Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)

Several studies have proven the importance of field margins in sustaining biodiversity and other work has been done on the effect of field management on field margin flora. However few models have been built to predict the effects of field management on the flora. Our project addresses this need for a model capable of predicting the effect of cropping techniques and their timing on the flora of field margins. Primula vulgaris is a biodiversity indicator, characteristic of undisturbed flora and found in field margins and woodlands: its population has been declining for several years. We created a temporal matrix model of P. vulgaris populations on field margins, taking into account the effects of field, field margin and roadside management based on literature and expert knowledge. We then analysed its sensitivity to demographic parameters by comparing lambda (growth rate) sensitivity and elasticity. We compared the management parameter effect using the relative growth rate of the population after 6 years of simulation. Sensitivity analysis to biological parameters showed the importance of adult survival and seed production and germination. Results show that P. vulgaris is particularly sensitive to broad-spectrum herbicides and that other management techniques like early mowing, scything and scrub-killer (diluted broad-spectrum herbicide or specific herbicide) are less aggressive. Our simulations show that management of cash crops in Brittany is too aggressive for P. vulgaris populations and that 4-5 years of grassland in the adjacent field are necessary to maintain populations.     

Controlling annual weeds in cereals by deploying crop rotation at the landscape scale: Avena sterilis as an example

Weed control through crop rotation has mainly been studied in a nonspatial context. However, weed seeds are often spread beyond the crop field by a variety of vectors. For weed control to be successful, weed management should thus be evaluated at the landscape level. In this paper we assess how seed dispersal affects the interactions between crop rotation and landscape heterogeneity schemes with regard to weed control. A spatially explicit landscape model was developed to study both short- and long-term weed population dynamics under different management scenarios. We allowed for both two- and three-crop species rotations and three levels of between-field weed seed dispersal. All rotation scenarios and seed dispersal fractions were analyzed for both completely homogeneous landscapes and heterogeneous landscapes in which more than one crop was present. The potential of implementing new weed control methods was also analyzed. The model results suggest that, like crop rotation at the field level, crop rotation implemented at the landscape level has great potential to control weeds, whereby both the number of crop species and the cropping sequence within the crop rotation have significant effects on both the short- and long-term weed population densities. In the absence of seed dispersal, weed populations became extinct when the fraction of each crop in the landscape was randomized. In general, weed seed densities increased in landscapes with increasing similarity in crop proportions, but in these landscapes the level of seed dispersal affected which three-crop species rotation sequence was most efficient at controlling the weed densities. We show that ignoring seed dispersal between fields might lead to the selection of suboptimal tactics and that homogeneous crop field patches that follow a specific crop rotation sequence might be the most sustainable method of weed control. Effective weed control through crop rotation thus requires coordination between farmers with regard to cropping sequences, crop allocation across the landscape, and/ or the fraction of each crop across the landscape.     

A simulation study of the medium-term effects of field patterns on cross-pollination rates in oilseed rape (Brassica napus L.)

Gene flow between cultivars within a landscape may lead to impurities that reduce harvest value. In OSR, as for most crops, impurity rates are expected to depend on the spatial distribution of crops over the landscape. However, in contrast to other well-studied crops such as maize, OSR crops generate seed banks in European agro-ecosystems. Gene flow is thus a spatio-temporal process which depends on cropping systems. We therefore aimed at identifying spatial variables that have an effect on regional or local harvest impurities, taking account of the time since the introduction of OSR crops in the regions and of cropping system. Gene flow was simulated over 36 field patterns cultivated with either 15% or 30% of OSR fields, among which 10% or 50% were GM, for three contrasted cropping systems, with the GeneSys software already used for EU co-existence studies. Through regression analyses, we determined spatial and agronomic factors that most affected harvest impurity rates of non-GM OSR after one or seven years of OSR cultivation. The cropping system was the main factor explaining regional harvest impurity rates. Its importance increased after six years of OSR cultivation. For a given cropping system, the regional impurity rate after one year increased linearly with the current proportion of GM crop. In contrast, impurity rates after six years largely depended on the proportions of OSR crop (GM or not) in the two preceding years. During the first year of OSR cultivation, local impurity rates were mostly explained by the distance to the closest GM field. After six years, these rates were mostly explained by the density of GM volunteers in the analysed field and, to a lesser degree, to that of volunteers in neighbour non-OSR fields. Cropping systems were most important in determining impurity rates and the way impurity rates related to regional or local factors. Determination of isolation distances to ensure harvest purity should thus consider past history of OSR cultivation in the area and, in particular, how current or future cropping systems will manage volunteers. Regression quantiles were fitted to the simulated data to determine regional rules (i.e. the maximum regional area of GM OSR and isolation distances between GM and non-GM crops) as a function of the risk accepted by the decision-maker (i.e. the % of situations exceeding harvest impurity thresholds), the cropping system and the volunteer infestation.     

