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Results for “Ecological Modelling”

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At least 361 records · Page 20Linked to original sources
USGS2011

Increasing accuracy of dispersal kernels in grid-based population models

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels ( σ > 10 cells), the total kernel error was <10 −11 compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10 −11 and invasion time error to <5%.

Ecological Modelling↗
USGS2015

A conceptual model for site-level ecology of the giant gartersnake ( Thamnophis gigas ) in the Sacramento Valley, California

Giant gartersnakes (Thamnophis gigas) comprise a species of semi-aquatic snakes precinctive to marshes in the Central Valley of California (Hansen and Brode, 1980; Rossman and others, 1996). Because more than 90 percent of their historical wetland habitat has been converted to other uses (Frayer and others, 1989; Garone, 2007), giant gartersnakes have been listed as threatened by the State of California (California Department of Fish and Game Commission , 1971) and the United States (U.S. Fish and Wildlife Service, 1993). Giant gartersnakes currently occur in a highly modified landscape, with most extant populations occurring in the rice - growing regions of the Sacramento Valley, especially near areas that historically were tule marsh habitat (Halstead and others, 2010, 2014). In ricelands and managed marshes, many operational decisions likely affect the health and viability of giant gartersnake populations. Land-use decisions, including the management of water, aquatic vegetation, terrestrial vegetation, and co-occurring species, have the potential to affect giant gartersnakes. Little is known, however, about the effects of these types of decisions on the viability of giant gartersnake populations. Bayesian network models are a useful tool to help guide decisions with uncertain outcomes. These models require the articulation of what experts think they know about a system, and facilitate learning about the hypothesized relations (Marcot and others, 2001; Uusitalo , 2007). Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.

California↗
USGS2015

Estimating the short-term recovery potential of little brown bats in the eastern United States in the face of White-nose syndrome

White-nose syndrome (WNS) was first detected in North American bats in New York in 2006. Since that time WNS has spread throughout the northeastern United States, southeastern Canada, and southwest across Pennsylvania and as far west as Missouri. Suspect WNS cases have been identified in Minnesota and Iowa, and the causative agent of WNS ( Pseudogymnoascus destructans ) has recently been detected in Mississippi. The impact of WNS is devastating for little brown bats ( Myotis lucifugus ), causing up to 100% mortality in some overwintering populations, and previous research has forecast the extirpation of the species due to the disease. Recent evidence indicates that remnant populations may persist in areas where WNS is endemic. We developed a spatially explicit model of little brown bat population dynamics to investigate the potential for populations to recover under alternative scenarios. We used these models to investigate how starting population sizes, potential changes in the number of bats overwintering successfully in hibernacula, and potential changes in demographic rates of the population post WNS may influence the ability of the bats to recover to former levels of abundance. We found that populations of the little brown bat and other species that are highly susceptible to WNS are unlikely to return to pre-WNS levels in the near future under any of the scenarios we examined.

Ecological Modelling↗
USGS2025

Foraging of wading birds on a patchy landscape: Simulating effects of social information, interference competition, and patch selection on prey intake and individual distribution

Foragers on patchy landscapes must acquire sufficient resources despite uncertainty in the location and amount of the resources. Optimal Foraging Theory posits that foragers deal with this uncertainty by using strategies that optimize resource intake within foraging periods. For species such as wading birds, this optimization is closely linked to their survival and reproductive success. Understanding the influence of patch selection on individual resource intake and foraging distribution is therefore crucial. In this study, we simulated how resource distribution, interference competition, and social cues—such as aggregation behaviors—influence resource intake and foraging spatial distribution. We employed an individual-based model simulating wading bird foraging behaviors, with 900 individuals simultaneously foraging across a landscape with unknown resource distribution. Birds employed one of three patch-finding strategies: random, cue-searching, or hybrid, which uses both searching strategies. Each bird decided whether to remain in a patch based on a prey density threshold. We compared the daily resource intake and foraging distribution of birds across different modeled patch-finding strategies, resource distribution patterns, and the presence or absence of interference competition. Wading birds exhibiting aggregation behavior displayed increased intake rates when resources were concentrated and interference minimal. Aggregation behavior led to a closer match with the ideal free distribution when the prey density threshold was optimal. These findings provide theoretical support that aggregation behavior is effective in scenarios where resources are concentrated in a few patches, social cues are used by relatively few individuals, and interference competition is limited.

