{"title":"夜间人造光通过生态过程影响林下植物性状——中国橡胶园两年试验","authors":"Cong Zhou, Akihiro Nakamura, Xiaoyang Song, Masatoshi Katabuchi","doi":"10.3390/ecologies4040046","DOIUrl":null,"url":null,"abstract":"Artificial light at night (ALAN) demonstrated a new ecological factor that influences organisms through a multi-approach. Yet, the impacts of ALAN on understory plants remain largely unknown. We evaluated whether ALAN would affect the leaf mass per area (LMA) of understory plants through a two-year field light experiment in a tropical rubber plantation in south China. We hypothesized that ALAN could impact the understory in two ways: by directly supplementing light to aboveground plant parts (which increases LMA) and indirectly affecting soil nutrient composition by attracting insects (which decreases LMA). We selected two species: Colocasia gigantea, representing shade-tolerant species, and Melastoma candidum, representing light-demanding species. We measured canopy openness, LMA, soil nutrients, and individual distance away from light resources. Our Bayesian linear mixed model showed a negative relationship between LMA and the strength of ALAN, indicating that ALAN may influence LMA more indirectly by enhancing soil nutrient availability rather than directly acting as a light resource. This relationship was significant for Colocasia gigantea but not for Melastoma candidum. These results suggest that ALAN might have complex and species-specific impacts on the understory ecosystem. Our study underscores the need for continued research and informed management of anthropogenic ecosystems.","PeriodicalId":72866,"journal":{"name":"Ecologies","volume":" 15","pages":"0"},"PeriodicalIF":1.7000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Light at Night (ALAN) Influences Understory Plant Traits through Ecological Processes: A Two-Year Experiment in a Rubber Plantation in China\",\"authors\":\"Cong Zhou, Akihiro Nakamura, Xiaoyang Song, Masatoshi Katabuchi\",\"doi\":\"10.3390/ecologies4040046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial light at night (ALAN) demonstrated a new ecological factor that influences organisms through a multi-approach. Yet, the impacts of ALAN on understory plants remain largely unknown. We evaluated whether ALAN would affect the leaf mass per area (LMA) of understory plants through a two-year field light experiment in a tropical rubber plantation in south China. We hypothesized that ALAN could impact the understory in two ways: by directly supplementing light to aboveground plant parts (which increases LMA) and indirectly affecting soil nutrient composition by attracting insects (which decreases LMA). We selected two species: Colocasia gigantea, representing shade-tolerant species, and Melastoma candidum, representing light-demanding species. We measured canopy openness, LMA, soil nutrients, and individual distance away from light resources. Our Bayesian linear mixed model showed a negative relationship between LMA and the strength of ALAN, indicating that ALAN may influence LMA more indirectly by enhancing soil nutrient availability rather than directly acting as a light resource. This relationship was significant for Colocasia gigantea but not for Melastoma candidum. These results suggest that ALAN might have complex and species-specific impacts on the understory ecosystem. Our study underscores the need for continued research and informed management of anthropogenic ecosystems.\",\"PeriodicalId\":72866,\"journal\":{\"name\":\"Ecologies\",\"volume\":\" 15\",\"pages\":\"0\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/ecologies4040046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/ecologies4040046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
Artificial Light at Night (ALAN) Influences Understory Plant Traits through Ecological Processes: A Two-Year Experiment in a Rubber Plantation in China
Artificial light at night (ALAN) demonstrated a new ecological factor that influences organisms through a multi-approach. Yet, the impacts of ALAN on understory plants remain largely unknown. We evaluated whether ALAN would affect the leaf mass per area (LMA) of understory plants through a two-year field light experiment in a tropical rubber plantation in south China. We hypothesized that ALAN could impact the understory in two ways: by directly supplementing light to aboveground plant parts (which increases LMA) and indirectly affecting soil nutrient composition by attracting insects (which decreases LMA). We selected two species: Colocasia gigantea, representing shade-tolerant species, and Melastoma candidum, representing light-demanding species. We measured canopy openness, LMA, soil nutrients, and individual distance away from light resources. Our Bayesian linear mixed model showed a negative relationship between LMA and the strength of ALAN, indicating that ALAN may influence LMA more indirectly by enhancing soil nutrient availability rather than directly acting as a light resource. This relationship was significant for Colocasia gigantea but not for Melastoma candidum. These results suggest that ALAN might have complex and species-specific impacts on the understory ecosystem. Our study underscores the need for continued research and informed management of anthropogenic ecosystems.