Prediction of germination rates of weed species: Relationships between germination speed parameters and species traits

In fields, the timing of weed emergence flushes is mostly related to the timing and rate of seed germination, which depend on seed dormancy level, soil temperature and water potential conditions as well as soil tillage and crop sowing date. Seed germination parameters are essential in weed dynamics models to account for the effects of soil conditions on weed demography. Since these parameters are difficult to measure, our objective was to test the possibility of estimating them from easily accessible information. Seed germination parameters (germination lag-time, time to mid-germination and mid-germination rate) were measured or collected from the literature for 25 weed species with contrasted seed characteristics. Correlations were then searched for between these parameters and morphological, chemical and physiological seed traits as well as seed dormancy level. The dormancy level was positively correlated with speed of germination parameters. Earliness of germination was positively correlated with seed lipid content and the seed area to mass ratio. Germination was also earlier and faster in species with a high base temperature for germination. These relationships explained about half the observed variability in germination speed parameters but should be further tested before being used to predict the germination behaviour of weed species in the field in different seasons.     

A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal

Spatial model of annual weed seed dispersal, in this article, was theoretically derived. According to the requirements of building the spatial model, we designed and done an indoor experiment of weed seed dispersal by wind. In the experiment, the seeds of Bromus sterilis were released at 100 cm height under different wind velocity conditions. Based on the experimental data, the spatial models of seed dispersal of the weed species were built, which were divided into three types according to the coefficient β < 0, β = 0, β > 0. The results showed that dispersal of annual weed seed in any direction obeyed an approximate Gaussian distribution; under the experimental conditions, spatial distribution type of weed seed dispersal changed with variation of wind velocity. Well-known Howard et al.'s model (Howard et al., 1991) of Bromus sterilis seed dispersal is an especial example of the model built in this article. The result of model analysis indicated that the distribution type described by Howard's model was similar to that of seed dispersal of the weed species at the height of 100 cm under the condition of lower wind velocity (about 2.18 m/s). Using CA simulation analysis we found that mean control agent applying to a cell with weed should have a decrease with an increase of wind velocity to prevent weed with the initial configuration from spreading, which implicated less herbicide needs spraying in every cell with weed on average when wind velocity increases.     

Data-directed modelling of Daphnia dynamics in a long-term micro-ecosystem experiment

The micro-ecosystem under consideration consists of three compartments forming a closed chain in which water circulates. Three trophic levels are represented in different compartments: autotrophs (algae, mainly Chlorella vulgaris), herbivores (Daphnia magna) and microbial decomposers. From a 20 years experiment with this system, data has been selected for this study. The dynamics of algae and Daphnia magna in only one of the compartments were modeled by different systems of differential and difference equations. We describe the successive steps in the process of model development, and the fitting of parameters using a Nelder-Mead simplex calibration method. Identification problems were overcome by taking values for physiological parameters in agreement with the literature. It turned out that a logistic type of model gives the best result for the structured Daphnia population because of the set up of the experiment: algae grow and reproduce in the upstream compartment. For this reason well-known plant–herbivore models did not comply with the data. The results of the parameter estimation procedure are discussed. The estimated grazing rate by Daphnia was smaller than expected. Possibly the Daphnia fed also on detritus and decomposing algae which were not measured.     

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.     

