A simulation model for the management of vicuña populations

The population dynamics of the vicuña was modelled based on field data from the Central Galeras Sector, Perú. Rains were simulated in order to obtain net primary productivity and grass availability which act upon density-dependent fecundity and mortality. The model produces a population growth curve that tends to stabilize at densities around 100 vicuñas per km². Harvest and shearing processes were simulated as part of the vicuña population management model. Harvest was based upon a fixed threshold density D_e below which no harvest occurs; for densities above D_e harvesting is applied at a rate proportional to the difference between D_e and the current population density (fixed escapement or ‘bang-bang’ harvest rule). Management optimization was analyzed by determining the optimal escapement density D_e, which maximized either net profits or the number of animals harvested. Analyzing the results as cumulative totals over 20 years of simulation, an optimum harvest production was obtained for a D_e of about 40 vicuñas per km², and maximum profit was obtained for a D_e around 70 vicuñas per km². Analyzing the results of 20 years of simulation as annual averages with an original population density of 40 vicuñas per km², the harvest production and profits were maximized for a D_e of 40 and 60 vicuñas per km², respectively.The model was validated using data from the Reserva Nacional San Guillermo, Argentina, where vicuña and guanaco populations coexist (although their interaction was not modelled). The sensitivity analysis was performed with three different techniques: (a) stepwise multiple linear regression, (b) visual graphic analysis based on a polar coordinates system, and (c) direct evaluation of the effect on management decisions. The curve shape parameters of the fecundity and mortality functions proved to be the most important ones in determining the outcome of the model.     

A model for approving and controlling sea water pollution for recreational activity

A model for assessing approval of a beach for recreational water activity was proposed. The model is based upon a sanitary survey together with intensive microbiological monitoring three times a day, five times a week for a month. In highly populated areas, continuous surveys once a day, five days a week are needed in order to assure the cleanliness and safety of these beaches.

Due to our intensive monitoring system, we can assure that Tel‐Aviv has one of the cleanest beaches near a metropolitan area in the Mediterranean Sea.     

A simulation model of management alternatives in a freshwater fishery

A model for investigating management alternatives on the Pyramid Lake-Truckee River system of Nevada and California is presented. Cutthroat trout, Cui-ui, Tahoe Sucker and Tui Chub are modeled with special emphasis on river spawning by trout. Management decision variables include hatchery input, water flow control, and diversion screening. Preliminary results indicate that some hatchery input will be needed to support the trout even with the best river management.     

A project for the integrated management of protected coastal areas in Malta

This paper examines a 3-yr EU LIFE-funded project for the management of two especially protected areas on the Maltese coast. Project partners are the Euro-Mediterranean Centre on Insular Coastal Dynamics (ICoD), the Gaia Foundation and the Ministry for the Environment of Malta. Project sites are the Ghajn Tuffieha area on the northwest coast of Malta, and the Ramla Bay area on the island of Gozo. While both sites are in a relatively pristine state and comprise a number of features of ecological and scientific importance, they are also prime recreational areas, hosting thousands of visitors especially during the summer months. The challenge is to manage these sites in a sustainable manner in order to protect their unique ecology while simultaneously controlling and managing the human activities taking place there. The following sequence of activities is being implemented at both sites: surveys of the resources present (biodiversity, habitats, geological and hydrological features, and archaeological heritage), implementation of first intervention measures, and the drawing up and implementation of site-specific management plans, including rehabilitation and protection of biodiversity and habitats, regulations for site use, and awareness raising and educational measures. The management structure of this project supports the concept of decentralization of management of protected areas, through the granting of responsibility for the direct management of these sites to a non-governmental organization, under joint government/EU funding. This paper thus presents the project as a model for similar initiatives for the management of protected sites in the Mediterranean.     

Development of an integrated decision-support model for density management within jack pine stand-types

