17
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Potential worldwide distribution of Fusarium dry root rot in common beans based on the optimal environment for disease occurrence

      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

          Root rots are a constraint for staple food crops and a long-lasting food security problem worldwide. In common beans, yield losses originating from root damage are frequently attributed to dry root rot, a disease caused by the Fusarium solani species complex. The aim of this study was to model the current potential distribution of common bean dry root rot on a global scale and to project changes based on future expectations of climate change. Our approach used a spatial proxy of the field disease occurrence, instead of solely the pathogen distribution. We modeled the pathogen environmental requirements in locations where in-situ inoculum density seems ideal for disease manifestation. A dataset of 2,311 soil samples from commercial farms assessed from 2002 to 2015 allowed us to evaluate the environmental conditions associated with the pathogen’s optimum inoculum density for disease occurrence, using a lower threshold as a spatial proxy. We encompassed not only the optimal conditions for disease occurrence but also the optimal pathogen’s density required for host infection. An intermediate inoculum density of the pathogen was the best disease proxy, suggesting density-dependent mechanisms on host infection. We found a strong convergence on the environmental requirements of both the host and the disease development in tropical areas, mostly in Brazil, Central America, and African countries. Precipitation and temperature variables were important for explaining the disease occurrence (from 17.63% to 43.84%). Climate change will probably move the disease toward cooler regions, which in Brazil are more representative of small-scale farming, although an overall shrink in total area (from 48% to 49% in 2050 and 26% to 41% in 2070) was also predicted. Understanding pathogen distribution and disease risks in an evolutionary context will therefore support breeding for resistance programs and strategies for dry root rot management in common beans.

          Related collections

          Most cited references53

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Yield Trends Are Insufficient to Double Global Crop Production by 2050

          Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops—maize, rice, wheat, and soybean—that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Selecting pseudo-absences for species distribution models: how, where and how many?

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

              Niches and distributional areas: concepts, methods, and assumptions.

              Estimating actual and potential areas of distribution of species via ecological niche modeling has become a very active field of research, yet important conceptual issues in this field remain confused. We argue that conceptual clarity is enhanced by adopting restricted definitions of "niche" that enable operational definitions of basic concepts like fundamental, potential, and realized niches and potential and actual distributional areas. We apply these definitions to the question of niche conservatism, addressing what it is that is conserved and showing with a quantitative example how niche change can be measured. In this example, we display the extremely irregular structure of niche space, arguing that it is an important factor in understanding niche evolution. Many cases of apparently successful models of distributions ignore biotic factors: we suggest explanations to account for this paradox. Finally, relating the probability of observing a species to ecological factors, we address the issue of what objects are actually calculated by different niche modeling algorithms and stress the fact that methods that use only presence data calculate very different quantities than methods that use absence data. We conclude that the results of niche modeling exercises can be interpreted much better if the ecological and mathematical assumptions of the modeling process are made explicit.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 November 2017
                2017
                : 12
                : 11
                : e0187770
                Affiliations
                [1 ] Universidade Federal de Goiás, Escola de Agronomia e Engenharia de Alimentos, Goiânia, GO, Brazil
                [2 ] Universidade Federal de Goiás, Departamento de Ecologia e Evolução, Goiânia, GO, Brazil
                [3 ] Empresa Brasileira de Pesquisa Agropecuária–Embrapa Arroz e Feijão, Santo Antônio de Goiás, GO, Brazil
                Universita degli Studi di Pisa, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-3681-4570
                Article
                PONE-D-17-19778
                10.1371/journal.pone.0187770
                5673228
                29107985
                d58a99f3-ab14-4502-a9f8-c329fd66a191
                © 2017 Macedo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 June 2017
                : 25 October 2017
                Page count
                Figures: 4, Tables: 3, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Award Recipient :
                Funded by: Fundação de Amparo à Pesquisa do Estado de Goiás (BR)
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 407844/2013-9
                Award Recipient :
                R.M. was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, http://www.capes.gov.br/. L.L.S-A was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico, http://cnpq.br/. L.P.S. was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, http://www.capes.gov.br/. F.Y. was supported by Fundação de Amparo à Pesquisa do Estado de Goiás, http://www.fapeg.go.gov.br/. M.L J. was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico, http://cnpq.br/; CNPq grant 407844/2013-9. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Legumes
                Beans
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Change
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                People and places
                Geographical locations
                South America
                Brazil
                Biology and Life Sciences
                Plant Science
                Plant Pathology
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Physical Sciences
                Mathematics
                Probability Theory
                Statistical Distributions
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Vegetables
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article