Allelopathy,a chance for sustainable weed management

The exploitation of crop allelopathy against weeds may be useful to reduce issues related to the use of herbicides. Several crops, such as alfalfa, barley, black mustard, buckwheat, rice, sorghum, sunflower and wheat, demonstrate strong weed suppression ability, either by exuding allelochemical compounds from living plant parts or from decomposing residues. As well as the positive effect on weed reduction, the introduction in agronomic rotations of allelopathic crops, their use as a mulch to smother crops or as a green manure may also be helpful in reduction of other agricultural problems, such as environmental pollution, use of unsafe products and human health concerns, through a reduction in chemical inputs. Knowledge of allelopathic properties of crops may also be advantageous in mitigation of soil sickness. Moreover, information on weed allelopathy may be profitable in preventing serious crop damage if the weed biomass is buried in the soil, and a crop susceptible to allellochemicals is planned for the following year. The use of allelopathic traits from crops or cultivars with important weed inhibition qualities, together with common weed control strategies, can play an important role in the establishment of sustainable agriculture.     

Agent-based simulation of effects of stress on forest tent caterpillar (Malacosoma disstria Hübner) population dynamics

The forest tent caterpillar (Malacosoma disstria Hübner) (FTC) has an outbreak cycle of approximately 10 years; however, smaller spatial scale analyses show some regions have longer or more frequent periods of high defoliation. This may be a result of local forest fragmentation, pollution or other sources of stress that may affect FTC directly or indirectly through stress on their hosts or parasitoids. Population dynamics of FTC were examined to investigate how stress may alter the severity and frequency of defoliation. We developed a spatially explicit agent-based model to simulate the host-parasitoid dynamics of FTC. Theoretical and empirically derived parameters were established using past literature and over 50 years of population data of FTC from Ontario, Canada. We find that increasing FTC fecundity, FTC dispersal or parasitoid mortality resulted in more severe outbreaks while a decrease in parasitoid fecundity or searching efficiency resulted in an overall elevation of defoliation. Parasitoid efficiency was the most effective parameter for altering the FTC defoliation. Since plant stress has been shown to alter several of these parameters in nature due to changes in food quality, habitat suitability, and chemical cue interference, our results suggest that forests affected by stressors such as climate change and pollution will have more severe and frequent defoliation from these insects than surrounding unaffected forests. As stressors such as drought and pollution emissions are predicted to increase in frequency or intensity over the next few decades, understanding how they may affect the outbreak cycle of a forest defoliator can aid in planning strategies to reduce the detrimental effects of this insect.     

Effects of irrigation water qualities on biomass and sugar contents of sugar beet and sweet sorghum cultivars

An experiment involving four qualities of irrigation water two sugar beet and three sweet sorghum cultivars was conducted in a split plot design with four replications at Rudasht Drainage and Reclamation Experiment Station in 1999. The results showed salinity of water has an adverse effect on sugar beet and sweet sorghum biomass. Sweet sorghum cultivar SSV108 had the lowest biomass under all qualities of irrigation water Sweet sorghum cultivar Rio had the maximum biomass with water qualities of 2, 5, and 8 dS m(-1). Sugar beet cultivar 7233 had the maximum biomass with 11 dS m(-1). The effect of irrigation water quality was not significant for sugar characteristics such as brix, pol and purity. However, responses of cultivars on the above parameters were significant and sugar beet cultivars had higher brix, pol and purity and lower invert sugar and starch than sweet sorghum cultivars. In conclusion, sweet sorghum cultivars are not recommended to be irrigated with saline water of more than 8 dS m(-1) for sugar production. Under such condition, they may be suitable to be grown for forage purposes.     

飞机草的繁殖能力与种子的萌发特性

飞机草（Chromolaena odorata）是一种入侵性极强的外来杂草,现正在我国南部地区迅速传播,其繁殖特性与种子萌发对环境条件的适应能力是成功入侵扩散的前提。采用野外调查与室内试验相结合的方法,研究了飞机草的繁殖能力与种子的萌发特性。结果表明,飞机草能够进行无性繁殖,但其有性生殖能力更强,成熟植株的种子生产量高,种子质量轻,并且具有冠毛等附属结构。环境因子能够影响飞机草种子的萌发,其萌发的最适温度约为28℃,萌发过程中不需要特别的养分供应,并且能够忍耐一定程度的干旱胁迫。酸性环境能够促进飞机草种子的萌发,但当pH降至2.0时,其发芽率显著降低。掩埋处理能够抑制飞机草种子的萌发,当埋藏深度达3.0 cm时,所有的种子均不能正常萌发与出苗。     

Analysis of annual fluctuations of C. nodosa in the Venice lagoon: Modeling approach

