Robyn Dynes

Farmer's intended and actual adoption of climate change mitigation and adaptation strategies

A growing body of work aims to understand the impacts of climate change on agriculture as well as farmer’s perceptions of climate change and their likeliness to adopt adapting and mitigating behaviors. Despite this, little work has considered how intention to adopt differs from actual adoption of climate change practices in agriculture. Applying the Theory of Planned Behavior we aim to assess whether different factors affect intended versus actual adoption of climate behaviors among farmers in New Zealand. Data were collected through mixed methods (37 interviews and a telephone survey of 490 farmers) in two regions of New Zealand 2010–2012. Through multiple regression models we test hypotheses related to the Theory of Planned Behavior around the role of attitudes, subjective norms, and perceived capacity in affecting intended and actual adoption. Results suggest that there are different drivers of intended and actual adoption of climate change practices. Climate change attitudes and belief is only associated with intended not actual adoption. We find no evidence that subjective norms (climate change policy support) significantly influence either intention or actual adoption. Only perceived capacity and self-efficacy were important predictors of both intended and actual adoption. These results suggest a disconnect between intended and actual behavior change and that using data about intention as a guiding factor for program and policy design may not be prudent. Furthermore, fostering perceived capacity and self-efficacy for individuals may be crucial for encouraging both intended and actual adoption of climate adapting and mitigating behaviors.

Pasture Monitoring from Polarimetric TerraSAR-X Data

Good pasture management and optimal feed use are key drivers of profitability for New Zealands pastoral dairy and meat industries. Preliminary results are reported on a study to evaluate TerraSAR-X dual-polarisation radar imagery for estimation of pasture biomass. At the time of writing, 4 out of 36 images have been acquired and processed. Several linear models have been tested for field-measured pasture biomass in terms of co- and cross-polarisation backscatter. The best model is a linear regression using the HH and HV sum and difference, resulting in a residual standard error of 191.4 (kg/ha), with no evidence of a date effect.

Robust estimation of pasture biomass using dual-polarisation TerrASAR-X imagery

The efficient management of pasture is a key driver of profitability for New Zealands pastoral dairy and meat industries. In this paper, we report results from a study that tests the viability of using short-wavelength imaging radar to estimate pasture biomass. We use images from the TerraSAR-X satellite, comparing the HH & HV and VV&HV dual-polarisation combinations. Several linear models have been tested for field-measured pasture biomass. The best model is a linear regression using backscatter from the HH&HV combination, resulting in a residual standard error of 317 kg/ha. This standard error is 61% less than the standard error for the VV&VH combination (511 kg/ha), which clearly suggests adopting the HH&HV model. A model for prediction of the pasture biomass rank percentile is somewhat less convincing than the model for the pasture biomass itself. Finally, a repeated measures analysis for the HH&HV pair, suggests invariance of the regression for pasture biomass over time, except for a possible outlier date 01 September 2008.

Feeding diets with fodder beet decreased methane emissions from dry and lactating dairy cows in grazing systems

Fodder beet (Beta vulgaris L.) has a very high readily fermentable carbohydrate concentration, which could affect rumen fermentation and reduce enteric methane (CH4) emissions. The objective of the current study was to estimate CH4 emissions from dry dairy cows grazing either fodder beet supplemented with perennial ryegrass (Lolium perenne L.)-dominated pasture silage (6 kg DM/cow/day; FB+Sil) or forage kale (Brassica oleracea L.) supplemented with barley (Hordeum vulgare L.) straw (3 kg DM/cow/day; kale+Str; dry cows, Experiment 1), and from dairy cows in early lactation grazing perennial ryegrass-dominated pasture alone (pasture) or supplemented with fodder beet bulbs (3 kg DM/cow/day; past+FB; lactating cows; Experiment 2). Methane measurements were performed using GreenFeed units (C-Lock Inc., Rapid City, SD, USA) for 40 days in August–September 2015 (Experiment 1) and for 22 days in November–December 2015 (Experiment 2), from 45 and 31 Holstein–Friesian × Jersey dairy cows in Experiments 1 and 2, respectively. Dry cows grazing FB+Sil in Experiment 1 produced 18% less CH4 (g/day) and had 28% lower CH4 yield (g/kg DM intake; P < 0.001) than did cows grazing kale+Str. Lactating cows grazing past+FB in Experiment 2 produced 18% less CH4 and had 16% lower CH4 intensity (g/kg fat and protein-corrected milk production; P < 0.01) than did cows grazing pasture alone, while milk production and composition were similar for the two groups. In conclusion, feeding fodder beet at ~50% and 20% of the diet of dry and lactating dairy cows in pastoral systems can mitigate CH4 emissions.

Nitrous oxide emissions from cattle urine deposited onto soil supporting a winter forage kale crop

ABSTRACT Wintering cows on forage crops leads to urine being excreted onto wet, compacted soils, which can result in significant emissions of nitrous oxide (N2O). A field trial was conducted to determine the N2O emission factor (EF3; proportion of urine-N lost as N2O-N) for dairy cows wintered on a kale forage crop on a poorly drained soil. Urine was collected from non-lactating dairy cows on a forage kale diet and applied at 550 kg N ha−1 to artificially compacted soil to simulate trampling and non-compacted soil in a kale field. Cumulative N2O losses over four months were 7.38 and 2.64 kg N2O-N ha−1 from urine applied to, respectively, compacted and non-compacted soil. The corresponding EF3 values 0.75% and 0.30%, respectively, differed (P = .003) due to compaction. Combining our results with previous studies, where brassica-fed livestock urine was applied to soils supporting a forage brassica crop, suggested a significant relationship between soil water-filled pore space (WFPS) and brassica-derived urine EF3 (P = .005).

