{"title":"Effects of different fire slash artificial promotion regeneration and natural material regeneration on ecological function","authors":"Xiaojing Cai, Falin Liu","doi":"10.3389/fevo.2024.1338166","DOIUrl":null,"url":null,"abstract":"IntroductionIn the aftermath of a fire, prompt reforestation of the affected areas is crucial to mitigate economic losses and ecological impacts.MethodsThis paper introduces an ecological function assessment model leveraging the Back Propagation Neural Network (BPNN). The model's efficacy is validated through simulation comparison experiments. Subsequently, an analysis of the ecosystem's material circulation and energy flow capabilities is undertaken.ResultsSimulation outcomes reveal that our proposed model attains convergence by the 10th training iteration, with a loss function value of just 0.28, highlighting minimal training loss. This underscores the model's rapid convergence and impressive training performance. Our method proves superior to the comparison method in both initial and later operational phases. Notably, it offers a significantly faster response speed and boasts an accuracy rate exceeding 95%.DiscussionConsequently, employing this model to analyze ecological function changes is deemed feasible. The analysis of ecosystem material circulation and energy flow capabilities reveals that while initial assessments show minimal change, scores exhibit a clear acceleration as the cycle progresses.","PeriodicalId":12367,"journal":{"name":"Frontiers in Ecology and Evolution","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Ecology and Evolution","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3389/fevo.2024.1338166","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}
引用次数: 0
Abstract
IntroductionIn the aftermath of a fire, prompt reforestation of the affected areas is crucial to mitigate economic losses and ecological impacts.MethodsThis paper introduces an ecological function assessment model leveraging the Back Propagation Neural Network (BPNN). The model's efficacy is validated through simulation comparison experiments. Subsequently, an analysis of the ecosystem's material circulation and energy flow capabilities is undertaken.ResultsSimulation outcomes reveal that our proposed model attains convergence by the 10th training iteration, with a loss function value of just 0.28, highlighting minimal training loss. This underscores the model's rapid convergence and impressive training performance. Our method proves superior to the comparison method in both initial and later operational phases. Notably, it offers a significantly faster response speed and boasts an accuracy rate exceeding 95%.DiscussionConsequently, employing this model to analyze ecological function changes is deemed feasible. The analysis of ecosystem material circulation and energy flow capabilities reveals that while initial assessments show minimal change, scores exhibit a clear acceleration as the cycle progresses.
期刊介绍:
Frontiers in Ecology and Evolution publishes rigorously peer-reviewed research across fundamental and applied sciences, to provide ecological and evolutionary insights into our natural and anthropogenic world, and how it should best be managed. Field Chief Editor Mark A. Elgar at the University of Melbourne is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide.
Eminent biologist and theist Theodosius Dobzhansky’s astute observation that “Nothing in biology makes sense except in the light of evolution” has arguably even broader relevance now than when it was first penned in The American Biology Teacher in 1973. One could similarly argue that not much in evolution makes sense without recourse to ecological concepts: understanding diversity — from microbial adaptations to species assemblages — requires insights from both ecological and evolutionary disciplines. Nowadays, technological developments from other fields allow us to address unprecedented ecological and evolutionary questions of astonishing detail, impressive breadth and compelling inference.
The specialty sections of Frontiers in Ecology and Evolution will publish, under a single platform, contemporary, rigorous research, reviews, opinions, and commentaries that cover the spectrum of ecological and evolutionary inquiry, both fundamental and applied. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria. Through this unique, Frontiers platform for open-access publishing and research networking, Frontiers in Ecology and Evolution aims to provide colleagues and the broader community with ecological and evolutionary insights into our natural and anthropogenic world, and how it might best be managed.