The objectives of this study were to (1) develop a modular-based structural stand density management model (SSDMM) and corresponding algorithmic analogue for natural (naturally regenerated stands without a history of density regulation) and managed (naturally or artificially regenerated stands with a history of density regulation) jack pine (Pinus banksiana Lamb.) stand-types, and (2) demonstrate the utility of the model in operational density management decision-making. Employing an Ontario-centric database consisting of 262 and 221 tree-list measurements obtained from 91 and 139 permanent and temporary sample plots situated within natural and managed stand-types, respectively, combined with data derived from density control experiments and sawmill simulation studies, six integrated estimation modules were constructed: Module A consisted of the parameterization of the core yield–density relationships which together drive the entire yield prediction system (e.g., size–density relationships for quadratic mean diameter, dominant height, mean volume, and mean live crown ratio, and site-specific height–age relationships); Module B consisted of the development of Weibull-based parameter prediction equation systems for recovering diameter distributions and composite height-diameter equations for height estimation; Module C consisted of the development of composite taper equations for predicting log products and stem volumes; Module D consisted of the development of allometric-based composite biomass equations for each above-ground component (bark, stem, branch and foliage) from which biomass estimates and associated carbon-based equivalents were derived; Module E consisted of the development of sawmill-specific composite equations for estimating chip and lumber volumes; and Module F consisted of the development of composite equations for estimating wood density and mean maximum branch diameter. The utility of the model was demonstrated by simultaneously contrasting a set of complex density management regimes (commercial thinning and variable planting densities) in terms of a broad array of stand-level yield outcomes and performance measures: overall productivity, log-product distributions, biomass production and carbon yields, recoverable products (chip and lumber volumes) and associated monetary values, economic efficiency, duration of optimal site occupancy, structural stability, and fibre attributes (wood density and mean maximum branch diameter). In summary, the modular-based SSDMM provides the analytical foundation for evaluating the likelihood of realizing a multitude of stand-level objectives when designing density control regimes for jack pine stand-types.     

A strategy for wildlife management in depopulating rural areas of Japan

Former ranges of wild animals have been reestablished in many developed countries. However, this reestablishment has led to increasing human–wildlife conflict in agroforest ecosystems. In Japan, human–wildlife conflict, such as crop raiding by and ecological impacts of wild ungulates and primates, is a serious problem in depopulated rural areas due to these animal range expansions and increased abundances. Japan's human population is predicted to decline by 24% by 2050, and approximately 20% of agricultural settlements will become completely depopulated. In this scenario, anthropogenic pressures on wildlife (e.g., hunting and habitat alteration) will continue to decrease and human–wildlife conflict will increase due to increasing wildlife recovery. Japan's local governments plan to slow range recovery, prevent species reestablishment, or remove recolonizing large mammals through lethal control. This strategy, however, is not cost-effective, and workforce shortages in depopulated communities make it infeasible. Moreover, the suppression of wildlife prevents the recovery of ecological functions and thus would degrade regional biodiversity. The declining pressure on wildlife that accompanies human depopulation will prevent the restoration of any past states of human–wildlife interaction. We suggest human-used areas in rural landscapes be aggregated in compact cities and that in transition zones between human settlements and depopulated lands that land-sharing approaches be applied. Concentrating management efforts in compact cities may effectively decrease human–wildlife conflict, rather than intensifying human pressures. Reforestation of depopulated lands may lead to recovery of wildlife habitats, their ecosystem functions, and regional biodiversity due to minimization of negative anthropogenic effects (land-sparing approach). Balancing resolution of human–wildlife conflict and ecological rewilding could become a new, challenging task for regional wildlife managers.     

Wastewater reuse: A sanitation and management strategy for the Mediterranean coastal areas

Wastewater agricultural reuse has two main aspects. It is capable of preventing the discharge of wastewater treatment plant effluents in receiving waters and it is also a way to increase water resources. The controlled agricultural reuse has not been developed until now, either in Languedoc or in Catalonia, but is expected a quick development due to several circumstances: the growing awareness of water resources scarcity, the concern for sanitary hazards in bathing places, the WHO guidelines and the development of tertiary cost‐effective treatment methods. In the coastal areas, the growing demand on water resources is putting heavy pressure on some big water users, as golf courses and landscape irrigations, potential users of reclaimed wastewater.     

A stochastic bioeconomic model for the management of clam farming

The Manila clam Tapes philippinarum is one of the most important commercial mollusc species in Europe. Intensive clam farming takes place in several coastal lagoons of the Northern Adriatic Sea, supporting local economy but raising the problem of the environmental sustainability of this activity. In this work, we propose a bioeconomic model that provides guidelines for an efficient management of intensive clam farming. Clam demography is described by a stochastic model of growth and survival, accounting for the effect of water temperature, seeding substratum and density dependence of vital rates. The model is calibrated on and applied to the case of Sacca di Goro, a lagoon located in the Po River Delta (Northern Italy). We consider two distinct management criteria: the optimisation of the marketable yield and the optimisation of monetary benefits, respectively. The use of a stochastic formulation allows us to reveal the existing trade-off between maximizing the median yield or profit and minimizing its variance. A Pareto analysis shows that seeding in spring or fall on sandy substrata and harvesting 18 months later provides the best compromise between these two contrasting objectives, maximizing profits while minimizing the associated uncertainty level. Finally, we show that seeding clams at high densities (more than 750 clams m⁻² on muddy substrata and more than 1500 elsewhere) can have not only a potentially negative impact on the ecological sustainability of clam farming, but also a negative economic effect.     

