Using a fisheries ecosystem model with a water quality model to explore trophic and habitat impacts on a fisheries stock: A case study of the blue crab population in the Chesapeake Bay

Recent calls for the development of ecosystem-based fisheries management compel the development of resource management tools and linkages between existing fisheries management tools and other resource tools to enable assessment and management of multiple impacts on fisheries resources. In this paper, we describe the use of the Chesapeake Bay Fisheries Ecosystem Model (CBFEM), developed using the Ecopath with Ecosim (EwE) software, and the Chesapeake Bay Water Quality Model (WQM) to demonstrate how linkages between available modeling tools can be used to inform ecosystem-based natural resource management. The CBFEM was developed to provide strategic ecosystem information in support of fisheries management. The WQM was developed to assess impacts on water quality. The CBFEM was indirectly coupled with the WQM to assess the effects of water quality and submerged aquatic vegetation (SAV) on blue crabs. The output from two WQM scenarios (1985-1994), a baseline scenario representing actual nutrient inputs and another with reduced inputs based on a tributary management strategy, was incorporated into the CBFEM. The results suggested that blue crab biomass could be enhanced under management strategies (reduced nutrient input) when the effective search rate of blue crab young-of-the-year's (YOY's) predators or the vulnerability of blue crab YOY to its predators was adjusted by SAV. Such model linkages are important for incorporating physical and biological components of ecosystems in order to explore ecosystem-based fisheries management options.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Zooplankton population model coupled to a biogeochemical model of the North Western Mediterranean Sea ecosystem

A stage structured population (SSP) model based on Fennel's [Fennel, W., 2001. Modelling copepods with links to circulation models. Journal of Plankton Research, 23, 1217–1232] equations is applied to Centropages typicus (Kröyer), a dominant copepod species of the North Western Mediterranean Sea (NWMS) and a prey of small pelagic fish. The model considers five groups of stages and development rates are represented by a mechanistic formulation depending on individual specific growth in each stage. Individual growth is calculated from the individual energy budget depending on food availability and temperature.     

Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90–125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12–16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the “escapement” due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management.     

Importance of jumbo squid Dosidicus gigas (Orbigny, 1835) in the pelagic ecosystem of the central Gulf of California

The Humboldt squid is an important predator in the pelagic ecosystem of the central Gulf of California and the commercial catch of this species has increased over the past decade, probable due to a decrease of several top predators (sharks, large pelagic fish and the marine mammals) and the optimal feeding conditions in this area. Its high abundance and important position in the pelagic food web was quantified through two trophic models of the pelagic ecosystem of the central Gulf of California. Models represented conditions in 1980 and 2002, to document the decadal changes in ecosystem structure and function. The models were composed of 18 functional groups, including marine mammals, birds, fish, mollusks, crustaceans, and primary producers. Model results show direct negative effects on principal prey groups such as myctophids and pelagic red crab and positive effects on sharks, marine mammals and specifically sperm whales. It thus appears that the jumbo squid has an important role in the ecosystem and plays a central part in the overall energy flow as main food item for most top predators, and due to its predation of organisms on lower tropic levels.     

Modelling the effects of eutrophication, mitigation measures and an extreme flood event on estuarine benthic food webs

Human-mediated and natural disturbances such as nutrient enrichment, habitat modification, and flood events often result in significant shifts in species composition and abundance that translate into changes in the food web structure. Six mass-balanced models were developed using the “Ecopath with Ecosim” software package to assess changes in benthic food web properties in the Mondego estuarine ecosystem (Portugal). Field, laboratory and literature information were used to construct the models. The main study objective was to assess at 2 sites (a Zostera meadow and a bare sediment area) the effects of: (1) a period of anthropogenic enrichment, which led to excessive production of organic matter in the form of algal blooms (1993/1994); (2) the implementation of mitigation measures, following a long period of eutrophication (1999/2000); and (3) a centenary flood (winter 2000/2001). Different numbers of compartments were identified at each site and in each time period. In general, the Zostera site, due to its complex community, showed a higher number of compartments and a higher level of system activity (i.e. sum of consumptions, respiration, flow to detritus, production, total system throughput, net primary production and system omnivory index). The differences at the two sites in the three time periods in the breakdown of throughput were mainly due to differences in the biomass of the primary producers (higher primary production at the Zostera site). Consumption, respiration and flow to detritus were dominated by the grazers Hydrobia ulvae and Scrobicularia plana at the Zostera and bare sediment sites respectively. At both sites, after recovery measures were implemented there was an increase in S. plana and Hediste diversicolor biomass, consumption, respiration and flows to detritus, and a decrease in H. ulvae biomass and associated flows, which increased again after the flood event. The mass-balanced models showed that the trophic structure of the benthic communities in Mondego estuary was affected differently by each disturbance event. Interestingly, in our study a high system throughput seems to be associated with higher stress levels, which contradicts the idea that higher system activity is always a sign of healthier conditions.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

