FOAM, a new simple benthic degradative module for the LAMP3D model: an application to a Mediterranean fish farm

The modelling framework already introduced by Doglioli, Magaldi, Vezzulli and Tucci to predict the potential impact of a marine fish farm is improved following different directions, namely (1) real historic current-metre data are used to force the simulations, (2) settling velocity values specifically targeting Mediterranean fish species are used, and (3) a new benthic degradative module, the Finite Organic Accumulation Module, is added to the modelling framework. The Finite Organic Accumulation Module uses the output of the other functional units of the modelling framework to calculate the organic load on the seabed. The Finite Organic Accumulation Module considers the natural capability of the seafloor in absorbing part of the organic load. Different remineralization rates reflect the sediment stress level according to the work of Findlay and Watling. Organic degradation for both uneaten feed and faeces is evaluated by changing the release modality (continuous and periodical) and by varying the settling velocities. It is found that the maximum impact on the benthic community is observed either for quickly sinking uneaten feed released twice a day, or for less intense near-bottom current conditions. If both the above-mentioned scenarios coexist, a high stress level is established in the sediment. The model also suggests that the use of self-feeders in cages can reduce farm impacts significantly. These results show how the new and more complete modelling framework presented here is able to improve the objectivity in the decision-making processes and how it may be successfully used for planning and monitoring purposes.     

Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km²), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m⁻² d⁻¹ and 2.7–6.1 g C m⁻² d⁻¹ for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data aggregation. However, the scale of climate data is more relevant for impacts on annual averages of NPP or if the period is strongly affected or dominated by drought stress. There should be an awareness of the greater uncertainty for the NPP values in these situations if data are not available at high resolution. On the other hand, the results suggest that there is no need to simulate at high resolution for long term regional NPP averages based on the simplified assumptions (soil and management constant in time and space) used in this study.     

The density dilemma: limitations on juvenile production in threatened salmon populations

Density‐dependent processes have repeatedly been shown to have a central role in salmonid population dynamics, but are often assumed to be negligible for populations at low abundances relative to historical records. Density dependence has been observed in overall spring/summer Snake River Chinook salmon Oncorhynchus tshawytscha production, but it is not clear how patterns observed at the aggregate level relate to individual populations within the basin. We used a Bayesian hierarchical modelling approach to explore the degree of density dependence in juvenile production for nine Idaho populations. Our results indicate that density dependence is ubiquitous, although its strength varies between populations. We also investigated the processes driving the population‐level pattern and found density‐dependent growth and mortality present for both common life‐history strategies, but no evidence of density‐dependent movement. Overwinter mortality, spatial clustering of redds and limited resource availability were identified as potentially important limiting factors contributing to density dependence. The ubiquity of density dependence for these threatened populations is alarming as stability at present low abundance levels suggests recovery may be difficult without major changes. We conclude that density dependence at the population level is common and must be considered in demographic analysis and management.     

变时相生长模型技术及其在小班数据更新中的应用

小班数据更新是地方森林资源监测和资源档案管理的需要，实现它的必要条件是建立小班动态数据库和建立小班数据更新模型。本文着重对后者的现实林分建模中每年变化的大量的部分，采伐的问题处理，根据微变化调整原理，提出变时相生长模型技术，从而消除了误差逐年积累和放大的问题，提高了小班数据更新的可靠性。     

Tracing Pb Pollution Penetration in Temperate Podzols

We combine high‐resolution soil sampling with lead (Pb) analyses (concentrations and stable isotopes) in two temperate podzols, together with previous data obtained with selective Al and Fe dissolution techniques. We aim to assess how atmospheric Pb is incorporated into the soils during pedogenesis. Partial least squares modelling for Pb concentrations shows that the podzolization process has the largest effect on Pb concentration (80·3% of the variance). The proportion of inorganic secondary compounds, the input of fresh organic matter from the soil surface and the relative abundance of Fe versus Al are responsible for a small part of the Pb concentration variance. Lead isotopic composition (²⁰⁶Pb/²⁰⁷Pb ratios) depends on soil organic matter content either fresh/poorly humified (57·3% of the variance) or humified (24·7% of the variance). The Pb linked to inorganic compounds and the overall podzolization process play a minor role in isotopic signature (5·3 and 3·7% of the variance respectively). Soil pH appears to be the controlling variable of the different transport and retention mechanisms. The relatively low isotopic ratios observed in spodic horizons result from geogenic Pb released through the preferential dissolution of the isotopically distinct most weatherable minerals of the parent material in the eluvial horizons, which undergoes downward mobilization. An accurate knowledge of soil reactive components and formation mechanisms is essential to a correct diagnose of the scope of Pb pollution and a more effective design of remediation strategies. Copyright © 2017 John Wiley & Sons, Ltd.     

