What good is weed diversity? Storkey, J; Neve, P; Liebman, Matt
Weed research,
August 2018, Volume:
58, Issue:
4
Journal Article
Peer reviewed
Open access
Summary
Should the declining diversity of weed communities in conventionally managed arable fields be regarded as a problem? The answer to this question has tended to divide researchers into those ...whose primary focus is on conserving farmland biodiversity and those whose goals are dictated by weed control and maximising yield. Here, we argue that, regardless of how weeds are perceived, there are common ecological principles that should underpin any approach to managing weed communities, and, based on these principles, increasing in‐field weed diversity could be advantageous agronomically as well as environmentally. We hypothesise that a more diverse weed community will be less competitive, less prone to dominance by highly adapted, herbicide‐resistant species and that the diversity of the weed seedbank will be indicative of the overall sustainability of the cropping system. Common to these hypotheses is the idea that the intensification of agriculture has been accompanied by a homogenisation of cropping systems and landscapes, accounting for both declines in weed diversity and the reduced resilience of cropping systems (including the build‐up of herbicide resistance). As such, weed communities represent a useful indicator of the success of rediversifying systems at multiple scales, which will be a central component of making agriculture and weed control more sustainable.
Weeds have an important role in maintaining farmland biodiversity. This needs to be balanced with their potential negative impact on crop yield and quality. Mechanistic models of crop-weed ...competition are an important tool in striking this balance. A range of common UK annual weeds were screened for the eco-physiological traits required by the models. Using multivariate techniques, a number of functional groups with a similar pattern of productivity and competition were identified, based on trade-offs between traits. A scheme was developed to assign species outside of the data set to one of the groups, based on life cycle, seed mass, maximum height and time of first flowering. As well as having a similar competitive ability, species within a group also appeared to have a similar ecosystem function, in terms of supporting higher trophic groups. Two beneficial groups of species were identified that combined a relatively low competitive ability with a high importance for invertebrates and birds. The identification of functional groups in the UK arable flora is a useful tool for assessing a weed community in the context of reconciling biodiversity provision with crop production. Preserving beneficial plant functional types within the crop would complement non-cropped wildlife refuges, such as field margins.
Meta-Learning in Neural Networks: A Survey Hospedales, Timothy; Antoniou, Antreas; Micaelli, Paul ...
IEEE transactions on pattern analysis and machine intelligence,
09/2022, Volume:
44, Issue:
9
Journal Article
Peer reviewed
Open access
The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent years. Contrary to conventional approaches to AI where tasks are solved from scratch using a fixed ...learning algorithm, meta-learning aims to improve the learning algorithm itself, given the experience of multiple learning episodes. This paradigm provides an opportunity to tackle many conventional challenges of deep learning, including data and computation bottlenecks, as well as generalization. This survey describes the contemporary meta-learning landscape. We first discuss definitions of meta-learning and position it with respect to related fields, such as transfer learning and hyperparameter optimization. We then propose a new taxonomy that provides a more comprehensive breakdown of the space of meta-learning methods today. We survey promising applications and successes of meta-learning such as few-shot learning and reinforcement learning. Finally, we discuss outstanding challenges and promising areas for future research.
The negative effect of increasing atmospheric nitrogen (N) pollution on grassland biodiversity is now incontrovertible. However, the recent introduction of cleaner technologies in the UK has led to ...reductions in the emissions of nitrogen oxides, with concomitant decreases in N deposition. The degree to which grassland biodiversity can be expected to 'bounce back' in response to these improvements in air quality is uncertain, with a suggestion that long-term chronic N addition may lead to an alternative low biodiversity state. Here we present evidence from the 160-year-old Park Grass Experiment at Rothamsted Research, UK, that shows a positive response of biodiversity to reducing N addition from either atmospheric pollution or fertilizers. The proportion of legumes, species richness and diversity increased across the experiment between 1991 and 2012 as both wet and dry N deposition declined. Plots that stopped receiving inorganic N fertilizer in 1989 recovered much of the diversity that had been lost, especially if limed. There was no evidence that chronic N addition has resulted in an alternative low biodiversity state on the Park Grass plots, except where there has been extreme acidification, although it is likely that the recovery of plant communities has been facilitated by the twice-yearly mowing and removal of biomass. This may also explain why a comparable response of plant communities to reduced N inputs has yet to be observed in the wider landscape.
The impact of crop management and agricultural land use on the threat status of plants adapted to arable habitats was analysed using data from Red Lists of vascular plants assessed by national ...experts from 29 European countries. There was a positive relationship between national wheat yields and the numbers of rare, threatened or recently extinct arable plant species in each country. Variance in the relative proportions of species in different threat categories was significantly explained using a combination of fertilizer and herbicide use, with a greater percentage of the variance partitioned to fertilizers. Specialist species adapted to individual crops, such as flax, are among the most threatened. These species have declined across Europe in response to a reduction in the area grown for the crops on which they rely. The increased use of agro-chemicals, especially in central and northwestern Europe, has selected against a larger group of species adapted to habitats with intermediate fertility. There is an urgent need to implement successful conservation strategies to arrest the decline of this functionally distinct and increasingly threatened component of the European flora.
Competitive crop cultivars offer a potentially cheap option to include in integrated weed management strategies (IWM). Although cultivars with high competitive potential have been identified amongst ...cereal crops, competitiveness has not traditionally been considered a priority for breeding or farmer cultivar choice. The challenge of managing herbicide‐resistant weed populations has, however, renewed interest in cultural weed control options, including competitive cultivars. We evaluated the current understanding of the traits that explain variability in competitive ability between cultivars, the relationship between suppression of weed neighbours and tolerance of their presence and the existence of trade‐offs between competitive ability and yield in weed‐free scenarios. A large number of relationships between competitive ability and plant traits have been reported in the literature, including plant height, speed of development, canopy architecture and partitioning of resources. There is uncertainty over the relationship between suppressive ability and tolerance, although tolerance is a less stable trait over seasons and locations. To realise the potential of competitive crop cultivars as a tool in IWM, a quick and simple‐to‐use protocol for assessing the competitive potential of new cultivars is required; it is likely that this will not be based on a single trait, but will need to capture the combined effect of multiple traits. A way needs to be found to make this information accessible to farmers, so that competitive cultivars can be better integrated into their weed control programmes.
