Modern broiler chickens are a major animal husbandry success story, both in terms of efficient resource utilisation and environmental sustainability. However, continuing artificial selection for both efficiency and rapid growth will be subject to both biological limits and animal welfare concerns. Using a novel analytical energy flow modelling approach, we predict how far such selection can go, given the biological limits of bird energy intake and partitioning of energy. We find that the biological potential for further improvements in efficiency, and hence environmental impact reduction, is minimal relative to past progress already made via artificial selection. An alternative breeding strategy to produce slower-growing birds to meet new welfare standards increases environmental burdens, compared to current birds. This unique analytic approach provides biologically sound guidelines for strategic planning of sustainable broiler production.

The principles and a quantitative theory of growth for monogastric livestock animals are described here, focusing on the period from birth to slaughter. The theory helps to understand key relationships between the outcomes that may be desired in a production system and their influencing factors, e.g. nutritional, genetic, and environmental, and forms the basis of current mechanistic models for predicting animal performance. We describe general physical, chemical and biological principles that should underlie any description of animal growth; and address growth as a three-faceted problem: 1) growth under ‘normal’ conditions; 2) growth under ‘limiting’ conditions; and 3) recovery growth when ‘normal’ conditions are restored. We propose a theoretical framework that incorporates these situations as facets of a whole, that encompasses growth conditions across modern livestock production systems, and in which terms such as ‘normal’ and ‘limiting’ acquire a meaning. To make this framework quantitative, we apply a body of theoretical and empirical principles in the derivation of mathematical models of growth. The usefulness of existing theories and mathematical models depends on the availability of data for testing hypotheses and parameterising models under a range of conditions. A challenge ahead, therefore, is in obtaining extensive data for further testing and consolidating modelling prediction of growth under a wide range of conditions, or as animals respond to change in limitations. Another challenge lies in addressing practical problems posed by heterogeneity in performance within groups of animals: i.e., how to manage groups towards optimal resource use and performance, and how to identify best phenotypical characteristics within breeds, strains, etc. and predict their performance. Further progress will require much greater availability of rich individual data cross-sectioning herds and breeds.

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This paper is devoted to the non-fragile exponential synchronization problem of complex dynamical networks with time-varying coupling delays via sampled-data static output-feedback controller involving a constant signal transmission delay. The dynamics of the nodes contain s quadratically restricted nonlinearities, and the feedback gain is allowed to have norm-bounded time-varying uncertainty. The control design is based on a Lyapunov–Krasovskii functional, which consists of the sum of terms assigned to the individual nodes, i.e., it is constructed without merging the complex dynamical network’s nodes into a single large-scale system. In this way, the proposed design method has substantially reduced computational complexity and improved conservativeness, and guaranties non-fragile exponential stability of the error system. The sufficient stability condition is expressed in terms of linear matrix inequalities that are solvable by standard tools. The efficiency of the proposed method is illustrated by numerical examples.

Simulation models of nutrient utilization ignore that variation in pig 19 system components can influence the predicted mean and variance of the performance 20 of a group of pigs. The objective was to develop a methodology to investigate how 21 variation: (a) in feed composition would affect the outputs of a nutrient utilization 22 model, and (b) would interact with variation that arises from the traits of individual 23 pigs. We used a P intake and utilization model to address these. Introduction of 24 stochasticity gave rise to a number of methodological challenges, e.g. how to generate 25 variation in both feed composition and pigs, and account for correlation between 26 ingredients when modelling variation associated with feed mixing efficiency. 27 Introducing variation in feed composition and genotype resulted in moderate 28 decreases in mean digested, retained and excreted P predicted for a population of pigs 29 and an increase in their associated CVs. A lower % of pigs in the population were 30 predicted to meet their requirements during the feeding period considered, by 31 comparison with the no variation (deterministic) scenario. Variation in feed ingredient 32 composition contributed more to performance variation than variation due to mixing 33 efficiency. When variation in both feed composition and pig traits were considered, it 34 was the former rather than the latter that had the dominant influence on variability in 35 pig performance. The developed framework emphasizes the consequences of 36 stochasticity on the predictions of nutrient utilization models. Such consequences will 37 have a significant impact on decisions about management strategies, such as feeding 38 that are subject to variation. 39

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The environmental impacts of 2 alternative UK broiler production systems that aim to improve bird welfare (a lower stocking density indoor system and the same system combined with heat exchangers for ventilation air) were compared with the baseline standard indoor system of broiler production. Furthermore, the environmental impacts of egg production in the conventional battery cage system (banned in the European Union in 2012) and its replacement, the enriched colony cage system, were compared. All comparisons were based on data obtained from the UK poultry industry, and the life cycle assessment method from cradle to farm gate was applied in the analyses. The results show that the lower density system slightly increased the global warming potential (GWP) of broiler production (by 2%), compared with the standard indoor system, due to increased heating requirements. However, when combined with the heat exchanger, the GWP was actually reduced by 3% when compared with the standard system. Both alternative systems for broilers resulted in a reduction in the eutrophication potential (by up to 8%) and acidification potential (by up to 10%). The results also showed that the colony cage system had 8% lower primary energy use and 3% lower GWP than the baseline cage system, due to better energy use efficiency and slightly improved productivity. There were only minor differences in the eutrophication and acidification potentials between different egg production systems. The results suggest that welfare-friendly changes in chicken systems can be achieved without a compromise in their environmental impacts.