Ecological Modelling↗
USGS2017

Intraspecific variability and reaction norms of forest understory plant species traits

Trait-based models of ecological communities typically assume intraspecific variation in functional traits is not important, though such variation can change species trait rankings along gradients in resources and environmental conditions, and thus influence community structure and function. We examined the degree of intraspecific relative to interspecific variation, and reaction norms of 11 functional traits for 57 forest understory plant species, including: intrinsic water-use efficiency (iWUE), Δ 15 N, 5 leaf traits, 2 stem traits and 2 root traits along gradients in light, nitrogen, moisture and understory cover. Our results indicate that interspecific trait variation exceeded intraspecific variation by at least 50% for most, but not all traits. Intraspecific variation in Δ 15 N, iWUE, leaf nitrogen content and root traits was high (47-70%) compared with most leaf traits and stem traits (13-38%). Δ 15 N varied primarily along gradients in abiotic conditions, while light and understory cover were relatively less important. iWUE was related primarily to light transmission, reflecting increases in photosynthesis relative to stomatal conductance. Leaf traits varied mainly as a function of light availability, with some reaction norms depending on understory cover. Plant height increased with understory cover, while stem specific density was related primarily to light. Resources, environmental conditions and understory cover did not contribute strongly to the observed variation in root traits. Gradients in resources, environmental conditions and competition all appear to control intraspecific variability in most traits to some extent. However, our results suggest that species cross-over (i.e., trait rank reversals) along the gradients measured here are generally not a concern. Intraspecific variability in understory plant species traits can be considerable. However, trait data collected under a narrow range of environmental conditions appears sufficient to establish species rankings and scale between community and ecosystem levels using trait-based models. Investigators may therefore focus on obtaining a sufficient sample size within a single set of conditions rather than characterizing trait variation across entire gradients in order to optimize sampling efforts.

Oregon↗
USGS2021

The Chesapeake Bay program modeling system: Overview and recommendations for future development

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.

Chesapeake Bay estuary and watershed↗
USGS2007

Optimal management of non-Markovian biological populations

Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator-prey system.

Ecological Modelling↗
USGS2018

A spatially discrete, integral projection model and its application to invasive carp

Natural resource managers and ecologists often desire an understanding of spatial dynamics such as migration, dispersion, and meta-population dynamics. Network-node models can capture these salient features. Additionally, the state-variable used with many species may be appropriately modeled as a continuous variable (e.g., length) and management activities sometimes can only target individuals of certain sizes. Integral projection models (IPMs) can capture this life history characteristic and allow for the examination of size-specific management. We combined an IPM with a network-node model to capture both of these salient features. We then demonstrated how this model could be used to understand and manage populations of invasive species focusing on grass carp as an example. Grass carp disrupt ecosystems outside of their native range and have spread around much of the world, including North America. The impacts of grass carp include adversely changing aquatic plant communities, which in turn affect a wide range of endpoints ranging from water quality to waterfowl recruitment. We specifically examined two theoretical systems using parameters from the literature. First, we modeled a lake with two tributaries and examined how modified sterile males could be used as a control tool. We found that modified sterile males may be a feasible control tool to limit population growth. Second, we modeled a series of river pools and examined how harvest and deterrents could be used to decrease the risk of expanding grass carp's range within a river system. Within this system, we also compared the impacts of size specific harvest and uniform harvest across all sizes. We found that targeting the largest, spawning populations may be more important than targeting the populations close to the invasion front for reducing the risk of spreading grass carp. We also demonstrate that size of harvested fish was important for controlling populations.

Ecological Modelling↗
USGS2022

Integrating monitoring and optimization modeling to inform flow decisions for Chinook salmon smolts

Monitoring is usually among the first actions taken to help inform recovery planning for declining species, but these data are rarely used formally to inform conservation decision making. For example, Central Valley Chinook salmon were once abundant, but anthropogenic activities have led to widespread habitat loss and degradation resulting in significant population declines. Monitoring data suggest survival through the southern Sacramento-San Joaquin River Delta, in particular, may be a limiting factor for juvenile Chinook salmon outmigrating from the San Joaquin River and its tributaries. However, survival and routing monitoring data have not been formally used to inform water management in a decision analytic framework. Here, we illustrate how estimates derived from disjunct monitoring data can be used to inform water management and as a basis for adaptively managing flows. We aggregated a meta-analysis of Chinook salmon smolt survival and routing estimates through the south Delta with other sources of data to develop a survival and routing simulation model to estimate optimal flows for the San Joaquin River during smolt outmigration from February–May. We found that large flow pulses at predictable times during the spring are projected to be optimal for increasing Chinook salmon smolt survival to the San Francisco Bay and that optimal scenarios differed somewhat with water year type. Sensitivity analysis revealed temperature and smolt outmigration timing are driving optimal pulse distribution and that water allocation changes little with parameter uncertainty. This case study highlights the utility of the decision-analytic framework for solving conservation problems.

