Publisher Correction: Artificial selection for improved energy efficiency is reaching its limits in broiler chickens.

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Artificial selection for improved energy efficiency is reaching its limits in broiler chickens.

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.

Quantifying the consequences of nutritional strategies aimed at decreasing phosphorus excretion from pig populations: a modeling approach.

There is a global imperative to reduce phosphorous (P) excretion from pig systems. In this study, a previously validated deterministic model was modified to be stochastic, in order to investigate the consequences of different management strategies on P excretion by a group of growing pigs. The model predicts P digestion, retention and excretion from feed composition and growth parameters that describe a specified pig phenotype. Stochasticity was achieved by introducing random variation in the latter. The strategies investigated were: (1) changing feed composition frequently in order to match more closely pig digestible P (digP) requirements to feed composition (phase feeding) and (2) grouping pigs into light and heavy groups and feeding each group according to the requirements of their group average BW (sorting). Phase feeding reduced P excretion as the number of feeding phases increased. The effect was most pronounced as feeding phases increased from 1 to 2, with a 7.5% decrease achieved; the increase in phases from 2 to 3 was associated with a further 2.0% reduction. Similarly, the effect was more pronounced when the feed targeted the population requirements for digP at the average BW of the first third, rather than the average requirements at the mid-point BW of each feeding sequence plan. Increasing the number of feeding phases increased the percentage of pigs that met their digP requirements during the early stages of growth and reduced the percentage of pigs that were supplied <85% of their digP requirements at any stage of their growth; the latter may have welfare implications. Sorting of pigs reduced P excretion to a lesser extent; the reduction was greater as the percentage of pigs in the light group increased from 10% to 30% (from 1.5% to 3.0% reduction, respectively). This resulted from an increase in the P excreted by the light group, accompanied by a decrease in the P excreted by the remaining pigs. Sorting increased the percentage of light pigs that met their dig P requirements, but only slightly decreased the percentage of heavy pigs that met these requirements at any point of their growth. Exactly the converse was the case as far as the percentage of pigs that were supplied <85% of their digP requirements were concerned. The developed model is flexible and can be used to investigate the effectiveness of other management strategies in reducing P excretion from groups of pigs, including precision livestock feeding.

Towards a methodology to formulate sustainable diets for livestock: accounting for environmental impact in diet formulation.

The objective of this study was to develop a novel methodology that enables pig diets to be formulated explicitly for environmental impact objectives using a Life Cycle Assessment (LCA) approach. To achieve this, the following methodological issues had to be addressed: (1) account for environmental impacts caused by both ingredient choice and nutrient excretion, (2) formulate diets for multiple environmental impact objectives and (3) allow flexibility to identify the optimal nutritional composition for each environmental impact objective. An LCA model based on Canadian pig farms was integrated into a diet formulation tool to compare the use of different ingredients in Eastern and Western Canada. By allowing the feed energy content to vary, it was possible to identify the optimum energy density for different environmental impact objectives, while accounting for the expected effect of energy density on feed intake. A least-cost diet was compared with diets formulated to minimise the following objectives: non-renewable resource use, acidification potential, eutrophication potential, global warming potential and a combined environmental impact score (using these four categories). The resulting environmental impacts were compared using parallel Monte Carlo simulations to account for shared uncertainty. When optimising diets to minimise a single environmental impact category, reductions in the said category were observed in all cases. However, this was at the expense of increasing the impact in other categories and higher dietary costs. The methodology can identify nutritional strategies to minimise environmental impacts, such as increasing the nutritional density of the diets, compared with the least-cost formulation.

The consequences of introducing stochasticity in nutrient utilisation models: the case of phosphorus utilisation by pigs.

