Effects of foundress number on brood raids and queen survival in the fire ant Solenopsis invicta

In several ant species, colonies are founded by small groups of queens (pleometrosis), which coexist until the first workers eclose, after which all but one queen is killed. It has been hypothesized that, by producing a larger cohort of workers, cooperating queens may increase colony success during brood raids, a form of competition in which brood and workers from losing nests are absorbed into winning colonies. To test whether this benefit is sufficient to favor pleometrosis, newly mated queens of the fire ant Solenopsis invicta were assembled in groups of one, two, three, or four, reared in the laboratory until the first workers eclosed, then planted in the field in replicated assemblages. The proportion of colonies engaging in brood raids increased with average foundress number per nest and with colony density but was unaffected by variance in foundress number among interacting colonies. Within mixed assemblages of single-queen and multiple-queen colonies, queen number had no effect on the likelihood of engaging in raids or the probability of nest survival through the brood raiding period. However, following nearly 30% of raids, queens moved to new nests and displaced the resident queens. When queen relocation and subsequent mortality were accounted for, it was found that the survival of queens from four-queen groups was substantially higher than that of solitary queens. By contrast, the survival of queens from two-queen colonies was no greater than that of solitary queens. These results show that the competitive advantages of multiple-queen colonies are sufficient to counterbalance the increased mortality of queens within groups only when the number of foundresses is greater than two and when colonies are founded at high density. When colonies lose brood raids, the workers appear to abandon their mothers to join surviving colonies. However, in laboratory experiments, queens attempting to enter foreign nests were significantly more likely to displace the resident queen if their own daughters were present within the invaded nest. Thus, workers may be able to bias the probability that their mother rejoins them and displaces competing queens.     

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.     

On the use of growth rate parameters for projecting population sizes: Application to aphids

This paper extends the application of the cumulative size based mechanistic model, which has previously been shown to describe diverse aphid population size data well. The mechanistic model is reviewed with a focus on the explanatory role of the birth and death rate formulation. An analysis of two data sets, one on the mustard aphid and the other on the pecan aphid, indicates that multiple linear regression equations based on the estimated birth and death rate parameters alone account for nearly all (R² > 0.95) of the variability in two key population attributes, namely the peak count and the cumulative density. This indicates that population size variables may be projected directly from the growth rate parameters using linear equations. Such linear relationships based on the birth and death rate parameters are shown to hold also for certain generalized mechanistic models for which the analytical solution is not available. The birth and death rate coefficients, therefore, constitute a new succinct set of variables that could be included in the predictive modeling of aphid populations, as well as other insect and animal populations with local collapse which follow similar growth dynamics.     

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.     

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.     

A multi-agent simulation to assess the risk of malaria re-emergence in southern France

A multi-agent simulation (MAS) was developed to assess the risk of malaria re-emergence in the Camargue in southern France, a non-endemic area where mosquitoes of the genus Anopheles (Culicidae) live. The contact rate between people and potential malaria vectors, or the human biting rate, is one of the key factor to predict the risk of re-emergence of malaria, would the parasite be introduced in the region. Our model (called MALCAM) represents the different agents that could influence malaria transmission in the Camargue – people, mosquitoes, animal hosts and the landscape – in a spatially explicit environment. The model simulates spatial and temporal variations in human biting rate at the landscape scale. These variations depend on the distribution of people and potential vectors, their behaviour and their interactions. A land use/cover map was used as a cellular-spatial support for the movements of and interactions between mobile agents. The model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. The MALCAM model provides a tool to better understand the interactions between the multiple agents of the disease transmission system, and the land use and land cover factors that control the spatial heterogeneity in these interactions. It allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. This application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.     