A simple simulation model was developed to describe the growth trends of Cymodocea nodosa (Ucria) Ascherson based on data sets from the Venice lagoon. The model reproduces the seasonal fluctuations in the above and belowground biomass and in shoot density. The modeling results are in good agreement with data on net production, growth rates and chemical–physical parameters of water. It was assumed that light and temperature are the most important factors controlling C. nodosa development, and that the growth was not limited by nutrient availability. The aim was to simulate biomass production as a function of external forcing variables (light, water temperature) and internal control (plant density). A series of simulation experiments were performed with the basic model showing that among the most important phenomena affecting C. nodosa growth are: (1) inhibition of production and recruitment of new shoots by high temperature and (2) light attenuation due to seasonal fluctuation.     

Modelling the effects of extreme events on the dynamics of the amphipod Corophium orientale

The brackish water amphipod Corophium orientale is the dominant macroinvertebrate species in the upper Mira estuary, a small mesotidal system located in the southwest coast of Portugal. As climate changes will increase the frequency and intensity of extreme events such as floods and droughts, these will have a negative effect on benthic estuarine invertebrates, namely C. orientale. In order to understand the effects of these events on C. orientale, a dynamic model, based on published information and calibrated with field data, was developed and different scenarios were tested.For model construction, the annual development of three cohorts of C. orientale, their growth rates, and the establishment of the timing of each cohort rise and extinction are introduced. This structure can be repeated indefinitely, for years, and few parameters are required. The model simulations highlight the need for refuge areas that enable a fast recovery of the amphipod population after an extreme event and the recolozination of the affected areas.     

The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics

A fundamentally revised version of the HERMES agro-ecosystem model, released under the name of MONICA, was calibrated and tested to predict crop growth, soil moisture and nitrogen dynamics for various experimental crop rotations across Germany, including major cereals, sugar beet and maize. The calibration procedure also included crops grown experimentally under elevated atmospheric CO₂ concentration. The calibrated MONICA simulations yielded a median normalised mean absolute error (nMAE) of 0.20 across all observed target variables (n = 42) and a median Willmott's Index of Agreement (d) of 0.91 (median modelling efficiency (ME): 0.75). Although the crop biomass, habitus and soil moisture variables were all within an acceptable range, the model often underperformed for variables related to nitrogen. Uncalibrated MONICA simulations yielded a median nMAE of 0.27 across all observed target variables (n = 85) and a median d of 0.76 (median ME: 0.30), also showing predominantly acceptable results for the crop biomass, habitus and soil moisture variables. Based on the convincing performance of the model under uncalibrated conditions, MONICA can be regarded as a suitable simulation model for use in regional applications. Furthermore, its ability to reproduce the observed crop growth results in free-air carbon enrichment experiments makes it suited to predict agro-ecosystem behaviour under expected future climate conditions.     

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.     

COSMOS,a spatially explicit model to simulate the epidemiology of Cosmopolites sordidus in banana fields

A stochastic individual-based model called COSMOS was developed to simulate the epidemiology of banana weevil Cosmopolites sordidus, a major pest of banana fields. The model is based on simple rules of local movement of adults, egg laying of females, development and mortality, and infestation of larvae inside the banana plants. The biological parameters were estimated from the literature, and the model was validated at the small-plot scale. Simulated and observed distributions of attacks were similar except for five plots out of 18, using a Kolmogorov–Smirnov test. These exceptions may be explained by variation in predation of eggs and measurement error. An exhaustive sensitivity analysis using the Morris method showed that predation rate of eggs, demographic parameters of adults and mortality rate of larvae were the most influential parameters. COSMOS was therefore used to test different spatial arrangements of banana plants on the epidemiology of C. sordidus. Planting bananas in groups increased the time required to colonise plots but also the percentage of banana plants with severe attacks. Spatial heterogeneity of banana stages had no effect on time required to colonise plots but increased the mean level of attacks. Our model helps explain key factors of population dynamics and the epidemiology of this tropical pest.     

A system-dynamic model on the competitive growth between Potamogeton malaianus Miq. and Spirogyra sp.

