coastal restoration in terms of balancing the need for wetland restoration versus preserving eastern oyster ( Crassostrea virginica ) production. Further complicating the issue, climate change-induced sea-level rise (SLR) and land subsidence are also expected to affect estuarine water quality. In this study, we developed a process-based numerical modeling system that couples hydrodynamic, water quality, and oyster population dynamics. We selected Breton Sound Estuary (BSE) (∼2740 km 2 ) in the eastern Mississippi River Deltaic Plain since it is home to several of the largest public oyster seed grounds and private leases for the Gulf coast. The coupled oyster population model was calibrated and validated against field observed oyster growth data. We predicted the responses of oyster population in BSE to small- (142 m 3 s −1 ) and large-scale (7080 m 3 s −1 ) river diversions at the Caernarvon Freshwater Diversion structure planned in the 2012 Coastal Master Plan (Louisiana) under low (0.38 m) and high (1.44 m) relative sea-level rise (RSLR = eustatic SLR + subsidence) compared to a baseline condition (Year 2009). Model results showed that the large-scale diversion had a stronger negative impact on oyster population dynamics via freshening of the entire estuary, resulting in reduced oyster growth rate and production than RSLR. Under the large-scale diversion, areas with optimal oyster growth rates (>15 mg ash-free dry weight (AFDW) oyster −1 wk −1 ) and production (>500 g AFDW m −2 yr −1 ) would shift seaward to the southeastern edge of the estuary, turning the estuary into a very low oyster production system. RSLR however played a greater role than the small-scale diversion on the magnitude and spatial pattern of oyster growth rate and production. RSLR would result in an overall estuary-wide decrease in oyster growth rate and production as a consequence of decreased salinities in the middle and lower estuary because rising sea level likely causes increased stage and overbank flow downstream along the lower Mississippi River.

Louisiana↗
USGS2021

Modeling watershed carbon dynamics as affected by land cover change and soil erosion

Process-based ecosystem carbon cycle models typically incorporate vegetation growth, vegetation mortality, and soil respiration as well as the biotic and environmental drivers that influence these variables. However, few spatially explicit process models can efficiently incorporate the influence of land cover change and carbon lateral movement at regional scales or high spatial resolution. This study uses the Land Use and Carbon Scenario Simulator (LUCAS) to demonstrate the development of a fast ecosystem model that not only considers the basic carbon cycle but also incorporates the impact of land cover change, soil erosion, and soil deposition. As input to the LUCAS modeling framework, we used the integrated biosphere simulator (IBIS) to simulate a non-spatial reference carbon cycling scenario without considering land cover change for the Nisqually River watershed in the northwestern United States. We then used the Land Change Monitoring, Assessment, and Projection (LCMAP) remotely sensed 30-m sequential land cover data to generate annual land change history for the Nisqually River area from 1985 to 2017 and used the Unit Stream Powered Erosion and Deposition model (USPED) to estimate annual soil carbon lateral movement. Finally, we combined the annual carbon outputs from IBIS, the land change history from LCMAP, and the soil erosion and deposition from USPED within the LUCAS simulation framework. Results showed that from 1985 to 2017, along with the dynamic land cover changes, total ecosystem biomass carbon increased from 11.4 to 18.6 TgC, mainly due to forest growth. Total ecosystem soil carbon declined from 31.7 to 29.7 TgC, but the overall loss in soil carbon was not uniform across land cover types. Forestland (forest sector) and grassland lost carbon, while wetland, developed land and agricultural land gained carbon. Forest, grassland, and developed land lost 0.0553 TgC during the study period (1.73 Gg of C per year; 1 Gg = 0.001 Tg) from erosion, while wetland gained 0.0071 TgC (0.22 Gg C per year) from deposition. Agricultural land was neutral in terms of soil erosion.

Washington↗
USGS2010

Nutrient fluxes at the landscape level and the R* rule

Nutrient cycling in terrestrial ecosystems involves not only the vertical recycling of nutrients at specific locations in space, but also biologically driven horizontal fluxes between different areas of the landscape. This latter process can result in net accumulation of nutrients in some places and net losses in others. We examined the effects of such nutrient-concentrating fluxes on the R * rule, which predicts that the species that can survive in steady state at the lowest level of limiting resource, R *, can exclude all competing species. To study the R * rule in this context, we used a literature model of plant growth and nutrient cycling in which both nutrients and light may limit growth, with plants allocating carbon and nutrients between foliage and roots according to different strategies. We incorporated the assumption that biological processes may concentrate nutrients in some parts of the landscape. We assumed further that these processes draw nutrients from outside the zone of local recycling at a rate proportional to the local biomass density. Analysis showed that at sites where there is a sufficient biomass-dependent accumulation of nutrients, the plant species with the highest biomass production rates (roughly corresponding to the best competitors) do not reduce locally available nutrients to a minimum concentration level (that is, minimum R *), as expected from the R * rule, but instead maximize local nutrient concentration. These new results require broadening of our understanding of the relationships between nutrients and vegetation competition on the landscape level. The R * rule is replaced by a more complex criterion that varies across a landscape and reduces to the R * rule only under certain limiting conditions.