California↗
USGS2018

Using reverse-time egg transport analysis for predicting Asian Carp spawning grounds in the Illinois River

Identifying spawning grounds of Asian carp is important for determining the reproductive front of invasive populations. Ichthyoplankton monitoring along the Illinois Waterway (IWW) has provided information on abundances of Asian carp eggs in the IWW's navigation pools. Post-fertilization times derived from egg development stages and water temperatures can be used to estimate spawning times of Asian carp eggs, but estimating how far these eggs have drifted requires information on river hydraulics. A Fluvial Egg Drift Simulator (FluEgg) program was designed to predict the drift of Asian carp eggs in the riverine environment with egg growth considered. This paper presents a reverse-time particle tracking (RTPT) algorithm for back-casting the spawning location of eggs from their collection site. The RTPT algorithm was implemented as a module in FluEgg. The new version of FluEgg was coupled with an unsteady hydrodynamic model of the IWW to predict the spawning locations for 530 eggs that were collected in June 2015. The results indicate that tailwater sections below the Locks and Dams (L&Ds) in each navigation pool appear to be preferred spawning locations for Silver Carp. From the data analyzed, the most upstream spawning location for the June 2015 spawning period was in the upper Marseilles navigation pool, downstream of the Dresden Island L&D. The RTPT algorithm can efficiently estimate spawning locations for multiple egg samples.

Illinois↗
USGS2005

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan, Canada

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.

Ecological Modelling↗
USGS2005

Transient population dynamics: Relations to life history and initial population state

Most environments are variable and disturbances (e.g., hurricanes, fires) can lead to substantial changes in a population's state (i.e., age, stage, or size distribution). In these situations, the long-term (i.e., asymptotic) measure of population growth rate (??1) may inaccurately represent population growth in the short-term. Thus, we calculated the short-term (i.e., transient) population growth rate and its sensitivity to changes in the life-cycle parameters for three bird and three mammal species with widely varying life histories. Further, we performed these calculations for initial population states that spanned the entire range of possibilities. Variation in a population's initial net reproductive value largely explained the variation in transient growth rates and their sensitivities to changes in life-cycle parameters (all AICc ??? 6.67 units better than the null model, all R2 ??? 0.55). Additionally, the transient fertility and adult survival sensitivities tended to increase with the initial net reproductive value of the population, whereas the sub-adult survival sensitivity decreased. Transient population dynamics of long-lived, slow reproducing species were more variable and more different than asymptotic dynamics than they were for short-lived, fast reproducing species. Because ??1 can be a biased estimate of the actual growth rate in the short-term (e.g., 19% difference), conservation and wildlife biologists should consider transient dynamics when developing management plans that could affect a population's state, or whenever population state could be unstable.

Ecological Modelling↗
USGS2015

Accuracy or precision: Implications of sample design and methodology on abundance estimation

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N -mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Ecological Modelling↗
USGS2023

Less is more: Less herbicide does more when biological control is present in Pontederia crassipes

An experiment along with simulation modeling was applied to study the combinations of herbicide treatment and biological control that best limit invasive water hyacinth ( Pontederia crassipes , formerly Eichhornia crassipes ) in freshwater aquatic systems. The experiment consisted of 14 different treatments of P. crassipes in 1.67 m 2 outdoor tank mesocosms. Seven treatments were with and seven were without insect biological control agents, Neochetina eichhorniae . In both of the sets of seven treatments, there was one no-herbicide treatment, a one-time full-strength herbicide treatment with 40 %, 80 % and 100 % coverage of the P. crassipes , and a one-time half-strength herbicide treatment with 40 %, 80 %, and 100 % surface area coverage. An overarching hypothesis was that leaving part of a tank unsprayed, providing habitat for the maintenance of biological control agents, would optimize control. Data from the experiment, measured on five days over the 167-day period, were used to calibrate a difference equation model of P. crassipes with and without the biological control agent. The model was then used to project longer term dynamics of the system. The model predicted that an initial one-time herbicide treatment, combined with application of the biocontrol agent at 80 % areal coverage, could maintain P. crassipes at levels lower than the carrying capacity of the plant's biomass over the long term, though not enough that N. eichhorniae would be considered, by itself, a highly effective control. However, the results suggest that a combination of biocontrol with 80 % spraying coverage every 600 days or so would be an effective integrated biocontrol strategy for maintaining decreased P. crassipes biomass at low levels over the long term.

