A global FAOSTAT reference database of cropland nutrient budgets and nutrient use efficiency (1961–2020): nitrogen, phosphorus and potassium

Nutrient budgets help to identify the excess or insufficient use of fertilizers and other nutrient sources in agriculture. They allow for the calculation of indicators, such as the nutrient balance (surplus if positive or deficit if negative) and nutrient use efficiency, that help to monitor agricultural productivity and sustainability across the world. We present a global database of country-level budget estimates for nitrogen (N), phosphorus (P) and potassium (K) on cropland. The database, disseminated in FAOSTAT, is meant to provide a global reference, synthesizing and continuously updating the state of the art on this topic. The database covers 205 countries and territories, as well as regional and global aggregates, for the period from 1961 to 2020. Results highlight the wide range in nutrient use and nutrient use efficiencies across geographic regions, nutrients, and time. The average N balance on global cropland has remained fairly steady at about 50–55 kg ha-1 yr-1 during the past 15 years, despite increasing N inputs. Regional trends, however, show recent average N surpluses that range from a low of about 10 kgNha-1 yr-1 in Africa to more than 90 kgNha-1 yr-1 in Asia. Encouragingly, average global cropland N use efficiency decreased from about 59% in 1961 to a low of 43% in 1988, but it has risen since then to a level of 55 %. Phosphorus deficits are mainly found in Africa, whereas potassium deficits occur in Africa and the Americas. This study introduces improvements over previous work in relation to the key nutrient coefficients affecting nutrient budgets and nutrient use efficiency estimates, especially with respect to nutrient removal in crop products, manure nutrient content, atmospheric deposition and crop biological N fixation rates. We conclude by discussing future research directions and highlighting the need to align statistical definitions across research groups as well as to further refine plant and livestock coefficients and expand estimates to all agricultural land, including nutrient flows in meadows and pastures. Further information is available from https://doi.org/10.5061/dryad.hx3ffbgkh (Ludemann et al., 2023b) as well as the FAOSTAT database (https:// www.fao.org/faostat/en/#data/ESB; FAO, 2022a) and is updated annually

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.info:eu-repo/semantics/acceptedVersio

Estimated Annual Value of a Forage Cultivar Selection Decision Tool for New Zealand Sheep and Beef Farmers

In 2011, the New Zealand dairy industry developed a forage cultivar selection decision support tool called the DairyNZ Forage Value Index (FVI). Since then, there has been considerable interest shown in development of a FVI-type cultivar evaluation system for the New Zealand sheep and beef industry. The New Zealand Pastoral Industry Forage Strategy for example recommended actions to develop a FVI for the sheep and beef industry and to have closer collaboration between the sheep and beef industry, the dairy industry and the New Zealand Plant Breeding and Research Association. This is unsurprising since the dairy industry estimated the value of the benefits of the DairyNZ FVI as approximately $NZ160 million each year. The present study provides a cost benefit analysis of a forage cultivar selection decision support tool (DST) across the New Zealand sheep and beef industry. The analysis was performed using a nitrogen fertiliser/barley replacement cost method to estimate the value of forage dry matter. The value of sheep and beef farmers choosing 5 star rated cultivars of perennial ryegrass compared to 3 or 1 star rated cultivars was extrapolated to the eight Beef + Lamb NZ Farm Classes and to the whole sheep and beef industry. Multiple scenarios were examined to assess the net present value and modified internal rate of return of investment in the DST. These scenarios reflected differences in assumed rates of adoption over a 10-year period and differences in implementation costs. The modified internal rate of return over a 10-year period was estimated to range between 27 and 62 per cent depending on whether an annual cost of the DST was assumed to be$NZ0.5 million or $NZ1 million under the adoption scenarios considered. The NPV ranged between$NZ6 million and $NZ45 million. This highlights the potential value of improved farmer selection of ryegrass cultivars through a cultivar selection DST in a sheep and beef context in New Zealand

ludemannc/fao_cnb: FAO cropland nutrient budget analysis

<p>Data and code used for creating Cropland Nutrient Budget (1961-2020) related figures and tables in the Ludemann et al Earth Systems Science Data article available at: https://doi.org/10.5194/essd-2023-206.</p&gt

Is increasing ewe prolificacy the key to increasing Canterbury dry land farm profitability? Research using linear programming as a modelling tool

The sheep industry contributed $3.47 billion in export earnings for New Zealand in 2007. Canterbury produced 22.6% of the lambs born in the 2007/08 season, making it a significant region for lamb production. Increasing ewe prolificacy (EP) has been a trend over the last 24 years to aid the industry’s productivity to maintain economic sustainability. Previous research suggested that increasing ewe prolificacy could result in lower overall profitability to farms. However, none had related it specifically to Canterbury conditions. This research involved the development of a Linear Program to relate ewe prolificacy to net profits and biological efficiency of a typical Canterbury dry land sheep and beef farm. Profits and biological efficiency were maximised at 190% and 208% EP respectively. Thereafter, profits and efficiencies reduced with increasing EP. Ewe prolificacy was the main driver of profitability when EP was between 129-190%. Survival rates of triplet and quadruplet lambs became more influential as EP increased, and allowed the biological efficiency to continue to increase (above 208% EP) when they were increased to that of twin lambs. The stated optimal ewe prolificacy levels related specifically to Canterbury dry land conditions and ‘average’ lamb performance in terms of survival and live weight gains. Further research and technology could help to improve these performance measures to increase the optimal ewe prolificacy. Limitations and advantages of the Linear Program model as a farmer / consultant decision making tool were also discussed

