Root,shoot and soil parameters required for process-oriented models of crop growth limited by water or nutrients

A review is given of the prospects for using process-oriented models of water and nutrient uptake in improving integrated agriculture. Government-imposed restrictions on the use of external inputs will increase the likelihood of (temporary) nutrient or water stress in crop production in NW Europe and thus a better understanding is required of shoot-root-soil interactions than presently available. In modelling nutrient and water uptake, three approaches are possible: 1) models-without-roots, based on empirically derived efficiency ratios for uptake of available resources, 2) models evaluating the uptake potential of root systems as actually found in the field and 3) models which also aim at a prediction of root development as influenced by interactions with environmental factors. For the second type of models the major underlying processes are known and research can concentrate on model refinement on the one hand and practical application on the other. The main parameters required for such models are discussed and examples are given of practical applications. For the third type of models quantification of processes known only qualitatively is urgently needed.     

T cells in murine lupus: propagation and regulation of disease

MRL/Mp-lpr/lpr mice develop a spontaneous lupus syndrome, including hypergammaglobulinemia, autoantibodies, glomerulonephritis, and lymphadenopathy. To investigate the role of lymphocyte subsets in the pathogenesis of disease, lupus-prone MRL mice deficient in T cells, T cells, or both were generated. Mice deficient in T cells developed a partially penetrant lupus syndrome, characterized by lymphadenopathy, elevated levels of class-switched immunoglobulins, an increased incidence of antinuclear antibodies, and immune deposits in kidneys which progressed to renal insufficiency over time. In comparison to wild type animals, T cell-deficient animals developed an accelerated and exacerbated disease phenotype, characterized by accelerated hypergammaglobulinemia and enhanced autoantibody production and mortality. Repertoire analysis of these latter animals identified polyclonal expansion (V) of CD4+B220-cells. Mice lacking both and T cells failed to generate class-switched autoantibodies and immune complex renal disease. First, these findings demonstrate that murine lupus in the setting of Fas-deficiency does not absolutely require the presence of T cells, and they also suggest that a significant basis for MRL/lpr disease, including renal disease, involves T cell-independent, T cell dependent, polyreactive B cell autoimmunity, upon which T cell-dependent mechanisms aggravate specific autoimmune responses. Second, these data indicate that T cells partake in the regulation of systemic autoimmunity, presumably via their effects on CD4+B220-T cells that provide B cell help. Finally, these results demonstrate that MRL/lpr B cells, despite their intrinsic abnormalities, cannot per se cause tissue injury without T cell help.Abbreviations snRNPs small nuclear ribonucleoprotein particles     

Predicting badger sett numbers: evaluating methods in East Sussex

Abstract. One way in which a species' numbers may be estimated without direct counting is to predict their dispersion and density from more readily available habitat measures, such as landscape variables measured from maps or vegetation variables measured in the field. We compare the power of ordination and regression techniques for predicting badger ( Meles meles L.) numbers at a local scale, using a land class system, map-read landscape variables and field-derived vegetation variables. Sett density was used as a surrogate of badger density. Multiple linear regression using vegetation and landscape variables together gave the most accurate prediction of sett density, while ordination techniques were of lesser value. The addition of vegetation variables to landscape variables did not substantially improve the power of ordination. Outlier Sett Density was predicted more accurately, and by different variables, to Main Sett Density. The relationship between badger ecology and habitat variables that were useful in predicting sett density is discussed.     

Structured modelling of animal cells

Recent advances in computer technology have promoted the design and use of detailed, computer-based models for biological systems. For many non-biological systems, the complexity of such simulations may be considered inappropriate and unwieldy, but in biological systems, and more specifically in animal cell culture, this level of complexity simply mimics what is only beginning to be understood about metabolic processs. With this in mind, we contend that complex, structured models are vital tools in the investigation of fundamental biological processes. An example of such a simulation, which describes the commercial production of therapeutic proteins by animal cell cultures, is considered.     