Glyphosate, the most widely used herbicide, is linked with environmental harm and there is a drive to replace it in agricultural systems. We model the impacts of discontinuing glyphosate use and ...replacing it with cultural control methods. We simulate winter wheat arable systems reliant on glyphosate and typical in northwest Europe. Removing glyphosate was projected to increase weed abundance, herbicide risk to the environment, and arable plant diversity and decrease food production. Weed communities with evolved resistance to non-glyphosate herbicides were not projected to be disproportionately affected by removing glyphosate, despite the lack of alternative herbicidal control options. Crop rotations with more spring cereals or grass leys for weed control increased arable plant diversity. Stale seedbed techniques such as delayed drilling and choosing ploughing instead of minimum tillage had varying effects on weed abundance, food production, and profitability. Ploughing was the most effective alternative to glyphosate for long-term weed control while maintaining production and profit. Our findings emphasize the need for careful consideration of trade-offs arising in scenarios where glyphosate is removed. Integrated Weed Management (IWM) with more use of cultural control methods offers the potential to reduce chemical use but is sensitive to seasonal variability and can incur negative environmental and economic impacts.
Abstract To date, there are no reliable markers for predicting onset of schizophrenia in individuals at high risk (HR). Substantial promise is, however, shown by a variety of pattern classification ...approaches to neuroimaging data. Here, we examined the predictive accuracy of support vector machine (SVM) in later diagnosing schizophrenia, at a single-subject level, using a cohort of HR individuals drawn from multiply affected families and a combination of neuroanatomical, schizotypal and neurocognitive variables. Baseline structural magnetic resonance imaging (MRI), schizotypal and neurocognitive data from 17 HR subjects, who subsequently developed schizophrenia and a matched group of 17 HR subjects who did not make the transition, yet had psychotic symptoms, were included in the analysis. We employed recursive feature elimination (RFE), in a nested cross-validation scheme to identify the most significant predictors of disease transition and enhance diagnostic performance. Classification accuracy was 94% when a self-completed measure of schizotypy, a declarative memory test and structural MRI data were combined into a single learning algorithm; higher than when either quantitative measure was used alone. The discriminative neuroanatomical pattern involved gray matter volume differences in frontal, orbito-frontal and occipital lobe regions bilaterally as well as parts of the superior, medial temporal lobe and cerebellar regions. Our findings suggest that an early SVM-based prediction of schizophrenia is possible and can be improved by combining schizotypal and neurocognitive features with neuroanatomical variables. However, our predictive model needs to be tested by classifying a new, independent HR cohort in order to estimate its validity.
Several theories propose that the cortex implements an internal model to explain, predict, and learn about sensory data, but the nature of this model is unclear. One condition that could be highly ...informative here is Charles Bonnet syndrome (CBS), where loss of vision leads to complex, vivid visual hallucinations of objects, people, and whole scenes. CBS could be taken as indication that there is a generative model in the brain, specifically one that can synthesise rich, consistent visual representations even in the absence of actual visual input. The processes that lead to CBS are poorly understood. Here, we argue that a model recently introduced in machine learning, the deep Boltzmann machine (DBM), could capture the relevant aspects of (hypothetical) generative processing in the cortex. The DBM carries both the semantics of a probabilistic generative model and of a neural network. The latter allows us to model a concrete neural mechanism that could underlie CBS, namely, homeostatic regulation of neuronal activity. We show that homeostatic plasticity could serve to make the learnt internal model robust against e.g. degradation of sensory input, but overcompensate in the case of CBS, leading to hallucinations. We demonstrate how a wide range of features of CBS can be explained in the model and suggest a potential role for the neuromodulator acetylcholine. This work constitutes the first concrete computational model of CBS and the first application of the DBM as a model in computational neuroscience. Our results lend further credence to the hypothesis of a generative model in the brain.
The intensification of crop management in the U.K. over the past 60 years has resulted in the decline of the populations of a number of annual plant species adapted to arable habitats. In contrast, ...other species continue to be common as arable weeds. A community assembly approach was taken to explain these recent changes in the weed flora using databases of plant functional traits, a pot experiment, and weed surveys of the Broadbalk long-term experiment. The hypothesis was tested that species that have been selected against by increased fertilizer inputs and herbicide use share an adverse combination of traits. An analysis comparing the combination of maximum height, seed weight, and time of first flowering of 29 common and 32 rare or threatened U.K. autumn weeds established that rare or threatened species occupied an area of trait space that was distinct from the common species. A rare weed trait syndrome of short stature, large seed, and late flowering was identified. The theory that species with a trait syndrome that is currently unfavorable are better adapted for less fertile environments was supported by the pot experiment. Species with a combination of short stature and large seed had a relatively greater competitive ability in low compared to high fertility treatments. Analysis of survey data from the Broadbalk long-term experiment confirmed that, as N inputs increased, the abundance of the two functional groups that contained only common species remained stable or increased; whereas, the groups dominated by rare or threatened species declined as fertility increased. An understanding of the response traits of arable plants to management filters, including fertilizer inputs and herbicide, is valuable for designing conservation strategies for rare species or predicting future shifts in the functional diversity of weed communities including the potential for invasive species to establish.
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