Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.     

Antennal responses of four species of tree-killing bark beetles (Coleoptera: Scolytidae) to volatiles collected from beetles,and their host and nonhost conifers

Summary. Host selection in tree-killing bark beetles (Coleoptera: Scolytidae) is mediated by a complex of semiochemical cues. Using gas chromatographic-electroantennographic detection (GC-EAD) and GC-mass spectrometric analyses, we conducted a comparative study of the electrophysiological responses of four species of tree-killing bark beetles, the Douglas-fir beetle, Dendroctonus pseudotsugae, Hopkins, the mountain pine beetle, D. ponderosae Hopkins, the spruce beetle, D. rufipennis Kirby, and the western balsam bark beetle, Dryocoetes confusus Swaine, to volatiles captured by aeration of 1) bole and foliage of four sympatric species of conifers, Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco, lodgepole pine, Pinus contorta var. latifolia Engelm., interior spruce, Picea engelmannii x glauca, and interior fir, Abies lasiocarpa x bifolia, and 2) con- and heterospecific beetles at three stages of attack. We identified 13 monoterpenes in the conifers and nine compounds in the volatiles of beetles that elicited antennal responses. There was no qualitative difference in the terpene constitution of the four species of conifers and very little difference across beetle species in their antennal response to compounds from conifers or beetles. The lack of species-specific major or minor components in conifers suggests that beetles would need to detect differences in the ratios of different compounds in conifers to discriminate among them. Attraction to hosts and avoidance of nonhost conifers may be accentuated by perception of compounds emitted by con- and heterospecific beetles, respectively. The 22 compounds identified are candidate semiochemicals with potential behavioural roles in host location and discrimination.     

Assessing environmental factors in red spruce (Picea rubens Sarg.) growth in the Great Smoky Mountains National Park, USA: From conceptual model, envirogram, to simulation model

This study provides a method for assessing a multiplicity of environmental factors in red spruce growth in the Great Smoky Mountains National Park (GSMNP) of Southeastern USA. Direct and indirect factors in the annual growth increment are first organized into a schematic input-output envirogram (ARIRS), and this information is then used to construct a simulation model (ARIM). The envirogram represents a structured conceptualization of most environmental factors involved in growth, as developed from relevant literature. This interdisciplinary synthesis distinguishes direct vs. indirect factors in growth and takes account of the systems ecology concept that indirect factors may be as important as or more important than direct ones in regulating growth. The ARIRS envirogram summarizes hierarchically organized, within- and cross-scale, local-to-global interactions, and its construction makes it obvious that growth is influenced by many cross-scale spatiotemporal interactions. More research on genecology is still needed to clarify the role of phenotypic plasticity and adaptive capacity in nutrient cycling, global change, and human disturbance.     

Modelling the responses of wildlife to human disturbance: An evaluation of alternative management scenarios for black-crowned night-herons

The impact of anthropogenic disturbance on wildlife is increasing becoming a source of concern as the popularity of outdoor recreation rises. There is now more pressure on site managers to simultaneously ensure the continued persistence of wildlife and provide recreational opportunities. Using ‘Simulation of Disturbance Activities’, a model designed to investigate the impact of recreational disturbance on wildlife, we demonstrate how a simulation modelling approach can effectively inform such management decisions. As an example, we explored the implications of various design and management options for a proposed recreational area containing a historic breeding bird colony. By manipulating the proximity, orientation and intensity of recreation, we were able to evaluate the impact of recreational activities on the behaviour of black-crowned night-heron nestlings (Nycticorax nycticorax). Using a classification and regression tree (CART) procedure to analyse simulation output, we explored the dynamics of multiple strategies in concert. Our analysis revealed that there are inherent advantages in implementing multiple strategies as opposed to any single strategy. Nestlings were not disturbed by recreation when bird-watching facility placement (proximity and orientation) and type were considered in combination. In comparison, proximity alone only led to a <10% reduction in disturbance. Thus we demonstrate how simulation models based on customised empirical data can bridge the gap between field studies and active management, enabling users to test novel management scenarios that are otherwise logistically difficult. Furthermore, such models potentially have broad application in understanding human-wildlife interactions (e.g. exploring the implications of roads on wildlife, probability of bird strikes around airports, etc.). They therefore represent a valuable decision-making tool in the ecological design of urban infrastructures.     