Predictive models for phosphorus retention in wetlands

The potential of wetlands to efficiently remove (i.e., act as a nutrient sink) or to transform nutrients like phosphorus under high nutrient loading has resulted in their consideration as a cost-effective means of treating wastewater on the landscape. Few predictive models exist which can accurately assess P retention capacity. An analysis of the north American data base (NADB) allowed us to develop a mass loading model that can be used to predict P storage and effluent concentrations from wetlands. Phosphorus storage in wetlands is proportional to P loadings but the output total phosphorus (TP) concentrations increase exponentially after a P loading threshold is reached. The threshold P assimilative capacity based on the NADB and a test site in the Everglades is approximately 1 g m^–2 yr^–1. We hypothesize that once loadings exceed 1 g m^–2 yr^–1 and short-term mechanisms are saturated, that the mechanisms controlling the uptake and storage of P in wetlands are exceeded and effluent concentrations of TP rise exponentially. We propose a One Gram Rule for freshwater wetlands and contend that this loading is near the assimilative capacity of wetlands. Our analysis further suggests that P loadings must be reduced to 1 g m^–2 yr^–1 or lower within the wetland if maintaining long-term low P output concentrations from the wetlands is the central goal. A carbon based phosphorus retention model developed for peatlands and tested in the Everglades of Florida provided further evidence of the proposed One Gram Rule for wetlands. This model is based on data from the Everglades areas impacted by agricultural runoff during the past 30 years. Preliminary estimates indicate that these wetlands store P primarily as humic organic-P, insoluble P, and Ca bound P at 0.44 g m^–2 yr^–1 on average. Areas loaded with 4.0 g m^–2 yr^–1 (at water concentrations>150 g·L^–1 TP) stored 0.8 to 0.6 g m^–2 yr^–1 P, areas loaded with 3.3 g m^–2 yr^–1 P retained 0.6 to 0.4 g m^–2 yr^–1 P, and areas receiving 0.6 g m^–2 yr^–1 P retained 0.3 to 0.2 g m^–2 yr^–1. The TP water concentrations in the wetland did not drop below 50 g·L^–1 until loadings were below 1 g m² yr^–1 P.     

The expected effects of climate change on wheat development

Air temperature and the atmospheric concentrations of carbon dioxide are expected to rise. These two factor have a great potential to affect development, growth and yield of crops, including wheat. Rising air temperature may affect wheat development more than rising atmospheric CO₂ as there is not yet evidence that elevated CO₂ concentrations can directly induce changes in wheat development. In winter wheat, temperature has a complex effect on development due to its strong interaction with vernalization and photoperiod. In this paper, potential effects of rising temperature on the development of winter wheat from sowing to heading are considered in the light of this complex controlling mechanism. Data from a large series of field trials made in Romania is analysed at first and, subsequently, the IATA-Wheat Phenology model is used to calculate the impact of air warming on wheat development under different climate change scenarios. Data from the field trials showed very clearly the occurrence of a complex temperature/photoperiod/vernalization interaction for field sown crops and demostrated that the photoperiodic and vernalization responses have a key role in controlling the duration of the emergence-heading period. Temperature plays, instead, a central role in controlling seed germination and crop emergence as well as leaf inititiation and leaf appearance rate. The results of model analysis showed very well that the impact of an even or uneven distribution of warning effects may be very different. In the first case, the model predicted that the duration of the vegetative period was at least partly reduced in some years. In the second case, the model suggested that if warming will be more pronounced in winter than in spring, as predicted for some areas of the world by General Circulation Models, we may expect an increase in the duration of the vegetative phase of growth. On the contrary, in case of a spring warming but unchanged winter temperatures, we may expect a substantial decrease in the duration of the vegetative period.     