Modeling the role of macroalgae in a shallow sub-estuary of Narragansett Bay, RI (USA)

Proliferation of macroalgal mats is a frequent consequence of nutrient-driven eutrophication in shallow, photic coastal marine ecosystems. These macroalgae have the potential to significantly modify water quality, plankton productivity, nutrient cycling, and dissolved oxygen dynamics. We developed a model for Ulva lactuca and Gracilaria tikvahiae in Greenwich Bay, RI (USA), a shallow sub-estuary of Narragansett Bay, as part of a larger estuarine ecosystem model. The model predicts the biomass of both species in units of carbon, nitrogen, and phosphorus as a function of primary production, respiration, grazing, decay, and physical exchange, with particular attention to the effects of biomass layering on light attenuation and suppression of metabolic rates. The model successfully reproduced the magnitude and seasonal cycle of area-weighted and peak biomass in Greenwich Bay along with tissue C:N ratios, and highlighted the importance of grazing and inclusion of self-limitation primarily in the form of self-shading to overcome an order of magnitude difference in rates of production and respiration. Inclusion of luxury nutrient uptake demonstrated the importance of internal nutrient storage in fueling production when nutrients are limiting. Macroalgae were predicted to contribute a small fraction of total system primary production and their removal had little effect on predicted water quality. Despite a lack of data for calibration and a fair amount of sensitivity to individual parameter values, which highlights the need for further autecological studies to constrain formulations, the model successfully predicted macroalgal biomass dynamics and their role in ecosystem functioning. Our formulations should be exportable to other temperate systems where macroalgae occur in abundance.     

A simulation model to explore the response of the Gulf of Maine food web to large-scale environmental and ecological changes

A dynamic simulation model was constructed using outputs from a balanced Gulf of Maine (GOM) energy budget model as the initial parameter set. The model was structured to provide a recipient control set of dynamics, largely based off of flows to and from different biological groups. The model was used to produce Monte Carlo simulations that were compared (percent change in biomass) with basecase simulations for a variety of scenarios. Changes in primary production, large increases in pelagic and demersal fish biomass, increases in fishing mortality, and large increases in top predators such as baleen whales and pinnepids were simulated. These scenarios roughly simulated the potential impacts of climate change, altered fishing pressure, additional protected species mitigations, and combinations thereof. Results suggest that the GOM system is primarily influenced by bottom-up processes involving phytoplankton, zooplankton, and bacterial biomass. Pelagic and demersal fish were important in determining trends in some of the scenarios. Marine mammals, large pelagic fish, and seabirds have a minor role in the GOM system in terms of biomass flows among the ecosystem components. The system is resilient to large-scale change due, in part to many predator–prey linkages. However, major alterations could occur from sustained climate change, high fishing rates, and by combinations of these types of external forcing mechanisms.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.     

Individual-based modeling of flooding and salinity effects on a coastal swamp forest

Coastal swamps are among the rapidly vanishing wetland habitats in Louisiana. Increased flooding, nutrient and sediment deprivation, and salt-water intrusion have been implicated as probable causes of the decline of coastal swamps. We developed a two-species individual-based forest succession model to compare the growth and composition of a cypress-tupelo swamp under various combinations of flooding intensity and salinity levels, using historical time-series of stage and salinity data as inputs. Our model simulates forest succession over 500 years by representing the growth, mortality, and reproduction of individual Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) trees in a 1-km² spatial grid of 10 m × 10 m cells that vary in water levels and salinity through differences in elevation. We independently adjusted the elevations of each cell to obtain different grid-wide mean elevations and standard deviations of elevation; this affected the temporal and spatial pattern of flooding. We calibrated the model by adjusting selected parameters until averaged basal area, stem density and wood production rates under two different mean elevations (partially versus highly flooded) were qualitatively similar to comparable values reported for swamps in the literature. Corroboration involved comparing model predictions to four well-monitored contrasting habitat sites within the Maurepas Basin, Louisiana, USA. Model predictions of both species combined showed the same patterns among sites as the data, but the model overestimated wood production and the dominance of T. distichum. Exploratory simulations predicted that increased flooding leads to swamps with reduced basal areas and stem densities, while increased salinity resulted in lower basal areas at low salinity concentration (∼1-3 psu) and complete tree mortality at higher salinity concentrations (∼2-6 psu). Our model can provide insight into the succession dynamics of coastal swamps and information for the effective design of restoration actions.     