Simulation models of nutrient utilisation ignore that variation in pig system components can influence the predicted mean and variance of the performance of a group of pigs. The objective of this study was to develop a methodology to investigate how variation in feed composition would (a) affect the outputs of a nutrient utilisation model and (b) interact with variation that arises from the traits of individual pigs. We used a P intake and utilisation model to address these characteristics. Introduction of stochasticity gave rise to a number of methodological challenges--for example, how to generate variation in both feed composition and pigs and account for correlations between ingredients when modelling variation associated with feed mixing efficiency. Introducing variation in feed composition and pig phenotype resulted in moderate decreases in mean digested, retained and excreted P predicted for a population of pigs and an increase in their associated CV. A lower percentage of pigs in the population were predicted to meet their requirements during the feeding period considered, by comparison with the no-variation scenario. Variation in feed ingredient composition contributed more to performance variation than variation due to mixing efficiency. When variations in both feed composition and pig traits were considered, it was the former rather than the latter that had the dominant influence on variability in pig performance. The developed framework emphasises the consequences of random variability on the predictions of nutrient utilisation models. Such consequences will have a significant impact on decisions about management strategies such as feeding that are subject to variation.

Potential environmental benefits of prospective genetic changes in broiler traits.

A system approach-based Life Cycle Assessment (LCA) framework, combined with a simple mechanistic model of bird energy balance was used to predict the potential effects of 15 y prospective broiler breeding on the environmental impacts of the standard UK broiler production system. The year 2014 Ross 308 genotype was used as a baseline, and a future scenario was specified from rates of genetic improvement predicted by the industry. The scenario included changes in the traits of growth rate (reducing the time to reach a target weight 2.05 kg from 34 d to 27 d), body lipid content, carcass yield, mortality and the number of chicks produced by a breeder hen. Diet composition was adjusted in order to accommodate the future nutrient requirements of the birds following the genetic change. The results showed that predicted changes in biological performance due to selective breeding could lead to reduced environmental impacts of the broiler production chain, most notably in the Eutrophication Potential (by 12%), Acidification Potential (by 10%) and Abiotic Resource Use (by 9%) and Global Warming Potential (by 9%). These reductions were mainly caused by the reduced maintenance energy requirement and thus lower feed intake, resulting from the shorter production cycle, together with the increased carcass yield. However, some environmental benefits were limited by the required changes in feed composition (e.g., increased inclusion of soy meal and vegetable oil) as a result of the changes in bird nutrient requirements. This study is the first one aiming to link the mechanistic animal modeling approach to predicted genetic changes in order to produce quantitative estimates of the future environmental impacts of broiler production. Although a more detailed understanding on the mechanisms of the potential changes in bird performance and their consequences on feeding and husbandry would be still be needed, the modeling framework produced in this study provides a starting point for predictions of the effects of prospective genetic progress.

Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems.

The objective of the study was to develop a life cycle assessment (LCA) for pig farming systems that would account for uncertainty and variability in input data and allow systematic environmental impact comparisons between production systems. The environmental impacts of commercial pig production for 2 regions in Canada (Eastern and Western) were compared using a cradle-to-farm gate LCA. These systems had important contrasting characteristics such as typical feed ingredients used, herd performance, and expected emission factors from manure management. The study used detailed production data supplied by the industry and incorporated uncertainty/variation in all major aspects of the system including life cycle inventory data for feed ingredients, animal performance, energy inputs, and emission factors. The impacts were defined using 5 metrics-global warming potential, acidification potential, eutrophication potential (EP), abiotic resource use, and nonrenewable energy use-and were expressed per kilogram carcass weight at farm gate. Eutrophication potential was further separated into marine EP (MEP) and freshwater EP (FEP). Uncertainties in the model inputs were separated into 2 types: uncertainty in the data used to describe the system (α uncertainties) and uncertainty in impact calculations or background data that affects all systems equally (ß uncertainties). The impacts of pig production in the 2 regions were systematically compared based on the differences in the systems (α uncertainties). The method of ascribing uncertainty influenced the outcomes. In eastern systems, EP, MEP, and FEP were lower (P < 0.05) when assuming that all uncertainty in the emission factors for leaching from manure application was ß. This was mainly due to increased EP resulting from field emissions for typical ingredients in western diets. When uncertainty in these emission factors was assumed to be α, only FEP was lower in eastern systems (P < 0.05). The environmental impacts for the other impact categories were not significantly different between the 2 systems, despite their aforementioned differences. In conclusion, a probabilistic approach was used to develop an LCA that systematically dealt with uncertainty in the data when comparing multiple environmental impacts measures in pig farming systems for the first time. The method was used to identify differences between Canadian pig production systems but can also be applied for comparisons between other agricultural systems that include inherent variation.