Multi-metric evaluation of the models WARM,CropSyst, and WOFOST for rice

WARM (Water Accounting Rice Model) simulates paddy rice (Oryza sativa L.), based on temperature-driven development and radiation-driven crop growth. It also simulates: biomass partitioning, floodwater effect on temperature, spikelet sterility, floodwater and chemicals management, and soil hydrology. Biomass estimates from WARM were evaluated and compared with the ones from two generic crop models (CropSyst, WOFOST). The test-area was the Po Valley (Italy). Data collected at six sites from 1989 to 2004 from rice crops grown under flooded and non-limiting conditions were split into a calibration (to estimate some model parameters) and a validation set. For model evaluation, a fuzzy-logic based multiple-metrics indicator (MQI) was used: 0 (best) ≤ MQI ≤ 1 (worst). WARM estimates compared well with the actual data (mean MQI = 0.037 against 0.167 and 0.173 with CropSyst and WOFOST, respectively). On an average, the three models performed similarly for individual validation metrics such as modelling efficiency (EF > 0.90) and correlation coefficient (R > 0.98). WARM performed best in a weighed measure of the Akaike Information Criterion: (worst) 0<wk<1$0<w_k<1$ (best), considering estimation accuracy and number of parameters required to achieve it (mean wk=0.983$w_k=0.983$ against 0.007 and ∼0.000 with CropSyst and WOFOST, respectively). WARM results were sensitive to 30% of the model parameters (ratio being lower with both CropSyst, <10%, and WOFOST, <20%), but appeared the easiest model to use because of the lowest number of crop parameters required (10 against 15 and 34 with CropSyst and WOFOST, respectively). This study provides a concrete example of the possibilities offered using a range of assessment metrics to evaluate model estimates, predictive capabilities, and complexity.     

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.     

The effects of colony-level selection on the social organization of honey bee (Apis mellifera L.) colonies: colony-level components of pollen hoarding

Two-way selection for quantities of stored pollen resulted in the production of high and low pollen hoarding strains of honey bees (Apis mellifera L.). Strains differed in areas of stored pollen after a single generation of selection and, by the third generation, the high strain colonies stored an average 6 times more pollen than low strain colonies. Colony-level organizational components that potentially affect pollen stores were identified that varied genetically within and between these strains. Changes occurred in several of these components, in addition to changes in the selected trait. High strain colonies had a significantly higher proportion of foragers returning with loads of pollen, however, high and low strain colonies had equal total numbers of foragers Colony rates of intake of pollen and nectar were not independent. Selection resulted in an increase in the number of pollen collectors and a decrease in the number of nectar collectors in high strain colonies, while the reciprocal relationship occurred in the low strain. High and low strain colonies also demonstrated different diurnal foraging patterns as measured by the changing proportions of returning pollen foragers. High strain colonies of generation 3 contained significantly less brood than did low strain colonies, a consequence of a constraint on colony growth resulting from a fixed nest volume and large quantities of stored pollen. These components represent selectable colony-level traits on which natural selection can act and shape the social organization of honey bee coloniesCommunicated by R.F.A. Moritz     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.     

A model for measuring leaf growth rate of vegetative shoot in the seagrass, Zostera marina

A new model for determining leaf growth in vegetative shoots of the seagrass Zostera marina (eelgrass) is described. This model requires the weights of individual mature and immature whole leaves and leaf plastochrone interval (P_L) as parameters, differing from the conventional leaf marking technique (CLM) that requires cutting and separation between new and old tissue of leaves. The techniques required for the model are the same as for the plastochrone method, but the parameters differ between both methods in use of the weight of individual immature leaves. In a mesocosm study, eelgrass growth was examined, and parameters for the new model and plastochrone method (the weights of individual mature and immature leaves and P_L) were measured. Leaf growth rate was measured using the CLM and determined by the new method and the plastochrone method. The results were then compared between the CLM, the new model, and the plastochrone method. The results obtained with the new model were similar to those obtained with the CLM. However, the results of the plastochrone method differed from those of the CLM, while the weight of immature leaves varied seasonally. The new model was also used to determine leaf growth in a natural eelgrass bed in Mikawa Bay, Japan, and revealed the growth rates in all shoots and those of different ages. This method would be advantageous as an accurate means of direct measurement in fieldwork, and should therefore be a useful tool for monitoring seagrass growth.     

