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    Soil methane (CH4) fluxes in cropland with permanent pasture and riparian buffer strips with different vegetation

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    Background Methane (CH4) has a global warming potential (GWP) 28 times that of carbon dioxide (CO2) over a 100-year horizon. Riparian buffers strips are widely implemented for their water quality protection functions along agricultural land, but conditions prevailing within them may increase the production of radiative greenhouse gases (GHGs), including CH4. However, a few information is available regarding the dynamics of unintended emissions of soil CH4 in these commonplace features of agroecosystems and how the dynamics compare with those for agricultural land. Aims To understand the dynamics of soil CH4 fluxes from a permanent upslope pasture and contiguous riparian buffer strips with different (grass, willow, and woodland) vegetation as well controls with no buffer vegetation, an experiment was carried out using the static chamber technique on a replicated plot-scale facility. Methods Gas fluxes were measured periodically with soil and environmental variables between June 2018 and February 2019 at North Wyke, UK. Results Soils under all treatments were sinks of soil CH4 with the willow riparian buffer (–2555 ± 318.7 g CH4 ha–1) having the lowest soil CH4 flux followed by the grass riparian buffer (–2532 ± 318.7 g CH4 ha–1), woodland riparian buffer (–2318.0 ± 246.4 g CH4 ha–1), no-buffer control (–1938.0 ± 374.4 g CH4 ha–1), and last, the upslope pasture (–1328.0 ± 89.0 g CH4 ha–1), which had a higher flux. Conclusions The three vegetated riparian buffers were more substantial soil CH4 sinks, suggesting that they may help reduce soil CH4 fluxes into the atmosphere in similar agroecosystems

    Floral enhancement of arable field margins increases moth abundance and diversity

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    Moth populations have declined across large parts of north-western Europe since the mid-20th century due, in part, to agricultural intensification. Agri-environment schemes (AES) are widely implemented across Europe to protect biodiversity in agricultural landscapes. Grass field margins enriched with wildflowers typically out-perform grass-only margins in terms of increasing insect abundance and diversity. However, the effect of wildflower enrichment on moths remains largely unstudied. Here, the relative importance of larval hostplants and nectar resources for adult moths within AES field margins are investigated. Two treatments and a control were compared: (i) a plain grass mix, the control, (ii) a grass mix enriched with only moth-pollinated flowers, and (iii) a grass mix enriched with 13 wildflower species. Abundance, species richness and Shannon diversity were up to 1.4, 1.8 and 3.5 times higher, respectively, in the wildflower treatment compared to plain grass. The difference in diversity between treatments became greater in the second year. There was no difference in total abundance, richness or diversity between the plain grass treatment and grass enriched with moth-pollinated flowers. The increase in abundance and diversity in the wildflower treatment was due primarily to the provision of larval hostplants, with nectar provision playing a smaller role. The relative abundance of species whose larval hostplants included sown wildflowers increased in the second year, suggesting colonisation of the new habitat. Implications for insect conservation. We show that, at the farm scale, moth diversity can be greatly enhanced and abundance moderately enhanced by sowing diverse wildflower margins, providing these insects with both larval hostplants and floral resources, compared to grass-only margins

    Management and Productivity of Key Integrated Crop-Livestock Systems in Uruguay: The Palo a Pique Long-Term Experiment’s Third Phase

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    Integrated Crop Livestock Systems (ICLSs) use productive diversification as a strategy to improve productivity and land use efficiency. Pasture Crop Rotations are a part of ICLSs and imply a pasture phase included in the sequence of crops. The main reasons to include pastures in crop systems are low productivity of natural grasslands and increased crop yield after a pasture phase. Our objective was to analyze the productivity indicators and management of four ICLSs that combine crop and livestock production, with data collected over a 3 y period (2019–2022). The experimental site was The Palo a Pique (Treinta y Tres, Uruguay) long-term experiment installed in 1995, located in the subtropical climate zone and on Oxyaquic Argiudolls soils (3% average slope). Systems evaluated were CC (continuous cropping), SR (two years idem CC, two years of pastures), LR (two years idem CC, four years of pastures) and FR (continuous pasture with Tall Fescue). Liveweight (LW) production, grain production and dry matter (DM) production were evaluated. Liveweight production was higher in CC and SR (426 and 418 kg LW/ha) than in LR (369 kg LW/ha) and FR (310 kg LW/ha). DM production was higher in FR and SR (6867 and 5763 kg DM/ha/year) than in LR (5399 kg DM/ha/year) and CC (5206 kg DM/ha/year). Grain production was 10%, 16% and 9% lower in soybean, wheat and sorghum in CC

