Paul L. Mudge

Modelling carbon and water exchange of a grazed pasture in New Zealand constrained by eddy covariance measurements

We used two years of eddy covariance (EC) measurements collected over an intensively grazed dairy pasture to better understand the key drivers of changes in soil organic carbon stocks. Analysing grazing systems with EC measurements poses significant challenges as the respiration from grazing animals can result in large short-term CO2 fluxes. As paddocks are grazed only periodically, EC observations derive from a mosaic of paddocks with very different exchange rates. This violates the assumptions implicit in the use of EC methodology. To test whether these challenges could be overcome, and to develop a tool for wider scenario testing, we compared EC measurements with simulation runs with the detailed ecosystem model CenW 4.1. Simulations were run separately for 26 paddocks around the EC tower and coupled to a footprint analysis to estimate net fluxes at the EC tower. Overall, we obtained good agreement between modelled and measured fluxes, especially for the comparison of evapotranspiration rates, with model efficiency of 0.96 for weekly averaged values of the validation data. For net ecosystem productivity (NEP) comparisons, observations were omitted when cattle grazed the paddocks immediately around the tower. With those points omitted, model efficiencies for weekly averaged values of the validation data were 0.78, 0.67 and 0.54 for daytime, night-time and 24-hour NEP, respectively. While not included for model parameterisation, simulated gross primary production also agreed closely with values inferred from eddy covariance measurements (model efficiency of 0.84 for weekly averages). The study confirmed that CenW simulations could adequately model carbon and water exchange in grazed pastures. It highlighted the critical role of animal respiration for net CO2 fluxes, and showed that EC studies of grazed pastures need to consider the best approach of accounting for this important flux to avoid unbalanced accounting.

Changes in soil C, N and δ15N along three forest–pasture chronosequences in New Zealand

Changes in total soil carbon (C), nitrogen (N) and natural-abundance N isotopes (δ15N) were measured along three forest-to-pasture chronosequences on pumice soils in the Central North Island of New Zealand. On each of the three chronosequences, exotic pine forests had been converted to intensive dairy pastures 2–11 years before sampling and samples were also taken from remaining pine forests and long-term pastures (40–80 years old). The primary objective of the study was to test the hypothesis that surface-soil δ15N would increase over time following conversion of forest to pasture, due to greater N inputs and isotope-fractionating N losses (e.g. ammonia volatilisation) in pasture systems. Results supported our hypothesis, with linear regression revealing a significant (P < 0.001) positive correlation between log-transformed pasture age (log10[pasture age + 1]) and surface-soil δ15N. There was also a positive correlation (P < 0.001) between pasture age and total soil C and N, and a negative correlation of pasture age with C : N ratio. Surface-soil δ15N was also positively correlated (P < 0.001) with total soil N, and negatively correlated with C : N ratio when C : N was <13.6. These results suggested that as soils became more N-‘saturated’, isotope-fractionating N loss processes increased. Surface-soil δ15N in the pine forests was significantly less than subsoil δ15N, but there was no significant difference between the surface and subsoil in the long-term pastures, due to 15N enrichment of the surface soil. The difference in δ15N between the surface soil and subsoil may be a useful indicator of past land management, in addition to absolute δ15N values of surface soils.

Leaf economics spectrum-productivity relationships in intensively grazed pastures depend on dominant species identity.

Abstract Plant functional traits are thought to drive variation in primary productivity. However, there is a lack of work examining how dominant species identity affects trait–productivity relationships. The productivity of 12 pasture mixtures was determined in a 3‐year field experiment. The mixtures were based on either the winter‐active ryegrass (Lolium perenne) or winter‐dormant tall fescue (Festuca arundinacea). Different mixtures were obtained by adding forb, legume, and grass species that differ in key leaf economics spectrum (LES) traits to the basic two‐species dominant grass–white clover (Trifolium repens) mixtures. We tested for correlations between community‐weighted mean (CWM) trait values, functional diversity, and productivity across all plots and within those based on either ryegrass or tall fescue. The winter‐dormant forb species (chicory and plantain) had leaf traits consistent with high relative growth rates both per unit leaf area (high leaf thickness) and per unit leaf dry weight (low leaf dry matter content). Together, the two forb species achieved reasonable abundance when grown with either base grass (means of 36% and 53% of total biomass, respectively, with ryegrass tall fescue), but they competed much more strongly with tall fescue than with ryegrass. Consequently, they had a net negative impact on productivity when grown with tall fescue, and a net positive effect when grown with ryegrass. Strongly significant relationships between productivity and CWM values for LES traits were observed across ryegrass‐based mixtures, but not across tall fescue‐based mixtures. Functional diversity did not have a significant positive effect on productivity for any of the traits. The results show dominant species identity can strongly modify trait–productivity relationships in intensively grazed pastures. This was due to differences in the intensity of competition between dominant species and additional species, suggesting that resource‐use complementarity is a necessary prerequisite for trait–productivity relationships.