Modelling phosphorus intake, digestion, retention and excretion in growing and finishing pigs: model description.

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.

Modelling phosphorus intake, digestion, retention and excretion in growing and finishing pig: model evaluation.

A deterministic, dynamic model was developed, to enable predictions of phosphorus (P) digested, retained and excreted for different pig genotypes and under different dietary conditions. Before confidence can be placed on the predictions of the model, its evaluation was required. A sensitivity analysis of model predictions to ±20% changes in the model parameters was undertaken using a basal UK industry standard diet and a pig genotype characterized by British Society Animal Science as being of 'intermediate growth'. Model outputs were most sensitive to the values of the efficiency of digestible P utilization for growth and the non-phytate P absorption coefficient from the small intestine into the bloodstream; all other model parameters influenced model outputs by <10%, with the majority of the parameters influencing outputs by <5%. Independent data sets of published experiments were used to evaluate model performance based on graphical comparisons and statistical analysis. The literature studies were selected on the basis of the following criteria: they were within the BW range of 20 to 120 kg, pigs grew in a thermo-neutral environment; and they provided information on P intake, retention and excretion. In general, the model predicted satisfactorily the quantitative pig responses, in terms of P digested, retained and excreted, to variation in dietary inorganic P supply, Ca and phytase supplementation. The model performed well with 'conventional', European feed ingredients and poorly with 'less conventional' ones, such as dried distillers grains with solubles and canola meal. Explanations for these inconsistencies in the predictions are offered in the paper and they are expected to lead to further model development and improvement. The latter would include the characterization of the origin of phytate in pig diets.

The effects of welfare-enhancing system changes on the environmental impacts of broiler and egg production.

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.

Predicting the environmental impacts of chicken systems in the United Kingdom through a life cycle assessment: broiler production systems.

The aim of this study was to apply the life cycle assessment (LCA) method, from cradle to gate, to quantify the environmental burdens per 1,000 kg of expected edible carcass weight in the 3 main broiler production systems in the United Kingdom: 1) standard indoor, 2) free range, and 3) organic, and to identify the main components of these burdens. The LCA method evaluates production systems logically to account for all inputs and outputs that cross a specified system boundary, and it relates these to the useful outputs. The analysis was based on an approach that applied a structural model for the UK broiler industry and mechanistic submodels for animal performance, crop production, and major nutrient flows. Simplified baseline feeds representative of those used by the UK broiler industry were used. Typical UK figures for performance and mortality of birds and farm energy and material use were applied. Monte Carlo simulations were used to quantify the uncertainties in the outputs. The length of the production cycle was longer for free-range and organic systems compared with that of the standard indoor system, and as a result, the feed consumption and manure production per bird were higher in the free-range and organic systems. These differences had a major effect on the differences in environmental burdens between the systems. Feed production, processing, and transport resulted in greater overall environmental impacts than any other components of broiler production; for example, 65 to 81% of the primary energy use and 71 to 72% of the global warming potential of the system were due to these burdens. Farm gas and oil use had the second highest impact in primary energy use (12-25%) followed by farm electricity use. The direct use of gas, oil, and electricity were generally lower in free-range and organic systems compared with their use in the standard indoor system. Manure was the main component of acidification potential and also had a relatively high 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.

Predicting the environmental impacts of chicken systems in the United Kingdom through a life cycle assessment: egg production systems.

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.

Estimating stomatal conductance with thermal imagery.

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.

Soil temperature, gas exchange and nitrogen status of 5-year-old Norway spruce seedlings.

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 importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean forests ecosystems: an overview.

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.