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      The contribution of spatial mass effects to plant diversity in arable fields

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          Abstract

          1. In arable fields, plant species richness consistently increases at field edges. This potentially makes the field edge an important habitat for the conservation of the ruderal arable flora (or ‘weeds’) and the invertebrates and birds it supports. Increased diversity and abundance of weeds in crop edges could be owing to either a reduction in agricultural inputs towards the field edge and/or spatial mass effects associated with dispersal from the surrounding landscape.

          2. We contend that the diversity of weed species in an arable field is a combination of resident species, that can persist under the intense selection pressure of regular cultivation and agrochemical inputs (typically more ruderal species), and transient species that rely on regular dispersal from neighbouring habitats (characterised by a more ‘competitive’ ecological strategy).

          3. We analysed a large dataset of conventionally managed arable fields in the UK to study the effect of the immediate landscape on in‐field plant diversity and abundance and to quantify the contribution of spatial mass effects to plant diversity in arable fields in the context of the ecological strategy of the resulting community.

          4. We demonstrated that the decline in diversity with distance into an arable field is highly dependent on the immediate landscape, indicating the important role of spatial mass effects in explaining the increased species richness at field edges in conventionally managed fields.

          5. We observed an increase in the proportion of typical arable weeds away from the field edge towards the centre. This increase was dependent on the immediate landscape and was associated with a higher proportion of more competitive species, with a lower fidelity to arable habitats, at the field edge.

          6. Synthesis and applications. Conserving the ruderal arable plant community, and the invertebrates and birds that use it as a resource, in conventionally managed arable fields typically relies on the targeted reduction of fertilisers and herbicides in so‐called ‘conservation headlands’. The success of these options will depend on the neighbouring habitat and boundary. They should be placed along margins where the potential for ingress of competitive species, that may become dominant in the absence of herbicides, is limited. This will enhance ecosystem services delivered by the ruderal flora and reduce the risk of competitive species occurring in the crop.

          Abstract

          Conserving the ruderal arable plant community, and the invertebrates and birds that use it as a resource, in conventionally managed arable fields typically relies on the targeted reduction of fertilisers and herbicides in so‐called ‘conservation headlands’. The success of these options will depend on the neighbouring habitat and boundary. They should be placed along margins where the potential for ingress of competitive species, that may become dominant in the absence of herbicides, is limited. This will enhance ecosystem services delivered by the ruderal flora and reduce the risk of competitive species occurring in the crop.

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          Most cited references29

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          Small sample inference for fixed effects from restricted maximum likelihood.

          Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings. The statistic uses an adjusted estimator of the covariance matrix that has reduced small sample bias. This approach has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact, namely for Hotelling T2 type statistics and for analysis of variance F-ratios. The performance of the modified statistics is assessed through simulation studies of four different REML analyses and the methods are illustrated using three examples.
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            Vegetation classification by reference to strategies

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              Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities.

              The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community-weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale. © 2012 Blackwell Publishing Ltd/CNRS.
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                Author and article information

                Contributors
                helen.metcalfe@rothamsted.ac.uk
                Journal
                J Appl Ecol
                J Appl Ecol
                10.1111/(ISSN)1365-2664
                JPE
                The Journal of Applied Ecology
                John Wiley and Sons Inc. (Hoboken )
                0021-8901
                1365-2664
                03 June 2019
                July 2019
                : 56
                : 7 ( doiID: 10.1111/jpe.2019.56.issue-7 )
                : 1560-1574
                Affiliations
                [ 1 ] Sustainable Agricultural Sciences Rothamsted Research Harpenden Hertfordshire UK
                [ 2 ] Computational and Analytical Sciences Rothamsted Research Harpenden UK
                [ 3 ] System, INRA, CIHEAM‐IAMM, Montpellier SupAgro Univ Montpellier Montpellier France
                Author notes
                [*] [* ] Correspondence

                Helen Metcalfe

                Email: helen.metcalfe@ 123456rothamsted.ac.uk

                Author information
                https://orcid.org/0000-0002-2862-0266
                Article
                JPE13414
                10.1111/1365-2664.13414
                6618144
                31341329
                1993c6d6-a5f5-4540-8f70-587c981a1888
                © 2019 The Authors. Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 November 2018
                : 26 March 2019
                Page count
                Figures: 5, Tables: 3, Pages: 15, Words: 9400
                Funding
                Funded by: Natural Environment Research Council
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: NE/N018125/1 LTS-M
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                jpe13414
                July 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:10.07.2019

                Ecology
                agricultural landscape,arable fields,conservation headlands,fidelity score,field edge,plant diversity,spatial mass effects,weeds

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