Monoterpene chemodiversity of ponderosa pine in relation to herbivory and bark beetle colonization

Summary. Ponderosa pine, Pinus ponderosa Laws. (Pinaceae), forests in Arizona have suffered from a nine-year period of drought and bark beetle, Ips lecontei Swaine (Coleoptera: Scolytidae), outbreaks. Abiotic and biotic stress in ponderosa pine results in the induced synthesis of certain monoterpenes that may in turn affect bark beetle behavior and survival. In this study, we investigate whether induced monoterpene production could result in a different monoterpene composition that remains stored in the needles or the trunk resin of the tree. Needle and resin samples in addition to trunk cores were collected from ponderosa pines at three locations in Arizona. Ungulate browsing induced a significant increase in limonene (P=0.010) and in chemodiversity (P=0.009), a measure of the evenness of distribution among the monoterpenes present in needles. We compared the level of ‘stress’ of the trees by measuring the thickness of annual rings in living trees and those that were killed by bark beetles. Where drought occurred, the spacing of annual rings from the last 10 years of trees killed by bark beetles was significantly smaller (P=0.020) compared to living trees. There was no difference in the monoterpene composition between the core sections of closest spacing of annual rings (stressed years) compared to the sections of widest spacing, which indicates that monoterpenes are distributed evenly throughout the extended resin system. In the area where the degree of drought was less overall, none of the individual monoterpenes present in the resin was related to bark beetle killed trees. However, about half the living pines had resin in which one of the major monoterpenes (α-pinene, Δ³-carene, and limonene) was absent, and these trees had a lower monoterpene chemodiversity compared to trees killed by bark beetles. Trees with these three major monoterpenes, corresponding to the average relative proportion in living pines at that location, may sustain higher selection and colonization by bark beetles.     

A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations

In forest management and ecological research, consideration of the impacts and risks of climate change or management optimisation is complex. Computer models have long been applied as tools for these tasks. Process-based forest growth models claim to overcome the limitations of empirical statistical models, but the capacity of different process-based models and modelling approaches have rarely been compared directly. This study evaluates stepwise multiple regression models in comparison to four process-based modelling approaches (3-PG, 3-PG+, CABALA and Forest-DNDC) for greenfield predictions of Eucalyptus globulus plantation growth from 2 to 8 years after planting throughout southern Australia.     

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.     

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.     

A discrete model for estimating the development time from egg to infecting larva of Ostertagia ostertagi parametrized using a fuzzy rule-based system

Ostertagia ostertagi is a nematode, predominantly affecting cattle in the Pampean region of Argentina. A mathematical model parametrized using fuzzy rule-based systems of the Takagi-Sugeno-Kant type (FTSK) for estimating the development time from egg to infecting larval stage L3 of the gastrointestinal parasite O. ostertagi is here proposed. The estimation of development time of O. ostertagi is essential for the generation of appropriate control mechanisms, since this provides information about the time when parasites are ready to migrate to pastures. For the purpose of reflecting the natural environmental conditions, the mean daily temperature is taken as the main and only regulator of the development time. Humidity conditions are considered to be sufficient for the normal development of the larvae. Hence the individual's daily growth is a function of its length and the mean temperature recorded on the previous day. It is expressed in terms of a difference equation with fuzzy parameters, which are defined using laboratory data. Model outputs are tested against results of field experiments. Simulation results are very satisfactory, yielding a mean estimation error (MEE) of 0.64 weeks, with variance 0.34, and a determination coefficient R² = 0.74. The model clearly exhibits an inverse relationship between development time and temperature both in controlled and in field conditions. It also exhibits a very sensitive response both to the order in which the temperature sequence occurs, - reproducing the differences observed between spring and autumn - and to the amplitude of the temperature range.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation

In this study we combined an extensive database of observed wildfires with high-resolution meteorological data to build a novel spatially and temporally varying survival model to analyze fire regimes in the Mediterranean ecosystem in the Cape Floristic Region (CFR) of South Africa during the period 1980-2000. The model revealed an important influence of seasonally anomalous weather on fire probability, with increased probability of fire in seasons that are warmer and drier than average. In addition to these local-scale influences, the Antarctic Ocean Oscillation (AAO) was identified as an important large-scale influence or teleconnection to global circulation patterns. Fire probability increased in seasons during positive AAO phases, when the subtropical jet moves northward and low level moisture transport decreases. These results confirm that fire occurrence in the CFR is strongly affected by climatic variability at both local and global scales, and thus likely to respond sensitively to future climate change. Comparison of the modelled fire probability between two periods (1951-1975 and 1976-2000) revealed a 4-year decrease in an average fire return time. If, as currently forecasted, climate change in the region continues to produce higher temperatures, more frequent heat waves, and/or lower rainfall, our model thus indicates that fire frequency is likely to increase substantially. The regional implications of shorter fire return times include shifting community structure and composition, favoring species that tolerate more frequent fires.     