Fodder quality and intake by dairy cows. 1. Preference for oaten hays

This work was undertaken to determine whether measurement of preference 30 min after alternative hays are offered to lactating dairy cows adequately predicts preference over a 3-day period and to determine the influence of the concentrations of water-soluble carbon (WSC) and neutral detergent fibre (NDF) of hays on preference. Eleven test hays were chosen to provide an NDF concentration of between 45% and 60% and a WSC concentration of between 10% and 30%. The test hays were each offered to lactating dairy cows as an alternative choice, with two control hays with NDF concentrations of 49% and 54%. A replicated Latin-square design was used to determine the preference of cows for the test hays, using three cows for each test hay versus control-hay comparison. Preference measured 30 min after hays were offered to cows was highly correlated with measures of preference made after 24 h and again for the same measures on the third day of the hays being offered. However, preference measures with the two different control hays were not well related, thus indicating that preference values are control-hay specific. Total hay intake was unchanged with the low-NDF control hay but declined with increasing NDF concentration of the test hays with the higher-NDF control hay. WSC did not influence preference at any one level of NDF of the test hays when the control hay had a low NDF concentration, but there was a small rise in preference at each NDF level when the control hay had a higher NDF concentration. This may have been a result of a contribution of WSC to digestibility as much as to taste response. With the low-NDF control hay, drivers of preference were the NDF concentration and the digestibility of the hay, but with the higher-NDF control hay, the drivers were the NDF concentration and fibre characteristics (shear and potential fibre digestibility). Calculation of the NDF concentration of the total hay consumed, test plus control hays, suggested that a change in drivers of selection is likely at the point where the NDF concentration of the test hay equals that of the control hay. Unless models identifying selection drivers handle non-linear data, misleading results may be obtained.

A review of whole farm-system analysis in evaluating greenhouse-gas mitigation strategies from livestock production systems

Recognition is increasingly given to the need of improving agricultural production and efficiency to meet growing global food demand, while minimising environmental impacts. Livestock forms an important component of global food production and is a significant contributor to anthropogenic greenhouse-gas (GHG) emissions. As such, livestock production systems (LPS) are coming under increasing pressure to lower their emissions. In developed countries, LPS have been gradually reducing their emissions per unit of product (emissions intensity; EI) over time through improvements in production efficiency. However, the global challenge of reducing net emissions (NE) from livestock requires that the rate of decline in EI surpasses the productivity increases required to satisfy global food demand. Mechanistic and dynamic whole farm-system models can be used to estimate farm-gate GHG emissions and to quantify the likely changes in farm NE, EI, farm productivity and farm profitability as a result of applying various mitigation strategies. Such models are also used to understand the complex interactions at the farm-system level and to account for how component mitigation strategies perform within the complexity of these interactions, which is often overlooked when GHG mitigation research is performed only at the component level. The results of such analyses can be used in extension activities and to encourage adoption, increase awareness and in assisting policy makers. The present paper reviews how whole farm-system modelling has been used to assess GHG mitigation strategies, and the importance of understanding metrics and allocation approaches when assessing GHG emissions from LPS.

Methane and carbon dioxide emissions from lactating dairy cows grazing mature ryegrass/white clover or a diverse pasture comprising ryegrass, legumes and herbs

There is a growing interest in forage mixtures (Diverse pasture; e.g. containing grasses, legumes and herbs), especially those with a greater tolerance of dry conditions and a decreased nitrogen (N) content (reducing N losses), compared with ryegrass (Lolium perenne L and Lolium multiflorum L)/white clover (Trifolium repens L) pastures (RyeWC), which dominate New Zealand pastoral systems for dairy production. However, the effect of alternative forages on enteric methane (CH4) emissions is not known. The objective of the present trial was to compare CH4 emissions and milk production from dairy cows grazing either mature RyeWC or mature Diverse pasture (both approximately with pasture mass of 5600 kg DM/ha). The Diverse mixture comprised ryegrass, white clover, lucerne (Medicago sativa L), chicory (Cichorium intybus L) and plantain (Plantago lanceolata L). Milk production, measured from cows commencing at ~162 days of lactation, was less when cows grazed RyeWC than Diverse pastures (15.4 vs 16.7 kg/day; P < 0.001), whereas CH4 production (g/day) was similar for the respective treatments (411 g/day; P = 0.16). Milk composition was not affected by diet and CH4 intensity was similar for both diets (22 g/kg fat- and protein-corrected milk; P = 0.31). Methane yield [g/kg predicted dry matter intake (DMI)] averaged 22.6 and 24.9 for cows grazing RyeWC and Diverse pastures, respectively (P = 0.006). In conclusion, although the CH4 yield was greater when Diverse pasture was grazed, relative to RyeWC, there were no differences in emissions intensity or total CH4 emissions.

Collaborative Processes for Exploring Rural Futures: The Exploring Futures Platform

Collaborative approaches are becoming more common to help agriculture and rural communities navigate the range of complex issues they face. This article outlines the Exploring Futures Platform (EFP) process and critiques two case studies. EFP was developed for pastoral agriculture communities to help participants jointly define challenges and explore joint management of solutions for the future. EFP was designed to ensure successful integration of systems thinking and is built on transformational engagement, inclusion of diverse of views, delivery of real-time local data, building a system understanding, future focus, reflection and action. Lessons from the case studies using the EFP were to consider how researchers shape the discussion, make participants’ and researchers’ roles clear, ensure expectations of data and analysis presented are managed highlight the value of detailed case-studies identify the mandate for action from participants, build upon local knowledge, linking into local networks, and ensure continued future focus.