{"title":"植物群落组合中的性状差异是由环境因素相互作用产生的","authors":"Valério D. Pillar","doi":"10.1111/jvs.13259","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Question</h3>\n \n <p>What conditions drive trait divergence during community assembly through environmental filtering, and why are some communities more trait-diverse than others?</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>An individual-based, stochastic, spatially explicit metacommunity simulation model produced data on species traits, spatially autocorrelated, nested, feedback-generated environmental factors, and resulting community composition. I quantified environmentally driven alpha trait divergence using the correlation <i>r</i>(<b>RE</b>) to measure the relationship between Rao functional diversity and environmental factors. Environmentally driven beta trait divergence was assessed through the correlation <i>r</i>(<b>VE</b>), involving environmental factors and the squared residuals (<b>V</b>) of a second-order polynomial regression of community-weighted means on environmental factors (<b>E</b>). Permutation tests, assuming independence between traits and species composition, were used to establish the significance of <i>r</i>(<b>RE</b>) and <span><i>r</i></span>(<b>VE</b>). Additionally, the method was applied to grassland and soil data collected in plots across southern Brazil. Both simulated and real data were analysed at two spatial resolutions.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Significant <i>r</i>(<b>VE</b>) correlations were frequent with factor interactions incorporated in community assembly simulations, while <i>r</i>(<b>VE</b>) correlations mostly remained within expected Type I error range when factor interactions were absent. <i>r</i>(<b>VE</b>) was stronger than <i>r</i>(<b>RE</b>) at a finer spatial resolution and weaker than <i>r</i>(<b>RE</b>) when smaller community units were combined into larger units. <i>r</i>(<b>VE</b>) for specific leaf area (SLA) was related to soil variables, likely due to their interacting effects with total vegetation cover. When small plots were aggregated into larger units, <i>r</i>(<b>VE</b>) became non-significant, while <i>r</i>(<b>RE</b>) increased.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Environmentally driven trait divergence emerges during community assembly due to interactions between factors affecting the selection of individuals based on their traits. When the effects of these factors are spatially nested, including hidden, feedback-generated ones, trait divergence arises at the beta or alpha dimension, depending on the scale of the community units. This suggests that plant-to-plant positive or negative interactions, which can feedback on environmental factors and generate heterogeneity, do not necessarily lead to trait divergence if these factors do not interact.</p>\n </section>\n </div>","PeriodicalId":49965,"journal":{"name":"Journal of Vegetation Science","volume":"35 3","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trait divergence in plant community assembly is generated by environmental factor interactions\",\"authors\":\"Valério D. Pillar\",\"doi\":\"10.1111/jvs.13259\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Question</h3>\\n \\n <p>What conditions drive trait divergence during community assembly through environmental filtering, and why are some communities more trait-diverse than others?</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>An individual-based, stochastic, spatially explicit metacommunity simulation model produced data on species traits, spatially autocorrelated, nested, feedback-generated environmental factors, and resulting community composition. I quantified environmentally driven alpha trait divergence using the correlation <i>r</i>(<b>RE</b>) to measure the relationship between Rao functional diversity and environmental factors. Environmentally driven beta trait divergence was assessed through the correlation <i>r</i>(<b>VE</b>), involving environmental factors and the squared residuals (<b>V</b>) of a second-order polynomial regression of community-weighted means on environmental factors (<b>E</b>). Permutation tests, assuming independence between traits and species composition, were used to establish the significance of <i>r</i>(<b>RE</b>) and <span><i>r</i></span>(<b>VE</b>). Additionally, the method was applied to grassland and soil data collected in plots across southern Brazil. Both simulated and real data were analysed at two spatial resolutions.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Significant <i>r</i>(<b>VE</b>) correlations were frequent with factor interactions incorporated in community assembly simulations, while <i>r</i>(<b>VE</b>) correlations mostly remained within expected Type I error range when factor interactions were absent. <i>r</i>(<b>VE</b>) was stronger than <i>r</i>(<b>RE</b>) at a finer spatial resolution and weaker than <i>r</i>(<b>RE</b>) when smaller community units were combined into larger units. <i>r</i>(<b>VE</b>) for specific leaf area (SLA) was related to soil variables, likely due to their interacting effects with total vegetation cover. When small plots were aggregated into larger units, <i>r</i>(<b>VE</b>) became non-significant, while <i>r</i>(<b>RE</b>) increased.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Environmentally driven trait divergence emerges during community assembly due to interactions between factors affecting the selection of individuals based on their traits. When the effects of these factors are spatially nested, including hidden, feedback-generated ones, trait divergence arises at the beta or alpha dimension, depending on the scale of the community units. This suggests that plant-to-plant positive or negative interactions, which can feedback on environmental factors and generate heterogeneity, do not necessarily lead to trait divergence if these factors do not interact.</p>\\n </section>\\n </div>\",\"PeriodicalId\":49965,\"journal\":{\"name\":\"Journal of Vegetation Science\",\"volume\":\"35 3\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Vegetation Science\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jvs.13259\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Vegetation Science","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jvs.13259","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Trait divergence in plant community assembly is generated by environmental factor interactions
Question
What conditions drive trait divergence during community assembly through environmental filtering, and why are some communities more trait-diverse than others?
Methods
An individual-based, stochastic, spatially explicit metacommunity simulation model produced data on species traits, spatially autocorrelated, nested, feedback-generated environmental factors, and resulting community composition. I quantified environmentally driven alpha trait divergence using the correlation r(RE) to measure the relationship between Rao functional diversity and environmental factors. Environmentally driven beta trait divergence was assessed through the correlation r(VE), involving environmental factors and the squared residuals (V) of a second-order polynomial regression of community-weighted means on environmental factors (E). Permutation tests, assuming independence between traits and species composition, were used to establish the significance of r(RE) and r(VE). Additionally, the method was applied to grassland and soil data collected in plots across southern Brazil. Both simulated and real data were analysed at two spatial resolutions.
Results
Significant r(VE) correlations were frequent with factor interactions incorporated in community assembly simulations, while r(VE) correlations mostly remained within expected Type I error range when factor interactions were absent. r(VE) was stronger than r(RE) at a finer spatial resolution and weaker than r(RE) when smaller community units were combined into larger units. r(VE) for specific leaf area (SLA) was related to soil variables, likely due to their interacting effects with total vegetation cover. When small plots were aggregated into larger units, r(VE) became non-significant, while r(RE) increased.
Conclusions
Environmentally driven trait divergence emerges during community assembly due to interactions between factors affecting the selection of individuals based on their traits. When the effects of these factors are spatially nested, including hidden, feedback-generated ones, trait divergence arises at the beta or alpha dimension, depending on the scale of the community units. This suggests that plant-to-plant positive or negative interactions, which can feedback on environmental factors and generate heterogeneity, do not necessarily lead to trait divergence if these factors do not interact.
期刊介绍:
The Journal of Vegetation Science publishes papers on all aspects of plant community ecology, with particular emphasis on papers that develop new concepts or methods, test theory, identify general patterns, or that are otherwise likely to interest a broad international readership. Papers may focus on any aspect of vegetation science, e.g. community structure (including community assembly and plant functional types), biodiversity (including species richness and composition), spatial patterns (including plant geography and landscape ecology), temporal changes (including demography, community dynamics and palaeoecology) and processes (including ecophysiology), provided the focus is on increasing our understanding of plant communities. The Journal publishes papers on the ecology of a single species only if it plays a key role in structuring plant communities. Papers that apply ecological concepts, theories and methods to the vegetation management, conservation and restoration, and papers on vegetation survey should be directed to our associate journal, Applied Vegetation Science journal.