Predictive models of weed population dynamics

Many of the challenges faced by weed ecologists can be met only by the capability to predict the responses of weed populations to changes in their environment or management. In spite of this, a review of papers published in Weed Research suggests that weed ecologists are remarkably reluctant to produce detailed, quantitative predictions. This may result from uncertainty in the accuracy of predictions and indeed, a variety of reasons have been put forward to suggest that the potential utility of weed models may be limited in this regard. In this study, we review the applications to which weed models have been put. Focusing on predictive population modelling, we highlight several limitations that can lead to failures of this approach and we discuss the likely prospects for weed population modelling. We make three points regarding the future of weed modelling. First, owing to prohibitive data requirements, the development of highly mechanistic models that attempt to make detailed predictions of weed population numbers is unlikely to be very successful. Second, data collection for developing weed models needs to be rethought. Weed models are most commonly compromised by a lack of spatial and temporal replication, preventing modellers from measuring parameter variability and error effectively and limiting assessments of model uncertainty. Finally, the utility of models needs to be better appreciated; models are key tools in making long range predictions of how management will affect weed populations, but, we estimate, they are used in only a small fraction of studies. Without the further development of models for weed population dynamics, our ability to predict long-term dynamics will be restricted.     

Modelling the introduction and transmission of Campylobacter in a North American chicken flock

Campylobacter is the second leading cause of foodborne illness in the United States. Although many food production animals carry Campylobacter as commensal bacteria, consumption of poultry is the main source of human infection. Previous research suggests that the biology of Campylobacter results in complete flock colonization within days. However, a recent systematic review found that the on-farm prevalence of Campylobacter varies widely, with some flocks reporting low prevalence. We hypothesized that the low prevalence of Campylobacter in some flocks may be driven by a delayed introduction of the pathogen. The objectives of this study were to (a) develop a deterministic compartmental model that represents the biology of Campylobacter, (b) identify the parameter values that best represent the natural history of the pathogen in poultry flocks and (c) examine the possibility that a delayed introduction of the pathogen is sufficient to replicate the observed low prevalence examples documented in the literature. A deterministic compartmental model was developed to examine the dynamics of Campylobacter in chicken flocks over a 56-day time period prior to movement to the abattoir. The model outcome of interest was the final population prevalence of Campylobacter at day 56. The resulting model that incorporated a high transmission rate (β = 1.04) was able to reproduce the wide range of prevalence estimates observed in the literature when pathogen introduction time is varied. Overall, we established that the on-farm transmission rate of Campylobacter in chickens is likely high and can result in complete colonization of a flock when introduced early. However, delaying the time at which the pathogen enters the flock can reduce the prevalence observed at 56 days. These results highlight the importance of enforcing strict biosecurity measures to prevent or delay the introduction of the bacteria to a flock.     

Phocine distemper virus in the North and European Seas - Data and models, nature and nurture

Two outbreaks of phocine distemper have severely affected harbour seal (Phoca vitulina) populations in European and UK waters. The first occurred in 1988 when the causative virus was identified as a new member of the genus morbillivirus. The second outbreak in 2002 was first detected on the same Danish Island of Anholt and involved similar populations and geographical locations. However, despite the obvious similarities between the epidemics, differences in viral transmission and case mortality were found. Harbour seals are highly susceptible to infection while sympatric grey seals (Halichoerus grypus) are resistant but could be important asymptomatic carriers of the disease. Arctic phocid seals remain the most likely source of the virus and grey seals could be the link between these primary hosts and the harbour seal populations further south. Future epidemiological models should therefore consider including multiple host species. The future conservation and management of harbour seal populations vulnerable to PDV relies on the ability to accurately predict the long-term impact on population abundance and distribution. Although knowledge about the behaviour and pathogenesis of the virus has increased substantially and data on host movements and contact rates are accumulating, studies into the determinants of the host range have lagged behind. The development of more realistic epidemiological models should be combined with studies into the factors controlling species and individual susceptibility. Assessing the risk of infection to endangered but currently unexposed potential host species (such as the Hawaiian monk seal, Monachus schauinslandi) is essential for guiding potential conservation management options, such as vaccination     

红壤中水热耦合转化的实验和数值模拟研究

Coupled transfer of soil water and heat in closed columns of homogeneous red soil was studied under laboratory conditions.A coupled model was constructed using soil physical theory,empirical equations and experimental data to predict the coupled transfer.The results show that transport of soil water was affected by temperaature gradient,and the largest net water transport was found in the soil column with initial water content of 0.148m^3m^-3,At the same time,temperature changes with the transport of soil water was in a nonlinear shape as heat parameters wre function of water content,and the changes of temperature were positively correlated with the net amount of water transported.Numerical modelling results show that the predicted values of temperature distribution were close to the observed values,while the predicted values of water content exhibited limited deviation at both ends of the soil column due to the slight temperature changes at both ends .It WAS indicated that the model proposed here was applicable.