A general bioeconomic simulation model for annual-crop marine fisheries

A generalized bioeconomic simulation model of annual-crop marine fisheries is described and its use in marine fisheries management is demonstrated. The biological submodel represents the recruitment of new organisms into the fishery, the movement of organisms from one fishing area to another and from one depth to another, the growth of organisms and the mortality of organisms resulting both from natural causes and from fishing. The economic submodel represents the fishing effort exerted on each resource species, the monetary costs of fishing, the value of the harvest and the rent (or excess profits) to the fishery.Basic dynamics of the model results from changes in the number of organisms in the fishery over time, which can be summarized as a set of difference equations of the general form ΔN/Δt = R + I ? E ? M ? F where ΔN/Δt is the net change in number of organisms in the fishery over time, R is recruitment, I is immigration, E is emigration, M is natural mortality and F is fishing mortality. R is a driving variable, whereas I, E, M and F are functions of the state of the system at any given point in time. The model can be run in a deterministic or stochastic mode. Values for parameters affecting rates of recruitment, movement, growth, natural mortality and fishing mortality can be selected from uniform, triangular or normal distributions.Use of the model within a fisheries-management framework is demonstrated by evaluating several management alternatives for the pink shrimp (Penaeus duorarum) fishery on the Tortugas grounds in the Gulf of Mexico. Steps involved in use of the model, including parameterization, validation, sensitivity analysis and stochastic simulations of management policies, are explained.     

A simulation model for lead movement in a watershed

A simulation model of the movement and accumulation of automotively emitted lead in a watershed of Central Illinois is presented. The model is composed of four parallel terrestrial subsystems or zones based on traffic volume, and an aquatic system in series. The model is used to estimate historical accumulations of lead within the watershed and to compare different scenarios of reductions of lead emissions. Since the introduction of leaded gasoline an estimated 570, 000 kg of lead has been emitted in the watershed. Of this total about 36% remained airborne and left the watershed, and 3% left the watershed via the quatic system.Lead is found to be a significant pollutant in urban areas and near major highways. Without emission controls lead is expected to cause environmental problems after about 25 years.     

A survival-analysis-based simulation model for Russian wheat aphid population dynamics

A simulation model for Russian wheat aphid (RWA), Diuraphis noxia (Mordvilko), populations is built by integrating survival-analysis-based development and survivor functions and the same-shape reproduction distribution model in the framework of Leslie [Leslie, P.H., 1945. On the use of matrices in certain population mathematics. Biometrika 33, 183–212] matrix structure. Survival analysis is utilized to model both the development and survival of RWA populations, and the Cox (1972) proportional hazards model is fitted with the data sets from our laboratory observation of 1800 RWA individuals under 25 factorial combinations of five temperature regimes and five barley plant-growth stages. Rather than using simple age-specific survivor rates as in the traditional Leslie matrix, the survivor functions based on survival analysis describe age-specific, temperature and plant stage-dependent RWA survival probabilities. Similarly, a probability model from survival analysis to estimate the probability that an individual will reach mature adult stage is utilized to describe the development process; this makes the transition from nymphal stage to mature adult stage dependent on RWA age as well as temperature and plant-growth stage.Inspired by the same-shape distribution and rate-summation approach for modeling insect development, a similar approach for modeling insect reproduction under variable temperature is developed. This new same-shape reproduction distribution model incorporates individual variation in reproduction capability, as well as the effects of RWA age, temperature and plant-growth stage. Consequently, the same-shape reproduction distribution model replaces the simple age-specific fecundities in Leslie matrix model. To the best of our knowledge, this work is the first to introduce survival analysis to simulation modeling in entomology and ecology and also the first to integrate our newly developed same-shape reproduction distribution model into application.     

A state-dependent model for the optimal management of an invasive metapopulation.