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.     

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs,with emphasis on Halimeda tuna

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an “individual” being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns.     

Mechanisms of moisture stress in a mid-latitude temperate forest: Implications for feedforward and feedback controls from an irrigation experiment

While it is well established that stomata close during moisture stress, strong correlations among environmental (e.g., vapor pressure deficit, soil moisture, air temperature, radiation) and internal (e.g., leaf water potential, sap flow, root-shoot signaling) variables obscure the identification of causal mechanisms from field experiments. Models of stomatal control fitted to field data therefore suffer from ambiguous parameter identification, with multiple acceptable (i.e., nearly optimal) model structures emphasizing different moisture status indicators and different processes. In an effort to minimize these correlations and improve parameter and process identification, we conducted an irrigation experiment on red maples (Acer rubrum L.) at Harvard Forest (summers of 2005 and 2006). Control and irrigated trees experienced similar radiative and boundary layer forcings, but different soil moisture status, and thus presumably different diurnal cycles of internal leaf water potential. Measured soil moisture and atmospheric forcing were used to drive a transient tree hydraulic model that incorporated a Jarvis-type leaf conductance in a Penman–Monteith framework with a Cowan-type (resistance and capacitance) tree hydraulic representation. The leaf conductance model included dependence on both leaf matric potential, Ψ_L (so-called feedback control) and on vapor pressure deficit, D (so-called feedforward control). Model parameters were estimated by minimizing the error between predicted and measured sap flow. The whole-tree irrigation treatment had the effect of elevating measured transpiration during summer dry-downs, demonstrating the limiting effect that subsurface resistance may have on transpiration during these times of moisture stress. From the best fitted model, we infer that during dry downs, moisture stress manifests itself in an increase of soil resistance with a resulting decrease in Ψ_L, leading to both feedforward and feedback controls in the control trees, but only feedforward control for the irrigated set. Increases in the sum-of-squares error when individual model components were disabled allow us to reject the following three null hypotheses: (1) the f(D) stress is statistically insignificant (p = 0.01); (2) the f(Ψ_L) stress is statistically insignificant (p = 0.07); and (3) plant storage capacitance is independent of moisture status (p = 0.07).     

A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change—A means for assessing biosecurity risk

Increasing global temperatures as a result of climate change are widely considered inevitable for Australia. Despite this, the specific effects of climate change on Australian agriculture are little studied and the effects on agricultural pests and diseases are virtually unknown. In this paper we consider the impact of climate change on the Asiatic citrus psyllid (Diaphorina citri Kuwayama [Hemiptera: Psyllidae]); one of two known vectors of huanglongbing (citrus greening); a debilitating disease which is caused in Asia by a phloem-limited bacterium ‘Candidatus Liberibacter asiaticus’ (α-Proteobacteria). D. citri does not occur in Australia, but if introduced would pose a major threat to the viability of the Australian citrus industry and to native Citrus species. This paper presents an approach developed to understand how climate change may influence the behaviour, distribution and breeding potential of D. citri. Here we developed and describe an initial dynamic point model of D. citri biology in relation to its citrus host and applied it to a scenario of increasing temperatures, as indicators of climate change, on a continental scale. A comparison between model outputs for the three time frames considered (1990, 2030 and 2070) confirms that increasing temperatures projected under climate change will affect the timing and duration of new citrus growth (flush) necessary for psyllid development throughout Australia. Flushing will start progressively earlier as the temperature increases and be of shorter duration. There will also be a gradual southward expansion of shorter durations of the occurrence of flush. Increasing temperatures will impact on D. citri both directly through alteration of its temperature dependant development cycle and indirectly through the impact on the host flushing cycle. For the whole of Australia, a comparison between model outputs for the three scenarios considered indicates the seasonality of D. citri development will change to match changes in citrus flush initiation. Results indicate that the risk of establishment by D. citri is projected to decrease under increasing temperatures, mainly due to shortened intervals when it can feed on new leaf flushes of the host. However, the spatially heterogeneous results also suggest that regions located on the southern coastline of Australia could become more suitable for D. citri than projected under current temperatures. These results confirm the value of a linked host-pest approach as based on D. citri climatic requirements alone the model would have accounted only for shorter development periods and predicted an increased risk of potential distribution.     