Monitoring, modeling, and management impacts of bivalve filter feeders in the oligohaline and tidal fresh regions of the Chesapeake Bay system

Populations of bivalve filter feeders are distributed throughout the oligohaline waters of the Chesapeake Bay system and, to a lesser extent, in tidal fresh waters as well. Previous studies indicate these bivalves significantly diminish phytoplankton concentrations in one major tributary, the Potomac River, and observed chlorophyll concentrations suggest bivalve influence on phytoplankton in other oligohaline reaches. We incorporated a model of these bivalves into an existing eutrophication model of the system. The model indicated that bivalves may reduce phytoplankton concentrations in oligohaline and tidal fresh waters throughout the system but the most significant effects were noted in the Potomac and Patuxent tributaries. Bivalve impacts were related to hydraulic residence time. The greatest phytoplankton reductions occurred in the regions with the longest residence time. Model carbon and nutrient budgets indicated bivalves removed 14% to 40% of the carbon load, 11% to 23% of the nitrogen load, and 37% to 84% of the phosphorus load to the regions where their impact on computed chlorophyll was greatest.     

Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach

Ticks act as vectors of pathogens that can be harmful to animals and/or humans. Epidemiological models can be useful tools to investigate the potential effects of control strategies on diseases such as tick-borne diseases. The modelling of tick population dynamics is a prerequisite to simulating tick-borne diseases and the corresponding spread of the pathogen. We have developed a dynamic model to simulate changes in tick density at different stages (egg, larva, nymph and adult) under the influence of temperature. We have focused on the tick Ixodes ricinus, which is widespread in Europe. The main processes governing the biological cycles of ticks were taken into account: egg laying, hatching, development, host (small, mainly rodents, or large, like deer and cattle, mammals) questing, feeding and mortality. This model was first applied to a homogeneous habitat, where simulations showed the ability of the model to reproduce the general patterns of tick population dynamics. We considered thereafter a multi-habitat model, where three different habitats (woodland, ecotone and meadow) were connected through host migration. Based on this second application, it appears that migration from woodland, via the ecotone, is necessary to sustain the presence of ticks in the meadow. Woodland can therefore be considered as a source of ticks for the meadow, which in turn can be regarded as a sink. The influence of woodland on surrounding tick densities increases in line with the area of this habitat before reaching a plateau. A sensitivity analysis to parameter values was carried out and demonstrated that demographic parameters (sex ratio, development, mortality during feeding and questing, host finding) played a crucial role in the determination of questing nymph densities. This type of modelling approach provides insight into the influence of spatial heterogeneity on tick population dynamics.     

Sea level rise and eelgrass (Zostera marina) production: A spatially explicit relative elevation model for Padilla Bay, WA

The dynamics that govern the elevation of a coastal wetland relative to sea level are complex, involving non-linear feedbacks among opposing processes. Changes in the balance between these processes can result in significant alterations to vegetation communities that are adapted to a specific range of water levels. Given that current sedimentation rates in Padilla Bay, Washington are likely less than historical levels and that eustatic sea level rise is accelerating, the extensive Zostera marina (eelgrass) meadows in the bay may be at risk of eventual submergence. We developed a spatially explicit relative elevation model and used it to project changes in the productivity and distribution of eelgrass in Padilla Bay over the next century. The model is mechanistic and incorporates many of the processes and feedbacks that govern coastal wetland elevation change. Accretion estimates made using ²¹⁰Pb dating of sediment cores, sediment characteristics measured within cores, and eelgrass productivity and decomposition data were used to initialize and calibrate the model. Validation was performed using an elevation change rate measured with a network of surface elevation tables. Both the field data and model simulations revealed a net accretion deficit for the bay. Simulations using current rates of sea level rise indicated an overall expansion of eelgrass within Padilla Bay over the next century as it migrates from the center of the bay shoreward.     

Modelling spatial distribution of the Croatian marine benthic habitats

Within the framework of the 3-year project “Mapping the habitats of the Republic of Croatia” the marine benthic habitats of the entire Croatian maritory were mapped. The supralittoral and the mediolittoral were mapped as a function of the coastal lithology and the presumed levels of human impact (both in scale of 1:100,000). The infralittoral was mapped on the basis of spatial modelling (using neural networks as a modelling tool, data about habitats collected by fieldwork as the independent variable for training and testing the model, and the digital bathymetrical model, the distance from coast, the second spectral channel of Landsat ETM+ satellite image and the sea bottom sea temperature, salinity and current magnitude, as dependent variables). The circalittoral and the bathyal were mapped by overlapping and reinterpretation of the existing spatial databases (bathymetry and lithology) within the framework of the raster-GIS.     