Management of invasive species involves choosing between different management strategy options, but often the best strategy for a particular scenario is not obvious. We illustrate the use of optimization methods to determine the most efficient management strategy using one of the most devastating invasive forest pests in North America, the gypsy moth (Lymantria dispar), as a case study. The optimization approach involves the application of stochastic dynamic programming (SDP) to a metapopulation framework with different infestation patch sizes, with the goal of minimizing infestation spread. We use a novel "moving window" approach as a way to address a spatially explicit problem without being explicitly spatial. We examine results for two cases in order to develop general rules of thumb for management. We explore a model with limited parameter information and then assess how strategies change with specific parameterization for the gypsy moth. The model results in a complex but stable, state-dependent management strategy for a multiyear management program that is robust even under situations of uncertainty. The general rule of thumb for the basic model consists of three strategies: eradicating medium-density infestations, reducing large-density infestations, and reducing the colonization rate from the main infestation, depending on the state of the system. With specific gypsy moth parameterization, reducing colonization decreases in importance relative to the other two strategies. The application of this model to gypsy moth management emphasizes the importance of managing based on the state of the system, and if applied to a specific geographic area, has the potential to substantially improve the efficiency and cost-effectiveness of current gypsy moth eradication programs, helping to slow the spread of this pest. Additionally, the approach used for this particular invasive species can be extended to the optimization of management programs for the spread of other invasive and problem species exhibiting metapopulation dynamics.     

A model for ecological assessment to pesticide pollution management

Applying the relational analysis in the Grey System Theory and Method, the comprehensive evaluation on five pesticide pollution controlling techniques in the vegetable production has been made and a comprehensive profit (cp–comprehensive cost (cc) evaluation system (composed of 15 comprehensive cost indices and 14 comprehensive profit indices) has been established, with a index optimization matrix of comprehensive cost indices and comprehensive profit indices obtained and a ratio model of comprehensive cost to comprehensive profit (R_cc/cp) built. Results show that the R_cc/cp value of vegetables intercropping soybeans in insect-proof thin film greenhouses is the smallest and the R_cc/cp value of vegetables intercropping taros in insect-proof net greenhouses, pheromones in insect-proof thin film greenhouses, pheromones in insect-proof thin film greenhouses and ground planting (only using chemical pesticide for insect-proof without covering materials and synthetic sex pheromone) other four techniques are 0.6268, 0.6393, 0.6407, 0.9809 respectively. In accordance with the R_cc/cp value, vegetables intercropping soybeans in insect-proof thin film greenhouses can be the most optimized pesticide pollution controlling technique in the vegetable growing.     

The demand for site-specific recreational activities: A characteristics approach

A model of constrained utility maximizing behavior is developed to explain how a representative individual allocates his ski days among alternative sites. The physical characteristics of the ski areas and the individual's skiing ability are explicit arguments in the utility function; the budget allocation is given along with the parametric costs to ski (including travel costs, entrance fees, equipment costs, and the opportunity cost of his time). Shares (a site's share being the proportion of ski days that the individual spends at that site) are derived and assumed multinomially distributed, a stochastic specification which maintains the inherent properties of the shares. Maximum likelihood estimation confirms the basic hypothesis that costs, ability, and characteristics all are important determinants of the sites' shares. The model explains a large proportion of the skier's allocation of ski days. A multinomial logit model of skier behavior is also developed and maximum likelihood estimates of its parameters are obtained. Examination of the summary statistics from my model and the logit model indicates that my model predicts the skier's choice of sites better than the logit model.     

A simple model for simulation of insect pheromone dispersion within forest canopies

Synthetic pheromones and other behavioral chemicals are used by land managers to prevent insect-caused tree mortality or crop failure in forest and agricultural systems. Currently, no method exists to continuously measure pheromone concentration or movement in real-time. To improve our understanding of pheromone fate and transport under different forest canopies, results from a set of surrogate pheromone (sulfur hexafluoride tracer) experimental trials were used to evaluate a simple, instantaneous, three-dimensional Lagrangian dispersion model. The model was designed to predict both instantaneous and time-averaged pheromone concentrations. Overall, the results from the model show simulated time-averaged arc maximum concentrations within a factor of two of the observed data. The model correctly matched the sharp peaks and narrow widths of the meandering plumes observed in the instantaneous data, however the magnitude of the instantaneous peaks was often under-estimated. This model and evaluation provide the basis for a tool that can be used to guide deployment of synthetic pheromones or other semiochemicals for monitoring, mass trapping, or disruption of mating or aggregation.     