A system-dynamic model has been built to evaluate the competition between submerged macrophytes Potamogeton malaianus Miq. (PM) and filamentous green algae Spirogyra sp. (SP). The data background is based on a spring–summer and an autumn–winter experiment carried out in artificial field ponds. The experiments had the aim to acquire a knowledge base necessary to a successful restoration of submerged macrophyte vegetation in Lake Taihu, China by use of P. malaianus Miq. The model mainly focuses on variations in water volume; biomass dynamics of P. malaianus Miq., Spirogyra sp. and zoobenthos; nutrients cycling between water column, P. malaianus Miq., Spirogyra sp., zoobenthos, detritus and sediment. Sixteen state variables are included in the model: biomass of P. malaianus Miq., Spirogyra sp. and zoobenthos; nitrogen in sediments, detritus, in P. malaianus Miq., in Spirogyra sp. and zoobenthos; total dissolved nitrogen; phosphorus in sediments, detritus, in P. malaianus Miq., in Spirogyra sp. and in zoobenthos; total dissolved phosphorus, and water volume of the experiment pond. The calibration and validation of the model show a good accordance with the results of the spring–summer experiment and the autumn–winter experiment.     

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

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

Maximum feasible distance of windborne cross-pollination in Brassica napus: A ‘mass budget’ model

A theory of gene dispersal by wind pollination can make an important contribution to understanding the viability and evolution of important plant groups in the Earth's changing landscape and it can be applied to evaluate concerns about the spread of engineered genes from genetically modified (GM) crops into conventional varieties via windborne pollen. Here, we present a model of cross-pollination between plant populations due to the wind. We perform a ‘mass budget’ of pollen by accounting for the number of pollen grains from release in the source population, dispersal from the source to the sink population by the wind, and deposition on receptive surfaces in the sink population. Our model can be parameterised for any wind-pollinated species, but we apply it to Brassica napus (oilseed rape or canola) to investigate the threat posed by wind pollination to GM confinement in agriculture. Specifically, we calculate the maximum feasible distance at which a particular level of windborne gene dispersal could be attained. This is equivalent to the separation distance between populations or fields required to achieve a given threshold of gene dispersal or adventitious GM presence. As required, model predictions of the upper bounds on levels of wind-mediated gene dispersal exceed observations from a wide range of published studies. For a level of gene dispersal below 0.9%, which is the EU threshold for GM adventitious presence, we predict that the maximum feasible distance for agricultural fields of B. napus is 1000 m, regardless of field shape and direction of prevailing winds. For fields closer than 1000 m, our model results do not necessarily imply that the 0.9% threshold is likely to be breached, because in this instance we have conservatively set the values of parameters where current knowledge is limited. We also predict that gene dispersal is reduced by 50% when the lag in peak flowering between the source and sink populations is 13 days, and reduced by 90% when the lag is 24 days. We identify further measurements necessary to improve the accuracy of the model predictions.     

Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes

Effective conservation of amphibian populations requires the prediction of how amphibians use and move through a landscape. Amphibians are closely coupled to their physical environment. Thus an approach that uses the physiological attributes of amphibians, together with knowledge of their natural history, should be helpful. We used Niche Mapper™ to model the known movements and habitat use patterns of a population of Western toads (Anaxyrus (=Bufo) boreas) occupying forested habitats in southeastern Idaho. Niche Mapper uses first principles of environmental biophysics to combine features of topography, climate, land cover, and animal features to model microclimates and animal physiology and behavior across landscapes. Niche Mapper reproduced core body temperatures (T_c) and evaporation rates of live toads with average errors of 1.6 ± 0.4 °C and 0.8 ± 0.2 g/h, respectively. For four different habitat types, it reproduced similar mid-summer daily temperature patterns as those measured in the field and calculated evaporation rates (g/h) with an average error rate of 7.2 ± 5.5%. Sensitivity analyses indicate these errors do not significantly affect estimates of food consumption or activity. Using Niche Mapper we predicted the daily habitats used by free-ranging toads; our accuracy for female toads was greater than for male toads (74.2 ± 6.8% and 53.6 ± 15.8%, respectively), reflecting the stronger patterns of habitat selection among females. Using these changing to construct a cost surface, we also reconstructed movement paths that were consistent with field observations. The effect of climate warming on toads depends on the interaction of temperature and atmospheric moisture. If climate change occurs as predicted, results from Niche Mapper suggests that climate warming will increase the physiological cost of landscapes thereby limiting the activity for toads in different habitats.