Dries Landuyt , Haben Blondeel , Eline Lorer , Michael P. Perring , Kathy Steppe , Kris Verheyen
{"title":"温带森林林下群落动态预测的特征建模方法","authors":"Dries Landuyt , Haben Blondeel , Eline Lorer , Michael P. Perring , Kathy Steppe , Kris Verheyen","doi":"10.1016/j.ecolmodel.2024.110873","DOIUrl":null,"url":null,"abstract":"<div><p>Understorey communities in temperate forests have often been ignored in the study of the dynamics of forest structure and function, while evidence for the importance of this biotic layer is accumulating. Scarcity in understorey data with a high temporal resolution, and understorey data types that do not match popular vegetation modelling concepts, have limited previous modelling attempts to empirical models that are hard to extrapolate to new environmental conditions. Here we introduce a new process-based modelling approach designed specifically for understorey communities, whose dynamics are generally characterised by changes in (species-specific) cover data, while species characterisation is largely based on plant functional trait measurements. By confronting the model to data gathered in a large understorey mesocosm experiment, we show that our model concept is promising, and is able to predict performance differences within a species. Predictions across species were found to be more challenging, and will likely require new data on understorey traits and processes. In particular, new data on understorey carbon assimilation rates, vegetative phenology, plant architecture and belowground processes, are needed to advance the field of process-based understorey modelling.</p></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"498 ","pages":"Article 110873"},"PeriodicalIF":2.6000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A trait-based modelling approach towards dynamic predictions of understorey communities in temperate forests\",\"authors\":\"Dries Landuyt , Haben Blondeel , Eline Lorer , Michael P. Perring , Kathy Steppe , Kris Verheyen\",\"doi\":\"10.1016/j.ecolmodel.2024.110873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Understorey communities in temperate forests have often been ignored in the study of the dynamics of forest structure and function, while evidence for the importance of this biotic layer is accumulating. Scarcity in understorey data with a high temporal resolution, and understorey data types that do not match popular vegetation modelling concepts, have limited previous modelling attempts to empirical models that are hard to extrapolate to new environmental conditions. Here we introduce a new process-based modelling approach designed specifically for understorey communities, whose dynamics are generally characterised by changes in (species-specific) cover data, while species characterisation is largely based on plant functional trait measurements. By confronting the model to data gathered in a large understorey mesocosm experiment, we show that our model concept is promising, and is able to predict performance differences within a species. Predictions across species were found to be more challenging, and will likely require new data on understorey traits and processes. In particular, new data on understorey carbon assimilation rates, vegetative phenology, plant architecture and belowground processes, are needed to advance the field of process-based understorey modelling.</p></div>\",\"PeriodicalId\":51043,\"journal\":{\"name\":\"Ecological Modelling\",\"volume\":\"498 \",\"pages\":\"Article 110873\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Modelling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304380024002618\",\"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":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380024002618","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}
A trait-based modelling approach towards dynamic predictions of understorey communities in temperate forests
Understorey communities in temperate forests have often been ignored in the study of the dynamics of forest structure and function, while evidence for the importance of this biotic layer is accumulating. Scarcity in understorey data with a high temporal resolution, and understorey data types that do not match popular vegetation modelling concepts, have limited previous modelling attempts to empirical models that are hard to extrapolate to new environmental conditions. Here we introduce a new process-based modelling approach designed specifically for understorey communities, whose dynamics are generally characterised by changes in (species-specific) cover data, while species characterisation is largely based on plant functional trait measurements. By confronting the model to data gathered in a large understorey mesocosm experiment, we show that our model concept is promising, and is able to predict performance differences within a species. Predictions across species were found to be more challenging, and will likely require new data on understorey traits and processes. In particular, new data on understorey carbon assimilation rates, vegetative phenology, plant architecture and belowground processes, are needed to advance the field of process-based understorey modelling.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).