A GIS-based model for rating natural protection areas according to natural protection priorities

There has been a major urban shift of population in Turkey over the last century. Most people lived in rural areas until 1960, but now more than half live in urban areas. This trend has continued over the last 20 years, as families moved further away from city centres to find houses in the country, and this has caused land use to change rapidly. In decision-making studies to protect nature areas, rating and assessment of ecological data by scientific verification is difficult due to the huge volume and diversity of data. Therefore, the search for the most suitable and applicable method to achieve physical planning based on ecological understanding has been sought. The necessity for numerous parameters to be taken into account has stimulated the use of geographic information systems (GIS). This study assesses the usefulness of a GIS-based model in the protected area of Kaynaklar County, to the south of the city of Izmir. Existing cultural and natural land-use types, as well as soil, hydrologic, geologic and geomorphologic data layers (future classes) were gathered from field observation and using Landsat and IKONOS satellite images, and transferred to a database according to GIS rules. Index values were determined by taking impact on attributes of natural protection as a priority and these were attached to each feature class. Layers of data were merged by spatial intersection methods and new polygons were created for both cultural and natural features. A three-grade final map of the study area was generated using total index values of each new polygon.     

A model examining hierarchical wetland networks for watershed stormwater management

There is increasing awareness that solutions to degraded quality and excessive quantity of stormwater and resulting impacts on downstream water bodies may require a watershed approach to management rather that the incremental approach that is now common. Examination of low-relief watersheds characteristic of the southeastern coastal plain reveals common hierarchical patterns of surface water convergence that may be emulated in developed watersheds to enhance the efficacy of peak-flow attenuation and pollutant removal. A dynamic systems model was developed to compare stormwater management using a hierarchical network of treatment wetlands with the standard incremental approach wherein treatment systems are designed considering only site-level effluent criteria. The model simulates watershed hydrology, suspended sediment transport and phosphorus removal and transformation. Results indicate that watershed planning of stormwater collection and treatment systems using hierarchical networks can greatly enhance overall effectiveness (annual retention improvements of 31% for flow, 36% for sediment and 27% for phosphorus) with respect to an equal area of uniformly sized wetlands. Further, network proportions can be adjusted to specific runoff characteristics. Distinct roles were observed for each wetland size class: small headwater wetlands effectively removed sediment, medium-sized mid-reach wetlands retained phosphorus, while large wetlands primarily stored and attenuated long-period hydrologic flows.     

A simulation model for organic phosphorus transformation in a forest soil ecosystem

A numerical model which simulates the decomposition of litter and mineralization and immobilization of P in the humus layer of a temperate forest (beech site of Solling) is described. The model takes into account the effect of moisture, temperature and C/N ratio. The simulated concentration of P in the effluent of the humus layer agrees well with the measured values. The model predicts an increase in the C/P ratio of the unde-composed litter with time and that there is no direct mineralization of P from litter without passing through a microbial body. The net rate of mineralization is, however, always positive with its highest peak in July. Maximum immobilization of P from solution occurs in June and the minimum in January.The model is stable against changes in the litter input, its C/P ratio and other initial conditions, but it is very sensitive to changes in the efficiency factor which represents the fraction of decomposed C incorporated into microbial tissue. This is a site-specific model but can be used for grassland or agricultural systems with changes in certain parameters.     

The spread of marine non-indigenous species via recreational boating: A conceptual model for risk assessment based on fault tree analysis

Recreational vessel movements are increasingly recognised as an important pathway for the spread of non-indigenous species (NIS) in marine environments. Research on risks posed by recreational vessels has focused on external hull fouling, yet a number of studies reveal the potential for NIS to also be transferred by a range of other vessel components. This paper uses fault tree analysis as a framework for incorporating input from a panel of international experts, to elucidate the consecutive steps that must occur for NIS to be introduced from different components of recreational boats. Our conceptual model reveals the complexity of the invasion process even when only the ‘release’ phase is considered (i.e. the release of NIS from an infected vessel into a new area). The model highlights that, in addition to external fouling of the ‘hull’ (hull, rudder and propeller), important vessel components may also include fouling, sediment or water released from the deck, internal spaces, anchors and fishing/diving gear. The extent to which these components are important is situation-specific, and depends on attributes of the vessel, location and NIS present. Hence, the comprehensive model described here could be modified or simplified to reflect the attributes that are relevant to particular circumstances. We demonstrate this principle using examples of three NIS: the colonial tunicate Didemnum vexillum and the Asian kelp Undaria pinnatifida that both have established in Port Nelson New Zealand after vessel-mediated spread, and the clubbed tunicate Styela clava that was detected on a vessel hull in the port but is not known to have established. Although the modelling and assessment of some of the events identified in the fault trees would be difficult or unrealistic, it is important to acknowledge them in order to provide a comprehensive risk assessment tool. Even where risks are largely unknown, difficult to quantify, or reflect stochastic events, this does not necessarily preclude management intervention.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.