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      Evaluating the contribution of historical and contemporary temperature to the oospore production of self‐fertile Phytophthora infestans

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          Abstract

          Reproductive systems play an important role in the ecological function of species, but little is known about how climate change, such as global warming, may affect the reproductive systems of microbes. In this study, 116 Phytophthora infestans isolates sampled from five different altitudes along a mountain were evaluated under five temperature regimes to determine the effects of historical and experimental temperature on the reproductive system of the pathogen. Both altitude, a proxy for historical pathogen adaptation to temperature, and temperature used in the experiment affected the sexual reproduction of the pathogen, with experimental temperature, that is, contemporary temperature, playing a role several times more important than historical temperature. Furthermore, the potential of sexual reproduction, measured by the number of oospores quantified, increased with the temperature breadth (i.e., difference between the highest and lowest temperature at which sexual reproduction takes place) of the pathogen and reached the maximum at the experimental temperature of 21°C, which is higher than the annual average temperature in many potato‐producing areas. The results suggest that rising air temperature associated with global warming may increase the potential of sexual reproduction in P. infestans. Given the importance of sexuality in pathogenicity and ecological adaptation of pathogens, these results suggest that global warming may increase the threat of P. infestans to agricultural production and other ecological services and highlight that new epidemiological strategies may need to be implemented for future food security and ecological resilience.

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          Phytophthora infestans: the plant (and R gene) destroyer.

          Phytophthora infestans remains a problem to production agriculture. Historically there have been many controversies concerning its biology and pathogenicity, some of which remain today. Advances in molecular biology and genomics promise to reveal fascinating insight into its pathogenicity and biology. However, the plasticity of its genome as revealed in population diversity and in the abundance of putative effectors means that this oomycete remains a formidable foe.
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            Less Than 2 °C Warming by 2100 Unlikely

            The recently published Intergovernmental Panel on Climate Change (IPCC) projections to 2100 give likely ranges of global temperature increase in four scenarios for population, economic growth and carbon use 1 . However these projections are not based on a fully statistical approach. Here we use a country-specific version of Kaya’s identity to develop a statistically-based probabilistic forecast of CO2 emissions and temperature change to 2100. Using data for 1960-2010, including the UN’s probabilistic population projections for all countries 2–4 , we develop a joint Bayesian hierarchical model for GDP per capita and carbon intensity. We find that the 90% interval for cumulative CO2 emissions includes the IPCC’s two middle scenarios but not the extreme ones. The likely range of global temperature increase is 2.0–4.9°C, with median 3.2°C and a 5% (1%) chance that it will be less than 2°C (1.5°C). Population growth is not a major contributing factor. Our model is not a “business as usual” scenario, but rather is based on data which already show the effect of emission mitigation policies. Achieving the goal of less than 1.5°C warming will require carbon intensity to decline much faster than in the recent past.
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              Assessing population structure: F(ST) and related measures.

              Although F(ST) is widely used as a measure of population structure, it has been criticized recently because of its dependency on within-population diversity. This dependency can lead to difficulties in interpretation and in the comparison of estimates among species or among loci and has led to the development of two replacement statistics, F'(ST) and D. F'(ST) is the normal F(ST) standardized by the maximum value it can obtain, given the observed within-population diversity. D uses a multiplicative partitioning of diversity, based on the effective number of alleles rather than on the expected heterozygosity. In this study, we review the relationships between the three classes of statistics (F(ST), F'(ST) and D), their estimation and their properties. We illustrate the relationships between the statistics using a data set of estimates from 84 species taken from the last 4 years of Molecular Ecology. As with F(ST), unbiased estimators are available for the two new statistics D and F'(ST). Here, we develop a new unbiased F'(ST) estimator based on G(ST), which we call G''(ST). However, F'(ST) can be calculated using any F(ST) estimator for which the maximum value can be obtained. As all three statistics have their advantages and their drawbacks, we recommend continued use of F(ST) in combination with either F'(ST) or D. In most cases, F'(ST) would be the best choice among the latter two as it is most suited for inferences of the influence of demographic processes such as genetic drift and migration on genetic population structure. © 2010 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                jiasui.zhan@slu.se
                yikeshu1114@126.com
                Journal
                Evol Appl
                Evol Appl
                10.1111/(ISSN)1752-4571
                EVA
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                1752-4571
                29 January 2024
                January 2024
                : 17
                : 1 ( doiID: 10.1111/eva.v17.1 )
                : e13643
                Affiliations
                [ 1 ] Fujian Key Laboratory on Conservation and Sustainable Utilization of Marine Biodiversity, Fuzhou Institute of Oceanography Minjiang University Fuzhou China
                [ 2 ] Institute of Plant Pathology Fujian Agriculture and Forestry University Fuzhou China
                [ 3 ] College of Chemistry and Life Sciences Chengdu Normal University Chengdu China
                [ 4 ] Department of Forest Mycology and Plant Pathology Swedish University of Agricultural Sciences Uppsala Sweden
                Author notes
                [*] [* ] Correspondence

                Jiasui Zhan, Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden.

                Email: jiasui.zhan@ 123456slu.se

                Li‐Na Yang, Fujian Key Laboratory on Conservation and Sustainable Utilization of Marine Biodiversity, Fuzhou Institute of Oceanography, Minjiang University, Fuzhou 350108, China.

                Email: yikeshu1114@ 123456126.com

                Author information
                https://orcid.org/0009-0007-3889-7182
                https://orcid.org/0000-0002-7756-6534
                https://orcid.org/0000-0001-9250-0157
                https://orcid.org/0000-0003-4431-7213
                Article
                EVA13643 EVA-2023-198-OA.R2
                10.1111/eva.13643
                10824702
                38293269
                c597df68-b0fe-42a5-9c52-4d8d1e333e6a
                © 2024 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

                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
                : 27 December 2023
                : 12 September 2023
                : 03 January 2024
                Page count
                Figures: 4, Tables: 4, Pages: 10, Words: 7847
                Funding
                Funded by: National Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 31761143010
                Award ID: 31901861
                Award ID: U1405213
                Funded by: Natural Science Foundation of Fujian Province , doi 10.13039/501100003392;
                Award ID: 2023J011414
                Funded by: Talents Scheme of Minjiang University
                Award ID: MJY21019
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                January 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.6 mode:remove_FC converted:29.01.2024

                Evolutionary Biology
                adaptation,agriculture,climate change,ecological genetics,evolution of sex,microbial biology

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