Ecological Modelling↗
USGS2006

Planning for robust reserve networks using uncertainty analysis

Planning land-use for biodiversity conservation frequently involves computer-assisted reserve selection algorithms. Typically such algorithms operate on matrices of species presence?absence in sites, or on species-specific distributions of model predicted probabilities of occurrence in grid cells. There are practically always errors in input data?erroneous species presence?absence data, structural and parametric uncertainty in predictive habitat models, and lack of correspondence between temporal presence and long-run persistence. Despite these uncertainties, typical reserve selection methods proceed as if there is no uncertainty in the data or models. Having two conservation options of apparently equal biological value, one would prefer the option whose value is relatively insensitive to errors in planning inputs. In this work we show how uncertainty analysis for reserve planning can be implemented within a framework of information-gap decision theory, generating reserve designs that are robust to uncertainty. Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection. Search for robust-optimal reserve structures can still be implemented via typical reserve selection optimization techniques, including stepwise heuristics, integer-programming and stochastic global search.

Ecological Modelling↗
USGS1999

Modeling bird mortality associated with the M/V Citrus oil spill off St. Paul Island, Alaska

We developed a model to estimate the number of bird carcasses that were likely deposited on the beaches of St. Paul Island, Alaska following the M/V Citrus oil spill in February 1996. Most of the islands beaches were searched on an irregular schedule, resulting in the recovery of 876 King Eider carcasses. A sub-sample of beaches were intensively studied to estimate daily persistence rate and detection probability [Fowler, A.C., Flint, P.L., 1997. Marine Pollution Bulletin]. Using these data, our model predicted that an additional 733±70 King Eider carcasses were not detected during our searches. Therefore, we estimate that at least 1609±70 King Eider carcasses occurred on beaches as a result of the spill. We lacked sufficient sample size to model losses for other species, thus we applied the estimated recovery rate for King Eiders (54%) to other species and estimate a total combined loss of 1765 birds. In addition, 165 birds were captured alive making the total estimated number of birds impacted by the M/V Citrus spill 1930. Given that oiled birds occurred in places on the island which could not be systematically searched combined with the fact that it was unlikely that oiled birds that died at sea would have been recovered during our searches [Flint, P.L., Fowler, A.C., 1998. Marine Pollution Bulletin], our estimate of total mortality associated with the spill should be considered a minimum.

Alaska↗
USGS1997

Adaptation of a stage-projection model for species with multiple year reproductive cycles

We apply stage projection matrices to multiple age and reproductive categories, deriving the stable age - reproductive category distribution for populations with multi-year reproductive cycles and identifying conditions for the existence of a dominant latent root. Given the stable distribution of age and reproductive category and the number of female young for each reproductive category, the age specific fecundity rates can be calculated. For species with multi-year reproductive cycles, the fecundity rate associated with the stable age distribution is often not a smooth function of age, but fluctuates as a larger or smaller fraction of females becomes available to breed. We suggest that fecundity rates for species with multi-year reproductive cycles be defined in terms of litter size and probabilities of conception and successful gestation rather than average fecundity.

Ecological Modelling↗
USGS2017

An integral projection model with YY-males and application to evaluating grass carp control

Invasive fish species disrupt ecosystems and cause economic damage. Several methods have been discussed to control populations of invasive fish including the release of YY-males. YY-males are fish that have 2 male chromosomes compared to a XY-male. When YY-males mate, they only produce male (XY) offspring. This decreases the female proportion of the population and can, in theory, eradicate local populations by biasing the sex-ratio. YY-males have been used as a population control tool for brook trout in montane streams and lakes in Idaho, USA. The YY-male control method has been discussed for grass carp in Lake Erie, North America. We developed and presented an integral projection model for grass carp to model the use of YY-males as a control method for populations in this lake. Using only the YY-male control method, we found that high levels of YY-males would need to be release annually to control the species. Specifically, these levels were the same order of magnitude as the baseline adult population (e.g., 1000 YY-males needed to be released annual for 20 years to control a baseline adult population of 2500 grass carp). These levels may not be reasonable or obtainable for fisheries managers given the impacts of YY-males on aquatic vegetation and other constraints of natural resource management.

Ecological Modelling↗