6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Unexpected Effects of Local Management and Landscape Composition on Predatory Mites and Their Food Resources in Vineyards

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Simple Summary

          Sustainable agriculture becomes more important for biodiversity conservation and environmental protection. Viticulture is characterized by relatively high pesticide inputs, which could decrease arthropod populations and biological pest control in vineyards. This problem could be counteracted with management practices such as the implementation of diverse vegetation cover in the vineyard inter-rows, reduced pesticide input in integrated or organic vineyards, and a diverse landscape with trees and hedges. We examined the influence of these factors on predatory mites, which play a crucial role as natural enemies for pest mites on vines, and pollen as important alternative food source for predatory mites in 32 organic and integrated Austrian vineyards. Predatory mites benefited from integrated pesticide management and spontaneous vegetation cover in vineyard inter-rows. Pest mite populations were very low and sometimes completely absent on vines. This showed that agri-environmental schemes should consider less intensive pesticide use and spontaneous vegetation cover in the vineyard inter-row due to the beneficial effect on predatory mite populations and their related biological control potential in vineyards.

          Abstract

          Viticultural practices and landscape composition are the main drivers influencing biological pest control in vineyards. Predatory mites, mainly phytoseiid (Phytoseiidae) and tydeoid mites (Tydeidae), are important to control phytophagous mites (Tetranychidae and Eriophyidae) on vines. In the absence of arthropod prey, pollen is an important food source for predatory mites. In 32 paired vineyards located in Burgenland/Austria, we examined the effect of landscape composition, management type (organic/integrated), pesticide use, and cover crop diversity of the inter-row on the densities of phytoseiid, tydeoid, and phytophagous mites. In addition, we sampled pollen on vine leaves. Typhlodromus pyri Scheuten was the main phytoseiid mite species and Tydeus goetzi Schruft the main tydeoid species. Interestingly, the area-related acute pesticide toxicity loading was higher in organic than in integrated vineyards. The densities of phytoseiid and tydeoid mites was higher in integrated vineyards and in vineyards with spontaneous vegetation. Their population also profited from an increased viticultural area at the landscape scale. Eriophyoid mite densities were extremely low across all vineyards and spider mites were absent. Biological pest control of phytophagous mites benefits from less intensive pesticide use and spontaneous vegetation cover in vineyard inter-rows, which should be considered in agri-environmental schemes.

          Related collections

          Most cited references149

          • Record: found
          • Abstract: not found
          • Article: not found

          Fitting Linear Mixed-Effects Models Usinglme4

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Correlation Coefficients

            Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              World Map of the Köppen-Geiger climate classification updated

                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Insects
                Insects
                insects
                Insects
                MDPI
                2075-4450
                19 February 2021
                February 2021
                : 12
                : 2
                : 180
                Affiliations
                [1 ]Institute of Plant Protection, University of Natural Resources and Life Sciences Vienna (BOKU), Gregor-Mendel-Straße 33, 1180 Vienna, Austria; andreas.walzer@ 123456boku.ac.at (A.W.); markus.redl@ 123456boku.ac.at (M.R.); bozana.petrovic@ 123456boku.ac.at (B.P.); silvia.winter@ 123456boku.ac.at (S.W.)
                [2 ]Julius Kühn-Institute (JKI), Institute for Plant Protection in Fruit Crops and Viticulture, Geilweilerhof, 76833 Siebeldingen, Germany; christoph.hoffmann@ 123456julius-kuehn.de
                Author notes
                [* ]Correspondence: stefan.moeth@ 123456boku.ac.at ; Tel.: +43-1-47654-95329
                Author information
                https://orcid.org/0000-0002-2706-347X
                https://orcid.org/0000-0001-8364-751X
                https://orcid.org/0000-0002-8322-7774
                Article
                insects-12-00180
                10.3390/insects12020180
                7922120
                33669755
                cb202b69-d17f-4772-92dd-6484789282d2
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 January 2021
                : 17 February 2021
                Categories
                Article

                phytoseiidae,tydeidae,eriophyidae,biological pest control,viticulture,cover crops,pollen,pesticide toxicity index

                Comments

                Comment on this article