Low phosphorus (P) digestibility combined with intensive pig production can increase P diffuse pollution and environmental load. The aim of this paper was to develop a deterministic, dynamic model able to represent P digestion, retention and ultimately excretion in growing and finishing pigs of different genotypes, offered access to diets of different composition. The model represented the limited ability of pig endogenous phytase activity to dephosphorylate phytate as a linear function of dietary calcium (Ca). Phytate dephosphorylation in the stomach by exogenous microbial phytase enzymes was expressed by a first order kinetics relationship. The absorption of non-phytate P from the lumen of the small intestine into the blood stream was set at 0.8 and the dephosphorylated phytate from the large intestine was assumed to be indigestible. The net efficiency of using digested P was set at 0.94 and assumed to be independent of BW, and constant across genotype and sex. P requirements for both maintenance and growth were made simple functions of body protein mass, and hence functions of animal genotype. Undigested P was assumed to be excreted in the feaces in both soluble and insoluble forms. If digestible P exceeded the requirements for P then the excess digestible P was excreted through the urinary flow; thus the model represented both forms of P excretion (soluble and insoluble) into the environment. Using a UK industry standard diet, model behaviour was investigated for its predictions of P digestibility, retention and excretion under different levels of inclusion of microbial phytase and dietary Ca, and different non-phytate P : phytate ratios in the diet, thus covering a broad space of potential diet compositions. Model predictions were consistent with our understanding of P digestion, metabolism and excretion. Uncertainties associated with the underlying assumptions of the model were identified. Their consequences on model predictions, as well as the model evaluation are assessed in a companion paper.

The aim of this study was to apply a life cycle assessment (LCA) method, from cradle to gate, to quantify the environmental burdens per 1,000 kg of eggs produced in the 4 major hen-egg production systems in the United Kingdom: 1) cage, 2) barn, 3) free range, and 4) organic. The analysis was based on an approach that applied a structural model for the industry and mechanistic submodels for animal performance, crop production, and nutrient flows. Baseline feeds representative of those used by the UK egg production industry were used. Typical figures from the UK egg production industry, feed intake, mortality of birds, farm energy, and material use in different systems were applied. Monte Carlo simulations were used to quantify the uncertainties in the outputs and allow for comparisons between the systems. The number of birds required to produce 1,000 kg of eggs was highest in the organic and lowest in the cage system; similarly, the amount of feed consumed per bird was highest in the organic and lowest in the cage system. These general differences in productivity largely affected the differences in the environmental impacts between the systems. Feed production, processing, and transport caused greater impacts compared with those from any other component of production; that is, 54 to 75% of the primary energy use and 64 to 72% of the global warming potential of the systems. Electricity (used mainly for ventilation, automatic feeding, and lighting) had the second greatest impact in primary energy use (16-38%). Gas and oil (used mainly for heating in pullet rearing and incineration of dead layer birds) used 7 to 14% of the total primary energy. Manure had the greatest impact on the acidification and eutrophication potentials of the systems because of ammonia emissions that contributed to both of these potentials and nitrate leaching that only affected eutrophication potential. The LCA method allows for comparisons between systems and for the identification of hotspots of environmental impacts that could be subject to mitigation.

In recent years various papers have been published on the practical use of infrared thermometry and thermal imaging to estimate leaf stomatal resistance [(amongst others: Jones, H.G., 1999a,b; Leinonen et al., 2006). Use of infrared thermometry for estimation of stomatal conductance as a possible aid to irrigation scheduling. Agricultural and Forest Meteorology 95, 139–149; Jones, H.G., 1999b. Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant Cell and Environment 22, 1043–1055; Leinonen, I., Grant, O.M., Tagliavia, C.P.P., Chaves, M.M., Jones, H.G., 2006. Estimating stomatal conductance with thermal imagery. Plant, Cell & Environment 29, 1508–1518]. These papers are based on the physical relationships linking the stomatal resistance of a leaf to its own temperature and to the temperatures of reference leaves (dry and wet). These relationships differ depending on the type of leaf (amphistomatous or with stomata on only one side) and on the way the reference leaves are wetted (on either both sides or on one side only). Because of ambiguous assumptions on the wetting process and small inaccuracies in the calculation of some resistances, these basic relationships are not clear. The present paper aims to clarify and synthesize the appropriate equations for each case.