Simulating the temporal pattern of waste production in farmed gilthead seabream (Sparus aurata), European seabass (Dicentrarchus labrax) and Atlantic bluefin tuna (Thunnus thynnus)

Most fish farming waste output models provide gross waste rates as a function of stocked or produced biomass for a year or total culture cycle, but without contemplating the temporality of the discharges. This work aims to ascertain the temporal pattern of waste loads by coupling available growth and waste production models and developing simulation under real production rearing conditions, considering the overlapping of batches and management of stocks for three widely cultured species in the Mediterranean Sea: gilthead seabream (Sparus aurata), European seabass (Dicentrarchus labrax) and Atlantic bluefin tuna (Thunnus thynnus). For a similar annual biomass production, the simulations showed that waste output and temporal dumping patterns differ between the three species as a result of the disparities in growth velocity, nutrient digestibility, maintenance metabolic budget and husbandry. The simulations allowed the temporal patterns including the periods of maximum discharge and the dissolved and particulate nitrogen and phosphorus content in the wastes released to be determined, both of which were seen to be species-specific.     

Influences of canopy structure and physiological traits on flux partitioning between understory and overstory in an eastern Siberian boreal larch forest

Boreal forests play an important role in the global balance of energy and CO₂. Our previous study of elaborate eddy covariance observations in a Siberian boreal larch forest, conducted both above the forest canopy and at the forest floor, revealed a significant contribution of latent heat flux (LE) from the cowberry understory to the whole ecosystem LE. Thus, in the present study, we examined what factors control the partitioning of whole ecosystem LE and CO₂ flux into the understory and overstory vegetation, using detailed leaf-level physiology (for both understory and overstory vegetation) and soil respiration property measurements as well as a multilayer soil-vegetation-atmosphere transfer (SVAT) model. The modeling results showed that the larch overstory's leaf area index (LAI) and vertical profile of leaf photosynthetic capacity were major factors determining the flux partitioning in this boreal forest ecosystem. This is unlike other forest ecosystems that tend to have dense LAI. We concluded that control of the larch overstory's LAI had a relationship with both the coexistence of the larch with the cowberry understory and with the water resources available to the total forest ecosystem.     

Computer simulation applied to the biological control of the insect Aphis gossypii for the parasitoid Lysiphlebus testaceipes

In integrated pest management (IPM), biological control is one of the possible options for the prevention or remediation of an unacceptable pest activity or damage. The success of forecast models in IPM depends, among other factors, on the knowledge of temperature effect over pests and its natural enemies. In this work, we simulated the effects of parasitism of Lysiphlebus testaceipes (Cresson, 1880) (Hymenoptera: Aphidiidae) on Aphis gossypii (Glover, 1877) (Hemiptera: Aphididae), a pest that is associated to crops of great economic importance in several parts of the world. We made use of experimental data relative to the host and its parasitoid at different temperatures. Age structure was incorporated into the dynamics through the Penna model. The results obtained showed that simulation, as a forecast model, can be a useful tool for biological control programs.     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.     

Simulation modeling to understand how selective foraging by beaver can drive the structure and function of a willow community

Beaver–willow (Castor-Salix) communities are a unique and vital component of healthy wetlands throughout the Holarctic region. Beaver selectively forage willow to provide fresh food, stored winter food, and construction material. The effects of this complex foraging behavior on the structure and function of willow communities is poorly understood. Simulation modeling may help ecologists understand these complex interactions. In this study, a modified version of the SAVANNA ecosystem model was developed to better understand how beaver foraging affects the structure and function of a willow community in a simulated riparian ecosystem in Rocky Mountain National Park, Colorado (RMNP). The model represents willow in terms of plant and stem dynamics and beaver foraging in terms of the quantity and quality of stems cut to meet the energetic and life history requirements of beaver. Given a site where all stems were equally available, the model suggested a simulated beaver family of 2 adults, 2 yearlings, and 2 kits required a minimum of 4 ha of willow (containing about10 stems m⁻²) to persist in a steady-state condition. Beaver created a willow community where the annual net primary productivity (ANPP) was 2 times higher and plant architecture was more diverse than the willow community without beaver. Beaver foraging created a plant architecture dominated by medium size willow plants, which likely explains how beaver can increase ANPP. Long-term simulations suggested that woody biomass stabilized at similar values even though availability differed greatly at initial condition. Simulations also suggested that willow ANPP increased across a range of beaver densities until beaver became food limited. Thus, selective foraging by beaver increased productivity, decreased biomass, and increased structural heterogeneity in a simulated willow community.