The trade-offs between milk production and soil organic carbon storage in dairy systems under different management and environmental factors

A possible agricultural climate change mitigation option is to increase the amount of soil organic carbon (SOC). Conversely, some factors might lead to inadvertent losses of SOC. Here, we explore the effect of various management options and environmental changes on SOC storage and milk production of dairy pastures in New Zealand. We used CenW 4.1, a process-based ecophysiological model, to run a range of scenarios to assess the effects of changes in management options, plant properties and environmental factors on SOC and milk production. We tested the model by using 2years of observations of the exchanges of water and CO2 measured with an eddy covariance system on a dairy farm in New Zealands Waikato region. We obtained excellent agreement between the model and observations, especially for evapotranspiration and net photosynthesis. For the scenario analysis, we found that SOC could be increased through supplying supplemental feed, increasing fertiliser application, or increasing water availability through irrigation on very dry sites, but SOC decreased again for larger increases in water availability. Soil warming strongly reduced SOC. For other changes in key properties, such as changes in soil water-holding capacity and plant root:shoot ratios, SOC changes were often negatively correlated with changes in milk production. The work showed that changes in SOC were determined by the complex interplay between (1) changes in net primary production; (2) the carbon fraction taken off-site through grazing; (3) carbon allocation within the system between labile and stabilised SOC; and (4) changes in SOC decomposition rates. There is a particularly important trade-off between carbon either being removed by grazing or remaining on site and available for SOC formation. Changes in SOC cannot be fully understood unless all four factors are considered together in an overall assessment.

A review of soil carbon change in New Zealand’s grazed grasslands

ABSTRACT Soil organic matter is a potential sink of atmospheric carbon (C) and critical for maintaining soil quality. We reviewed New Zealand studies of soil C changes after conversion from woody vegetation to pasture, and under long-term pasture. Soil C increased by about 13.7 t C ha−1 to a new steady state when forests were initially converted to pasture. In the last 3–4 decades, resampling of soil profiles demonstrated that under long-term pasture on flat land, soil C had subsequently declined for allophanic, gley and organic soils by 0.54, 0.32 and 2.9 t C ha−1 y−1, respectively, and soil C had not changed in the remainder of sampled soil orders. For the same time period, pasture soils on stable midslopes of hill country gained 0.6 t C ha−1 y−1. Whether these changes are ongoing is not known, except for the organic soils where losses will continue so long as they are drained. Phosphorus fertiliser application did not change C stocks. Irrigation decreased carbon by 7 t C ha−1. Carbon losses during pasture renewal ranged between 0.8 and 4.1 t C ha−1. Some evidence suggests tussock grasslands can gain C when fertilised and not overgrazed. When combined to the national scale, different data sets suggest either no change or a gain of C, but with large uncertainties. We highlight key land-use practices and soil orders that require further information of soil C stock changes and advocate for a better understanding of underpinning reasons for changes in soil C.

Changes in soil total C and N contents at three chronosequences after conversion from plantation pine forest to dairy pasture on a New Zealand Pumice soil

The large amounts of carbon (C) and nitrogen (N) sequestered as organic matter in soils have implications for global and national C and N balances and greenhouse gas emissions. Changes in soil management can affect the amount of C and N stored in soil. We investigated the change in land use from radiata pine plantation to ryegrass–white clover dairy pasture on the total C and N content of Taupo Pumice Soil. Samples were taken at three study sites (Atiamuri, Tokoroa and Wairakei) in North Island, New Zealand. Soils were cored to 60 cm depth and subsampled by soil horizon, and bulk density cores were taken from soil pits. A chronosequence of sites was obtained after conversion from pines to pasture. Long-term pastures (40–80 years) and mature pine plantations were included for further comparison. Regression analyses were completed after logarithmic transformation of the time data. The data were highly variable, but significant (P < 0.05) increases in total C and N were found at the Atiamuri and Wairakei sites. However, there was no significant change in the total C content of the profile at the Tokoroa site. Increases in total C and N were greatest in the Ap horizon and were most rapid 1–5 years after conversion. Overall rates of increase in the first 10 years after conversion were 0.167 kg C m–2 year–1 for total C and 0.032 kg N m–2 year–1 for total N, dropping to 0.027 kg C and 0.005 kg N m–2 year–1 for the 10–50-year period. The change in land use from plantation forest to dairy pasture has resulted in a moderate increase or no change in soil storage of C. Compared with total C, increases in total N storage were proportionately greater in all three examples of this Taupo Pumice Soil.

Combining field experiments and predictive models to assess potential for increased plant diversity to climate-proof intensive agriculture

Abstract Agricultural production systems face increasing threats from more frequent and extreme weather fluctuations associated with global climate change. While there is mounting evidence that increased plant community diversity can reduce the variability of ecosystem functions (such as primary productivity) in the face of environmental fluctuation, there has been little work testing whether this is true for intensively managed agricultural systems. Using statistical modeling techniques to fit environment–productivity relationships offers an efficient means of leveraging hard‐won experimental data to compare the potential variability of different mixtures across a wide range of environmental contexts. We used data from two multiyear field experiments to fit climate–soil–productivity models for two pasture mixtures under intensive grazing—one composed of two drought‐sensitive species (standard), and an eight‐species mixture including several drought‐resistant species (complex). We then used these models to undertake a scoping study estimating the mean and coefficient of variation (CV) of annual productivity for long‐term climate data covering all New Zealand on soils with low, medium, or high water‐holding capacity. Our results suggest that the complex mixture is likely to have consistently lower CV in productivity, irrespective of soil type or climate regime. Predicted differences in mean annual productivity between mixtures were strongly influenced by soil type and were closely linked to mean annual soil water availability across all soil types. Differences in the CV of productivity were only strongly related to interannual variance in water availability for the lowest water‐holding capacity soil. Our results show that there is considerable scope for mixtures including drought‐tolerant species to enhance certainty in intensive pastoral systems. This provides justification for investing resources in a large‐scale distributed experiment involving many sites under different environmental contexts to confirm these findings.