Most thermal methods for the study of drought responses in plant leaves are based on the calculation of 'stress indices'. This paper proposes and compares three main extensions of these for the direct estimation of absolute values of stomatal conductance to water vapour (gs) using infrared thermography (IRT). All methods use the measured leaf temperature and two environmental variables (air temperature and boundary layer resistance) as input. Additional variables required, depending on the method, are the temperatures of wet and dry reference surfaces, net radiation and relative humidity. The methods were compared using measured gs data from a vineyard in Southern Portugal. The errors in thermal estimates of conductance were of the same order as the measurement errors using a porometer. Observed variability was also compared with theoretical estimates of errors in estimated gs determined on the basis of the errors in the input variables (leaf temperature, boundary layer resistance, net radiation) and the partial derivatives of the energy balance equations used for the gs calculations. The full energy balance approach requires accurate estimates of net radiation absorbed, which may not be readily available in field conditions, so alternatives using reference surfaces are shown to have advantages. A new approach using a dry reference leaf is particularly robust and recommended for those studies where the specific advantages of thermal imagery, including its non-contact nature and its ability to sample large numbers of leaves, are most apparent. Although the results suggest that estimates of the absolute magnitude of gs are somewhat subjective, depending on the skill of the experimenter at selecting evenly exposed leaves, relative treatment differences in conductance are sensitively detected by different experimenters.

The seasonal changes in two of the photosynthetic parameters of Scots pine (Pinus sylvestris L.), i.e. the light‐saturated assimilation rate (Amax) and the apparent quantum yield (α), were compared with the cold hardiness of needles throughout the course of a year. The data for the comparison were obtained from an experiment with close to ambient and elevated temperatures in open‐top chambers. The cold hardiness correlated with the photosynthesis parameters, but the relation was different in the cold acclimation and deacclimation phases, i.e. the same cold hardiness corresponded differently with Amax and α in the autumn and spring. The temperature treatment had a clear effect on the relation of α with cold hardiness in the dehardening phase but not during the hardening phase. The ecological significance of the seasonal changes in the photosynthetic capacity, i.e. in Amax and α, is discussed.

Five-year-old Norway spruce (Picea abies (L.) Karst.) seedlings were subjected to three simulated growing seasons in controlled environment chambers. Plants were acclimated to a soil temperature of 16 degrees C during the first and third growing seasons, but were allocated at random to soil temperature treatments of 9, 13, 18 and 21 degrees C during the second growing season. Low soil temperature during the second growing season depressed stomatal conductance and photosynthetic rate (A) per unit of projected leaf area, although intercellular CO2 concentrations did not differ significantly between treatments. At all soil temperatures, total chlorophyll concentration first decreased and then increased, although the rate of increase and the final concentration increased with soil temperature, which may explain the effect of soil temperature on A. Neither chlorophyll a/b ratio nor leaf nitrogen concentration was significantly affected by soil temperature. Treatment differences disappeared during the third simulated growing season when plants were again acclimated to a soil temperature of 16 degrees C.

The adaptation of the annual cycle of development of boreal and temperate trees to climatic conditions has been seen as a result of stabilizing selection caused by two opposite driving forces of natural selection, i.e. the tolerance of unfavorable conditions during the frost exposed season (survival adaptation) and the effective use of growth resources during the growing season (capacity adaptation). In this study, two theories of the effects of climate on the adaptation of the timing of bud burst of trees were evaluated. This was done with computer simulations by applying a temperature sum model for predicting the timing of bud burst of different Norway spruce genotypes on the basis of air temperature data from various climatic conditions. High geographical variation in the temperature response of bud burst, typical for Norway spruce, was included in the theoretical analyses. The average timing of bud burst and the corresponding risk of occurrence of damaging frost during the susceptible period after bud burst were calculated for each genotype in each climate. Two contrasting theories of the stabilizing selection were evaluated, i.e. the overall adaptedness of each genotype was evaluated either 1) by assuming a fixed threshold for the risk of frost damage, or 2) by assuming a tradeoff between the risk of frost damage and the length of the growing season. The tradeoff assumption produced predictions of between provenance variation in bud burst which correspond more closely with empirical observations available in literature, compared to the fixed threshold assumption.