    Modelling lifestyle changes in Insect endosymbionts, from insect mutualist to plant pathogen

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    Several insect endosymbionts have evolved to become plant pathogens, but the causes of this transition are currently unknown. In this paper, we use adaptive dynamics to develop hypotheses to explain why an insect endosymbiont would evolve to become a plant pathogen. We develop a model of facultative insect endosymbionts, capable of both vertical transmission within the insect population and horizontal transmission between insect and plant populations. We assume that an evolutionary trade-off between vertical and horizontal transmission exists. The transmission method of an endosymbiont is correlated with the nature of the symbiotic relationship between host and symbiont. We assume that vertical transmission represents an insect endosymbiont lifestyle and horizontal transmission represents a plant pathogen lifestyle. Our results suggest that temperature increases, increased agricultural intensification, disease dynamics within the plant host, insect mating system and change in the host plant of the insect may influence an evolutionary transition from an insect endosymbiont to a plant pathogen

    Agrochemicals interact synergistically to increase bee mortality

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    Global concern over widely documented declines in pollinators1,2,3 has led to the identification of anthropogenic stressors that, individually, are detrimental to bee populations4,5,6,7. Synergistic interactions between these stressors could substantially amplify the environmental effect of these stressors and could therefore have important implications for policy decisions that aim to improve the health of pollinators3,8,9. Here, to quantitatively assess the scale of this threat, we conducted a meta-analysis of 356 interaction effect sizes from 90 studies in which bees were exposed to combinations of agrochemicals, nutritional stressors and/or parasites. We found an overall synergistic effect between multiple stressors on bee mortality. Subgroup analysis of bee mortality revealed strong evidence for synergy when bees were exposed to multiple agrochemicals at field-realistic levels, but interactions were not greater than additive expectations when bees were exposed to parasites and/or nutritional stressors. All interactive effects on proxies of fitness, behaviour, parasite load and immune responses were either additive or antagonistic; therefore, the potential mechanisms that drive the observed synergistic interactions for bee mortality remain unclear. Environmental risk assessment schemes that assume additive effects of the risk of agrochemical exposure may underestimate the interactive effect of anthropogenic stressors on bee mortality and will fail to protect the pollinators that provide a key ecosystem service that underpins sustainable agriculture

    Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales

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    Weeds tend to aggregate in patches within fields, and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at various scales, the strength of the relations between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We developed a general method that uses novel within-field nested sampling and residual maximum-likelihood (reml) estimation to explore scale-dependent relations between weeds and soil properties. We validated the method using a case study of Alopecurus myosuroides in winter wheat. Using reml, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A.myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50m. Knowing how the variance was partitioned across the spatial scales, we optimised the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment

    Detecting chaotic dynamics of insect populations from long-term survey data

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    1. Estimates of the Lyapunov exponent, a statistic that measures the sensitive dependence of the dynamic behaviour of a system on its initial conditions, are used to characterize several sets of insect time series. 2. A new method is described to overcome the difficulty of defining the dynamics of an observed, noisy, short ecological time series. This method provides two test statistics for the estimated Lyapunov exponent. 3. This method is applied to forty-six time series comprising six aphid species from five sites and four moth species from six sites. There are few positive Lyapunov exponents and none is sufficiently large to characterize its time series as chaotic. 4. Two methods to estimate the Lyapunov exponent are compared; that based on logarithmically transformed counts yields less variable estimates for highly variable insect data than that based on untransformed counts


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