Assessing the value of novel perennial ryegrasses (Lolium perenne L.) for the Australian dairy industry

© 2015 Dr. Cameron Ian LudemannThe value of increasing the metabolizable energy (ME) concentration of grass using a genetically modified high-fructan perennial ryegrass (Lolium perenne L.)(‘GM ryegrass’), was assessed in this thesis. This included: an assessment of the expression of the fructan trait and effects on rumen fluid chemistry (in vitro), simulating potential profitability and greenhouse gas (GHG) emission effects on-farm, and the scale and distribution of benefits from changing the ME concentration of perennial ryegrass to the Australian dairy supply chain. The GM ryegrass was associated with an increase in herbage dry matter (DM) energy concentration between 0.8 megajoules (MJ) and 1.74 MJ of ME per kilogram (kg) of DM. In vitro experiment results indicate increasing the concentration of fructan in the GM ryegrass did not adversely affect rumen pH or methane production. Two representative dairy farms (in Terang in south-west Victoria and in Elliott in Tasmania) were used to provide context for the assessment of the value of increasing the ME concentration of perennial ryegrass herbage. Deterministic economic values, in Australian dollars (AUD) of AUD237/hectare(ha).year and AUD592/ha.year for a 1MJ/kg DM increase in pasture energy concentration were calculated using the replacement cost method for Terang and Elliott dairy farms respectively. Further economic modelling using a mechanistic pasture growth model was used to assess how farm operating profits (OP) changed when additional energy from the GM ryegrass was utilized through various management practices. Results indicate even greater changes in OP could be achieved compared to the replacement cost method if energy was utilized with greater milk production per cow. When energy was utilized through greater milk production per cow a 1MJ/kg DM increase in energy concentration was associated with an AUD482/ha.year mean increase in OP in Terang and a AUD783/ha.year increase for Elliott. Dilution of GHG emissions across the additional milk produced from cows consuming the GM ryegrass was estimated to reduce GHG emissions intensity (EI) of milk by 10% in Terang and 13% in Elliott compared to the Base Scenario. Mean total benefits to the Australian dairy supply chain from adoption of the GM ryegrass based on a 1MJ increase in energy concentration were estimated between AUD205 million and AUD300 million (as a net present value) over a 15 year period. This study also provides sensitivity analysis of the results to changes in key assumptions such as the rates of adoption and elasticities. Estimations of benefit at the Australian dairy supply chain level were calculated using an equilibrium displacement model assuming a 10% discount rate and farmers who adopted the GM ryegrass (‘adopter’ farmers) renovated 10% of their farm area into the GM ryegrass. Australian consumers were estimated to receive most (70%) benefit from farmer adoption of the GM ryegrass, followed by farmers and suppliers of the seed technology (26%). Benefits suppliers of the seed technology receive will depend on how the GM ryegrass is licensed, competition amongst seed companies, and how rapidly farmers adopt the GM ryegrass. Results from this thesis therefore supports the hypothesis that increasing expression of fructan concentration in perennial ryegrass could increase the energy concentration of herbage DM to provide significant increases in OP and reductions in GHG EI for farmers who adopt the technology. Results also provide valuable information for decision-makers for allocating appropriate resources toward deregulation of this GM ryegrass

The profitability of improving lambing percentages

Increasing ewe lambing percentages has the potential to improve farm profitability. However this depends on the level of fertility already being achieved by the ewes, the level of survival of the lambs as well as the lamb selling strategy that is implemented. Farmers need to carefully consider the implications of whether or not to focus on improving ewe fertility further

PigEV - a new tool to derive economic values for pigs

The breeding objective defines the selection emphasis placed on individual traits based on the economic importance of each trait. In PIGBLUP, the $Index defines the breeding objective based on the profit function developed by Stewart et al. (1990). The profit function was based on two main equations quantifying a sow herd sub-objective (SHSO) and a growing-finishing sub-objective (GFSO). Information required in the PIGBLUP$Index module included economic inputs outlining payment details and cost structures, performance levels in key characteristics of pig production and marketing weighting as outlined by Long (1991) during an earlier AGBU Pig Genetics Workshop. The number of traits considered in genetic evaluations has increased over time and the bio-economic model developed by de Vries (1989) was used by Cameron and Crump (1999) to derive economic weights for the main performance traits based on production and market parameters relevant for Australian conditions at the time. However, breeders require greater flexibility in the setup of company-specific breeding objectives for a wider range of traits. This need has now been met by the development of PigEV which is a tool that allows users to define breeding objectives in pigs using their own input parameters in regard to cost structures, performance and marketing information