Ecological Modelling↗
USGS2017

Meteorological drivers of hypolimnetic anoxia in a eutrophic, north temperate lake

Oxygen concentration is both an indicator and driver of water quality in lakes. Decreases in oxygen concentration leads to altered ecosystem function as well as harmful consequences for aquatic biota, such as fishes. The responses of oxygen dynamics in lakes to climate-related drivers, such as temperature and wind speed, are well documented for lake surface waters. However, much less is known about how the oxic environment of bottom waters, especially the timing and magnitude of anoxia in eutrophic lakes, responds to changes in climate drivers. Understanding how important ecosystem states, such as hypolimnetic anoxia, may respond to differing climate scenarios requires a model that couples physical-biological conditions and sufficiently captures the density stratification that leads to strong oxygen gradients. Here, we analyzed the effects of changes in three important meteorological drivers (air temperature, wind speed, and relative humidity) on hypolimnetic anoxia in a eutrophic, north temperate lake using the anoxic factor as an index that captures both the temporal and spatial extent of anoxia. Air temperature and relative humidity were found to have a positive correlation with anoxic factor, while wind speed had a negative correlation. Air temperature was found to have the greatest potential impact of the three drivers on the anoxic factor, followed by wind speed and then relative humidity. Across the scenarios of climate variability, variation in the simulated anoxic factor was primarily due to changes in the timing of onset and decay of stratification. Given the potential for future changes in climate, especially increases in air temperature, this study provides important insight into how these changes will alter lake water quality.

Ecological Modelling↗
USGS2021

Modeling structural mechanics of oyster reef self-organization including environmental constraints and community interactions

Self-organization is a process of establishing and reinforcing local structures through feedbacks between internal population dynamics and external factors. In reef-building systems, substrate is collectively engineered by individuals that also occupy it and compete for space. Reefs are constrained spatially by the physical environment, and by mortality, which reduces production but exposes substrate for recruits. Reef self-organization therefore depends on efficient balancing of production and occupancy of substrate. To examine this, we develop a three-dimensional individual-based model (IBM) of oyster reef mechanics. Shell substrate is grown by individuals as valves, accumulates at the reef level, and degrades following mortality. Single restoration events and subsequent dynamics are simulated for a case study in South Carolina (USA). Variability in model processes is included on recruitment, spatial environmental constraints, and predation, over multiple independent runs and five predator community scenarios. The main goal for this study is to summarize trends in dynamics that are robust across this uncertainty, and from these generate new hypotheses and predictions for future studies. Simulation results demonstrate three phases following restoration: initial transient dynamics with considerable shell loss, followed by growth and saturation of the live population, and then saturation of settlement habitat several years later. Over half of simulations recoup initial shell losses as populations grow, while others continue in decline. The balance between population density, substrate supporting the reef, and exposed surfaces for settlement is mediated by overall population size and size structure, presence of predators, and relative amounts of live individuals and intact dead shells. The efficiency of settlement substrate production improves through time as population size structure becomes more complex, and the population of dead valves accumulates.

Ecological Modelling↗
USGS2010

Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes

Effective conservation of amphibian populations requires the prediction of how amphibians use and move through a landscape. Amphibians are closely coupled to their physical environment. Thus an approach that uses the physiological attributes of amphibians, together with knowledge of their natural history, should be helpful. We used Niche Mapper™ to model the known movements and habitat use patterns of a population of Western toads ( Anaxyrus (= Bufo ) boreas ) occupying forested habitats in southeastern Idaho. Niche Mapper uses first principles of environmental biophysics to combine features of topography, climate, land cover, and animal features to model microclimates and animal physiology and behavior across landscapes. Niche Mapper reproduced core body temperatures ( T c ) and evaporation rates of live toads with average errors of 1.6 ± 0.4 °C and 0.8 ± 0.2 g/h, respectively. For four different habitat types, it reproduced similar mid-summer daily temperature patterns as those measured in the field and calculated evaporation rates (g/h) with an average error rate of 7.2 ± 5.5%. Sensitivity analyses indicate these errors do not significantly affect estimates of food consumption or activity. Using Niche Mapper we predicted the daily habitats used by free-ranging toads; our accuracy for female toads was greater than for male toads (74.2 ± 6.8% and 53.6 ± 15.8%, respectively), reflecting the stronger patterns of habitat selection among females. Using these changing to construct a cost surface, we also reconstructed movement paths that were consistent with field observations. The effect of climate warming on toads depends on the interaction of temperature and atmospheric moisture. If climate change occurs as predicted, results from Niche Mapper suggests that climate warming will increase the physiological cost of landscapes thereby limiting the activity for toads in different habitats.

Idaho↗