Waterfowls habitat modeling: Simulation of nest site selection for the migratory Little Tern (Sterna albifrons) in the Nakdong estuary

This paper aims to find patterns in nest site selection by Little Terns Sterna albifrons, in the Nakdong estuary in South Korea. This estuary is important waterfowl stopover and breeding habitat, located in the middle of the East Asia-Australasian Flyway. The Little Tern is a common species easily observed near the seashore but their number is gradually declining around the world. We investigated their nests and eggs on a barrier islet in the Nakdong estuary during the breeding season (May to June, 2007), and a pattern for the nest site selection was identified using genetic programming (GP). The GP generated a predictive rule-set model for the number of Little Tern nests (training: R² = 0.48 and test: 0.46). The physical features of average elevation, variation of elevation, plant coverage, and average plant height were estimated to determine the influence on nest numbers for Little Tern. A series of sensitivity analyses stressed that mean elevation and vegetation played an important role in nest distribution for Little Tern. The influence of these two variables could be maximized when elevation changed moderately within the sampled quadrats. The study results are regarded as a good example of applying GP to vertebrate distribution patterning and prediction with several important advantages compared to conventional modeling techniques, and can help establish a management or restoration strategy for the species.     

Using classification trees to analyze the impact of exotic species on the ecological assessment of polder lakes in Flanders, Belgium

Polder lakes in Flanders are stagnant waters that were flooded by the sea in the past. Several of these systems are colonized by exotic species, but have hardly been studied until present. The aim of the present study was: (1) to assess the influence of exotic macrobenthic species on the outcome of the Multimetric Macroinvertebrate Index Flanders (MMIF) and (2) to use classification trees for evaluating to what extent physical-chemical characteristics affect the presence of exotic species.In total, 27 mollusc and 10 macro-crustacean species were present in the monitored lakes of which respectively five and four were exotic. The exclusion of the exotic species from the MMIF resulted in a significant decline of this ecological index (−0.03 ± 0.04; p = 0.00). This elimination often resulted into a lower ecological water quality class and more samples were classified into the bad and poor ecological water quality classes.Single-target classification trees for Gammarus tigrinus and Potamopyrgus antipodarum were constructed, relating environmental parameters and ecological status (MMIF) to the occurrence of both exotic invasive species. The major advantages of using single-target classification trees are the transparency of the rule sets and the possibility to use relatively small datasets. However, this classification technique only predicts a single-target attribute and the trees of the different species are often hard to integrate and use for water managers. As a solution, a multi-target approach was used in the present study. Exotic molluscs and crustaceans communities were modelled based on environmental parameters and the ecological status (MMIF) using multi-target classification trees. Multi-target classification trees can be used in management planning and investment decisions as they can lead to integrated decisions for the whole set of exotic species and avoid the construction of many models for each individual species. These trees provide general insights concerning the occurrence patterns of individual crustaceans and molluscs in an integrated way.     

The benefits of multiple mating to female seaweed flies, Coelopa frigida (Diptera: Coelpidae)

Female seaweed flies, Coelopa frigida, have the potential to benefit from mating more than once. Single matings result in low fertility so females may benefit directly from multiple copulations by sperm replenishment. A chromosomal inversion associated with larval fitness, with heterokaryotypic larvae having higher viability than homokaryotypes, means that polyandrous homokaryotypic females have a higher probability of producing genetically fit offspring than monandrous homokaryotypic females. We allowed females to mate only once, repeatedly four times to the same male, or polyandrously four times to four different males. Multiply mated and polyandrous females laid more eggs and produced more offspring than singly mated and monandrous females, respectively. Polyandrous females laid more eggs, had higher egg-to-adult survival rates and produced more offspring than repeatedly mated females. Fertility rates did not differ between treatments. The observed fitness patterns therefore resulted from increased oviposition through multiple mating per se, and a further increase in oviposition coupled with higher egg-to-adult offspring survival benefits to polyandry. Daily monitoring of individual females over their entire life spans showed that multiple copulations induced early oviposition, with polyandrous females ovipositing earlier than repeatedly mated females. Singly mated and polyandrous females incurred a longevity cost independent of egg production, whereas repeatedly mated females did not. This suggests that repeatedly mating with the same male may counteract a general cost of mating. Longevity, however, was not correlated with overall female fitness. Our data are discussed in the overall context of the seaweed fly mating system.Communicated by G. Wilkinson     

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 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.     

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.     

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.