Reliable models are required to assess the impacts of climate change on forest ecosystems. Precise and independent data are essential to assess this accuracy. The flux measurements collected by the EUROFLUX project over a wide range of forest types and climatic regions in Europe allow a critical testing of the process-based models which were developed in the LTEEF project. The ECOCRAFT project complements this with a wealth of independent plant physiological measurements. Thus, it was aimed in this study to test six process-based forest growth models against the flux measurements of six European forest types, taking advantage of a large database with plant physiological parameters.The reliability of both the flux data and parameter values itself was not under discussion in this study. The data provided by the researchers of the EUROFLUX sites, possibly with local corrections, were used with a minor gap-filling procedure to avoid the loss of many days with observations.The model performance is discussed based on their accuracy, generality and realism. Accuracy was evaluated based on the goodness-of-fit with observed values of daily net ecosystem exchange, gross primary production and ecosystem respiration (gC m(-2) d(-1) ), and transpiration (kg H-2 O m(-2) d(-1) ). Moreover, accuracy was also evaluated based on systematic and unsystematic errors. Generality was characterized by the applicability of the models to different European forest ecosystems. Reality was evaluated by comparing the modelled and observed responses of gross primary production, ecosystem respiration to radiation and temperature. The results indicated that:Accuracy . All models showed similar high correlation with the measured carbon flux data, and also low systematic and unsystematic prediction errors at one or more sites of flux measurements. The results were similar in the case of several models when the water fluxes were considered. Most models fulfilled the criteria of sufficient accuracy for the ability to predict the carbon and water exchange between forests and the atmosphere.Generality. Three models of six could be applied for both deciduous and coniferous forests. Furthermore, four models were applied both for boreal and temperate conditions. However, no severe water-limited conditions were encountered, and no year-to-year variability could be tested.Realism. Most models fulfil the criterion of realism that the relationships between the modelled phenomena (carbon and water exchange) and environment are described causally. Again several of the models were able to reproduce the responses of measurable variables such as gross primary production (GPP), ecosystem respiration and transpiration to environmental driving factors such as radiation and temperature. Stomatalconductance appears to be the most critical process causing differences in predicted fluxes of carbon and water between those models that accurately describe the annual totals of GPP, ecosystem respiration and transpiration.As a conclusion, several process-based models are available that produce accurate estimates of carbon and water fluxes at several forest sites of Europe. This considerable accuracy fulfils one requirement of models to be able to predict the impacts of climate change on the carbon balance of European forests. However, the generality of the models should be further evaluated by expanding the range of testing over both time and space. In addition, differences in behaviour between models at the process level indicate requirement of further model testing, with special emphasis on modelling stomatal conductance realistically.

A new, controlled, environment facility for growing trees was built at Joensuu, Finland, between 1996 and 1998. It consists of four large rooms called dasotrons, with four large root pots in each. Each room is a separate unit, with independent control of air and soil temperature, air humidity and light. The environmental variables can be controlled to simulate conditions ranging from tropical to boreal. The controller set-points can be programmed locally or through a central control system running on a PC. The floor area and height of the rooms allows us to grow small trees (up to 3.7 m height) for several growing seasons. In each dasotron, there are four cylindrical pots with a removable upper section. There are access holes in the walls of the pots for the installation of sensors and minirhizotron tubes. Each pot has a drain, with valves, at the bottom to enable the removal of excess water or the collection of percolate samples. The operation of the facility was tested during one simulated annual growing cycle. During this test period, the dasotrons worked reliably and no systematic differences were found in the environmental conditions or in the growth of Norway spruce seedlings between the dasotrons. This new facility will enable diverse physiological and ecophysiological studies to be carried out on the responses of trees to their below- and above-ground environment.

An overview is presented of the phenological models relevant for boreal coniferous, temperate-zone deciduous and Mediterranean coniferous forest ecosystems. The phenology of the boreal forests is mainly driven by temperature, affecting the timing of the start of the growing season and thereby its duration, and the level of frost hardiness and thereby the reduction of foliage area and photosynthetic capacity by severe frost events. The phenology of temperate-zone forests is also mainly driven by temperature. Since temperate-zone forests are mostly mixed-species deciduous forests, differences in phenological response may affect competition between tree species. The phenology of Mediterranean coniferous forests is mainly driven by water availability, affecting the development of leaf area, rather than the timing of phenological events. These phenological models were subsequently coupled to the process-based forest model FORGRO to evaluate the effect of different climate change scenarios on growth. The results indicate that the phenology of each of the forest types significantly affects the growth response to a given climate change scenario. The absolute responses presented in this study should, however, be used with caution as there are still uncertainties in the phenological models, the growth models, the parameter values obtained and the climate change scenarios used. Future research should attempt to reduce these uncertainties. It is recommended that phenological models that describe the mechanisms by which seasonality in climatic drivers affects the phenological aspects of trees should be developed and carefully tested. Only by using such models may we make an assessment of the impact of climate change on the functioning and productivity of different forest ecosystems.