A mathematical optimisation model of a New Zealand dairy farm: The integrated dairy enterprise (IDEA) framework

Optimisation models are a key tool for the analysis of emerging policies, price sets, and technologies within grazing systems. A detailed nonlinear optimisation model of a New Zealand dairy farming system is described. The framework is notable for its rich portrayal of pasture and cow biology that add substantial descriptive power to standard approaches. Key processes incorporated in the model include: (1) pasture growth and digestibility that differ with residual pasture mass and rotation length, (2) pasture utilisation that varies by stocking rate, and (3) different levels of intake regulation. Model output is shown to closely match data from a more detailed simulation model (deviations between 0 and 5 per cent) and survey data (deviations between 1 and 11 per cent), providing confidence in its predictive capacity. Use of the model is demonstrated in an empirical application investigating the relative profitability of production systems involving different amounts of imported feed under price variation. The case study indicates superior profitability associated with the use of a moderate level of imported supplement, with Operating Profit ($NZ ha-1) of 934, 926, 1186, 1314, and 1093 when imported feed makes up 0, 5, 10, 20 and 30 per cent of the diet, respectively. Stocking rate and milk production per cow increase by 35 and 29 per cent, respectively, as the proportion of imported feed increases from 0 to 30 per cent of the diet. Pasture utilisation increases with stocking rate. Accordingly, pasture eaten and nitrogen fertiliser application increase by 20 and 213 per cent, respectively, as the proportion of imported feed increases from 0 to 30 per cent of the diet

Evaluating the Benefits of Restricted Grazing to Protect Wet Pasture Soils in Two Dairy Regions of New Zealand

Many dairy farms in the Manawatu and Southland regions of New Zealand have poorly drained soils that are prone to treading damage, an undesirable outcome on grazed pastures during the wetter months of the year. Removing cows to a stand-off pad during wet conditions can reduce damage, but incurs costs. The objective of this study was to evaluate the impact of different levels of restricted grazing (from 0 to 10 hours grazing time/day for lactating cows) on pasture yield, damage and wastage, feed and stand-off expenses, and farm operating profit. A simulated farm from each region was used in a farm systems model. This model simulated pasture-cow-management interactions, using site-specific climate data as inputs for the soil-pasture sub-models. Days to recover previous yield potential for damaged paddocks can vary widely. A sensitivity analysis (40 to 200 days to recover) was conducted to evaluate the effect of this parameter on results. Full protection when there is risk of damage (0 grazing hours/day) appeared to be less profitable compared with some level of grazing, because the advantages of reduced damage were outweighed by the disadvantages of managing infrequently grazed pastures. The differences in operating profit between full protection and some level of grazing became less as the recovery time increased, but for both regions grazing durations of 6-8 hours/day when a risk of damage is present appeared to be a sensible strategy irrespective of recovery time

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Cost-effective regulation of nonpoint emissions from pastoral agriculture: a stochastic analysis

Nutrient emissions from pastoral agriculture are a global cause of declining water quality. Their management is complicated through variability arising from climate and soil influences. This paper compares the implications of input-based policies and direct restrictions on leaching to achieve 10 and 20 per cent reductions in nitrogen (N) load, in the context of pasture-based New Zealand dairy farms. The most important mitigation practices on these farms are de-intensification (involving reductions in N fertiliser application and stocking rate) and the application of nitrification inhibitors. A stylised conceptual model, incorporating both sources of variability, is used to identify the implications of alternative policies. Direct restriction of estimated N leaching is the most cost-effective policy to reduce N leaching by 10 and 20 per cent. These results indicate the general insufficiency of input-based mechanisms for water quality improvement, given the low correlation between input use and leaching, possible substitution with unrestricted inputs and their failure to motivate the use of mitigation strategies. Additionally, model output indicates that inherent variability in water quality, mainly due to climate influences, can dominate the benefits of regulatory action in any given year

Cost-effective regulation of nonpoint emissions from pastoral agriculture: a stochastic analysis

Nutrient emissions from pastoral agriculture are a global cause of declining water quality. Their management is complicated through variability arising from climate and soil influences. This paper compares the implications of input-based policies and direct restrictions on leaching to achieve 10 and 20 per cent reductions in nitrogen (N) load, in the context of pasture-based New Zealand dairy farms. The most important mitigation practices on these farms are de-intensification (involving reductions in N fertiliser application and stocking rate) and the application of nitrification inhibitors. A stylised conceptual model, incorporating both sources of variability, is used to identify the implications of alternative policies. Direct restriction of estimated N leaching is the most cost-effective policy to reduce N leaching by 10 and 20 per cent. These results indicate the general insufficiency of input-based mechanisms for water quality improvement, given the low correlation between input use and leaching, possible substitution with unrestricted inputs and their failure to motivate the use of mitigation strategies. Additionally, model output indicates that inherent variability in water quality, mainly due to climate influences, can dominate the benefits of regulatory action in any given year

Detailed description of grazing systems using nonlinear optimisation methods: A model of a pasture-based New Zealand dairy farm

Grazing systems constitute the most extensive land use worldwide. However, economic analysis of these systems has mainly involved the use of linear optimisation methods that provide a general description of the complex processes contained therein. This paper describes a nonlinear optimisation model of a New Zealand dairy farm that incorporates a detailed depiction of key biophysical processes present within grazing systems. The capacity of this optimisation model to provide rich insight into the effects of higher stocking rates within grazing systems is demonstrated in an empirical application. In accordance with system trials, this application shows that higher stocking rates on pasture-based New Zealand dairy farms generally increase pre-grazing pasture biomass, decrease post-grazing pasture biomass, increase pasture utilisation, decrease herbage allowance, decrease intake and energy consumption per cow, decrease milk production per cow, increase milk production per ha, and reduce conception rate. Nevertheless, an intermediate stocking rate is optimal, as greater milk production with a higher stocking rate is not sufficient to offset the associated costs

An optimization model of a New Zealand dairy farm

Optimization models are a key tool for the analysis of emerging policies, prices, and technologies within grazing systems. A detailed, nonlinear optimization model of a New Zealand dairy farming system is described. This framework is notable for its inclusion of pasture residual mass, pasture utilization, and intake regulation as key management decisions. Validation of the model shows that the detailed representation of key biophysical relationships in the model provides an enhanced capacity to provide reasonable predictions outside of calibrated scenarios. Moreover, the flexibility of management plans in the model enhances its stability when faced with significant perturbations. In contrast, the inherent rigidity present in a less-detailed linear programming model is shown to limit its capacity to provide reasonable predictions away from the calibrated baseline. A sample application also demonstrates how the model can be used to identify pragmatic strategies to reduce greenhouse gas emissions