Models to predict lake annual mean total phosphorus

A lake is a product of processes in its watershed, and these relationships should be empirically quantifiable. Yet few studies have made that attempt. This study quantifies and ranks variables of significance to predict annual mean values of total phosphorus (TP) in small glacial lakes. Several new empirical models based on water chemistry variables, on map parameters of the lake and its catchment, and combinations of such variables are presented. Each variable provides only a limited (statistical) explanation of the variation in annual mean values of TP among lakes. The models are markedly improved by accounting for the distribution of the characteristics (e.g., the mires) in the watershed. The most important map parameters were the proportion of the watershed lying close to the lake covered by rocks and open land (as determined with the drainage area zonation method), relief of the drainage area, lake area and mean depth. These empirical models can be used to predict annual mean TP but only for lakes of the same type. The model based on map parameters (r ²=0.56) appears stable. The effects of other factors/variables not accounted for in the model (like redox-induced internal loading and anthropogenic sources) on the variation in annual mean TP may then be estimated quantitatively by residual analysis. A new mixed model (which combines a dynamic mass-balance approach with empirical knowledge) was also developed. The basic objective was to put the empirical results into a dynamic framework, thereby increasing predictive accuracy. Sensitivity tests of the mixed model indicate that it works as intended. However, comparisons against independent data for annual mean TP show that the predictive power of the mixed model is low, likely because crucial model variables, like sedimentation rate, runoff rate, diffusion rate and precipitation factor, cannot be accurately predicted. These model variables vary among lakes, but this mixed model, like most dynamic models, assumed that they are constants.     

Ecological optima and tolerances of Thelypteris limbosperma,Athyrium distentifolium,and Matteuccia struthiopteris along environmental gradients in Western Norway

The distribution and abundance of Thelypteris limbosperma, Athyrium distentifolium, and Matteuccia struthiopteris are modelled statistically in relation to 14 environmental variables along the major climatic, topographic, and edaphic gradients in western Norway. The data are from 624 stands from which measurements or estimates of mean January and mean July temperatures, humidity, altitude, aspect, and slope are available. From 182 of these stands eight soil variables have also been measured. The species responses are quantified by two numerical methods: Gaussian logit regression and weighted averaging (WA) regression. The estimated WA optima suggest that A. distentifolium has an ecological preference for low July and January temperatures, high altitudes, and soils of low-medium pH and base content. The species shows statistically significant Gaussian responses with summer temperature, humidity (= Martonnes humidity index), altitude, slope, aspect, pH, cation exchange capacity, and base saturation with optima of 8.7 °C, 188.9, 1220 m, 28°, 29°, 4.8, 13.77 mEq 100 g dry soil^-1, and 13.4%, respectively. These suggest that the occurrence and relative abundance of A. distentifolium are well predicted by summer temperature, topography, and soil pH and base status. T. limbosperma has WA optima that suggest that it favours moderately high winter and summer temperatures, high humidity, medium altitude, and soils of low pH and base content. It has significant Gaussian responses to summer temperature (optimum =12.6 °C), winter temperature (-1.8 °C), humidity (179.2), altitude (459.5 m), slope (22.5°), and Na (0.7 mg 100 g dry soil^-1). These suggest that climatic factors, altitude, and slope are significant predictors for its occurrence and abundance. M. struthiopteris has high WA optima for summer temperature, pH, Ca, Mg, K, Na, cation exchange capacity (CEC), and base saturation, and a low optima for humidity and winter temperature. Of these, summer temperature (16.0 °C), Ca (63.1 mg 100 g dry soil^-1), Mg (41.0 mg 100 g dry soil^-1), K (23.6 mg 100 g dry soil^-1), Na (5.0 mg 100 g dry soil^-1), CEC (60.7 mEq 100 g dry soil^-1), and base saturation (56.3%) have significant Gaussian logit responses, as do aspect (150.2°) and loss-on-ignition (9.4%). These results suggest that the occurrence and relative abundance of M. struthiopteris are well predicted by high soil base cations, a generally southern aspect, low organic content in the soil, and high July temperatures.