Identifying key life-traits for the dynamics and gene flow in a weedy crop relative: Sensitivity analysis of the GeneSys simulation model for weed beet (Beta vulgaris ssp. vulgaris)

The benefits of genetically modified herbicide-tolerant (GMHT) sugar beet (Beta vulgaris) varieties stem from their presumed ability to improve weed control and reduce its cost, particularly targeting weed beet, a harmful annual weedy form of the genus Beta (i.e. B. vulgaris ssp. vulgaris) frequent in sugar beet fields. As weed beet is totally interfertile with sugar beet, it is thus likely to inherit the herbicide-tolerance transgene through pollen-mediated gene flow. Hence, the foreseeable advent of HT weed beet populations is a serious threat to the sustainability of GM sugar beet cropping systems. For studying and quantifying the long-term effects of cropping system components (crop succession and cultivation techniques) on weed beet population dynamics and gene flow, we developed a biophysical process-based model called GeneSys-Beet in a previous study. In the present paper, the model was employed to identify and rank the weed life-traits as function of their effect on weed beet densities and genotypes, using a global sensitivity analysis to model parameters. Monte Carlo simulations with simultaneous randomization of all life-trait parameters were carried out in three cropping systems contrasting for their risk for infestation by HT weed beets. Simulated weed plants and bolters (i.e. beet plants with flowering and seed-producing stems) were then analysed with regression models as a function of model parameters to rank processes and life-traits and quantify their effects. Key parameters were those determining the timing and success of growth, development, seed maturation and the physiological end of seed production. Timing parameters were usually more important than success parameters, showing for instance that optimal timing of weed management operations is more important than its exact efficacy. The ranking of life-traits though depended on the cropping system and, to a lesser extent, on the target variable (i.e. GM weeds vs. total weed population). For instance, post-emergence parameters were crucial in rotations with frequent sugar beet crops whereas pre-emergence parameters were most important when sugar beet was rare. In the rotations with frequent sugar beet and insufficient weed control, interactions between traits were small, indicating diverse populations with contrasted traits could prosper. Conversely, when sugar beet was rare and weed control optimal, traits had little impact individually, indicating that a small number of optimal combinations of traits would be successful. Based on the analysis of sugar beet parameters and genetic traits, advice for the future selection of sugar beet varieties was also given. In climatic conditions similar to those used here, the priority should be given to limiting the presence of hybrid seeds in seed lots rather than decreasing varietal sensitivity to vernalization.     

A system dynamics model for the management of the Manila clam, Ruditapes philippinarum (Adams and Reeve, 1850) in the Bay of Arcachon (France)

The Manila clam Ruditapes philippinarum (Adams and Reeve, 1850) is one of the mollusc species that, driven mainly by the shellfish market industry, has extended throughout the world, far beyond the limits of its original habitat. The Manila clam was introduced into France for aquaculture purposes, between 1972 and 1975. In France, this venerid culture became increasingly widespread and, since 1988, this species has colonised most of the embayments along the French Atlantic coast. In 2004, this development resulted in a fishery of ca. 520 t in Arcachon Bay.     

A distributed-delay model to predict ageing and survival rates of adults of Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in granaries filled with wheat

A time-varying distributed-delay model simulating effects of multifactors was developed. Prediction of the ageing rate and survival distribution of adults of the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in various environments found in wheat-filled granaries was conducted as an example to illustrate the application of this developed model. Published adult mortalities, determined at different temperatures, relative humidities, and food sources, were directly used to find the average ageing rate and family of cumulative function of adult mortality. The developed model could predict the adult survival rate at constant or transient temperatures with different relative humidities. This model could also simulate the effect of adult acclimation to their environment when they experience temperature and moisture fluctuations inside granaries. To validate the developed model, the simulation results were compared with available experimental data from the literature. There was no difference between predicted and measured mortalities in two granaries in which the mortalities were determined in a 4-month experiment.