Scaling Forest Ecosystem Dynamics from Trees to Landscapes (Collaborative Research)

将森林生态系统动态从树木扩展到景观(合作研究)

基本信息

  • 批准号:
    9615936
  • 负责人:
  • 金额:
    $ 16.02万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    1996
  • 资助国家:
    美国
  • 起止时间:
    1996-08-15 至 2004-01-31
  • 项目状态:
    已结题

项目摘要

We propose to address a fundamental scaling dilemma that plagues ecologists and resource managers. Many current issues are concerned with processes operating on scales of landscapes or regions. But our conventional knowledge base is comparatively fine-scale. For example, anthropogenic climatic change broaches issues of regional (biome) or even larger-scale importance, but our best empirical understanding of the mechanisms of ecological response is at the level of the individual plant. Resource managers face a similar dilemma: multiple-use or ecosystem management implies scales of watersheds or landscapes, yet our knowledge base for forest management is founded at the level of individual trees or homogeneous stands. In general, scaling involves a trade-off between resolution (grain, or level of detail) and extent (the area or scope of the study). Large extent comes at the expense of fine-grained resolution of detail, and so, studies that focus on details do so over a small spatial domain, while large-scale studies typically sacrifice detail to embrace coarser-resolution patterns. This scaling trade-off can enforce an incompatibility across scales. Large-scale studies typically are based on different conceptual models and different data, as compared to fine-scale studies. While it might be assumed optimistically that models derived from different empirical bases at disparate scales might nonetheless converge at a common scale, in practice such models cannot be compared rigorously because they have too little in common. We propose to develop a suite of simulation models which address questions at different scales while still maintaining a consistent conceptual and empirical basis. By preserving this commonality among models, we can change scale rigorously as needed, and when using alternative models we can be confident that discrepancies in the predictions of these various models are due to explicit assumptions or formulations rather than to unknowable incompati bilities in the underlying data. We will begin with forest gap model, which simulates the establishment, growth, and mortality of individual trees on a small (0.1 ha) model plot, at an annual timestep. Gap models typically are used to extrapolate tree-level demographics to stand-level (~10 ha) dynamics over successional time periods. We will then use this model to generate and parameterize three derived models (metamodels) that reproduce selected coarse-resolution aspects of the gap model's behavior, but do so with much greater computational efficiency. We propose to demonstrate this approach with a nonlinear stage-structured model, a semi-markovian patch transition model, and a cellular automaton. Each metamodel emphasizes a different aspect of forest dynamics, and so each is amenable to particular kinds of applications. We have selected the forests of the Pacific Northwest (PNW) as a testbed for the development of this methodology, but the resulting methods will be applicable to a diverse range of forest ecosystems. In particular, our gap model is already in use in the northwest, southwest, northeast, and the southeastern United States. The approach should also be applicable to other types of models. We will make our models and documentation available to other users.
我们建议解决困扰生态学家和资源管理者的一个根本的规模困境。目前的许多问题都涉及在景观或区域规模上运作的过程。但我们的常规知识库规模相对较小。例如,人为气候变化提出了区域性(生物群)甚至更大范围的重要性问题,但我们对生态响应机制的最佳经验理解是在单个植物的水平上。资源管理者面临着类似的两难境地:多用途或生态系统管理意味着流域或景观的规模,而我们的森林管理知识库建立在单株树木或同类林分的水平上。通常,缩放涉及分辨率(颗粒或细节级别)和范围(研究的区域或范围)之间的权衡。很大程度上是以牺牲细节的细粒度分辨率为代价的,因此,专注于细节的研究是在较小的空间域上进行的,而大规模研究通常会牺牲细节,以接受较粗分辨率的模式。这种扩展权衡可能会强制实现跨扩展的不兼容性。与精细研究相比,大规模研究通常基于不同的概念模型和不同的数据。虽然可以乐观地假设,从不同尺度上的不同经验基础得出的模型仍然可以在共同的尺度上收敛,但在实践中,这些模型不能进行严格的比较,因为它们的共同点太少。我们建议开发一套模拟模型,解决不同规模的问题,同时保持一致的概念和经验基础。通过保留模型之间的这种共性,我们可以根据需要严格地改变比例,当使用替代模型时,我们可以确信,这些不同模型的预测差异是由于明确的假设或公式,而不是由于基础数据中不可知的不相容。我们将从森林空隙模型开始,该模型在一小块(0.1公顷)模型地块上以每年的时间步长模拟单株树木的建立、生长和死亡。林隙模型通常用于将林木水平的人口统计外推到林分水平(~10公顷)演替时期的动态。然后,我们将使用此模型生成三个派生模型(元模型)并将其参数化,这些模型复制GAP模型行为的选定粗分辨率方面,但这样做的计算效率要高得多。我们建议用一个非线性阶段结构模型、一个半马尔可夫斑块转移模型和一个元胞自动机来演示这个方法。每个元模型强调森林动态的不同方面,因此每个元模型都适用于特定类型的应用。我们选择了太平洋西北(PNW)的森林作为开发这一方法的试验台,但由此产生的方法将适用于不同范围的森林生态系统。特别是,我们的GAP模型已经在美国西北部、西南部、东北部和东南部使用。该方法也应适用于其他类型的模型。我们将向其他用户提供我们的模型和文档。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Miguel Acevedo其他文献

Two-dimensional simulation of the seismic response of the Santiago Basin, Chile
  • DOI:
    10.1016/j.soildyn.2022.107569
  • 发表时间:
    2023-01-01
  • 期刊:
  • 影响因子:
  • 作者:
    José Bustos;César Pastén;Diego Pavez;Miguel Acevedo;Sergio Ruiz;Rodrigo Astroza
  • 通讯作者:
    Rodrigo Astroza
MOTEINO-BASED WIRELESS DATA TRANSFER FOR ENVIRONMENTAL MONITORING Samuel Iyiola Thesis Prepared for the Degree of MASTER OF SCIENCE UNIVERSITY OF NORTH TEXAS
基于 MOTEINO 的环境监测无线数据传输 Samuel Iyiola 为北德克萨斯大学理学硕士学位论文准备
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Miguel Acevedo;Xinrong Li;Yan Wan;Shengli Fu;Victor Prybutok;Samuel Iyiola;Ramanpreet Singh;Phillip Hensley;Michael Assad;Sanjaya Gurung;Satish Kumar
  • 通讯作者:
    Satish Kumar
Electromagnetic Water Treatment and Soil Compost Incorporation to Alleviate the Impact of Soil Salinization
电磁水处理和土壤堆肥掺入减轻土壤盐碱化的影响
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Subanky Suvendran;David Johnson;Miguel Acevedo;Breana Smithers;Pei Xu
  • 通讯作者:
    Pei Xu

Miguel Acevedo的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Miguel Acevedo', 18)}}的其他基金

INFEWS/T2: Improving crop yield and soil salinity by cost-effective integration of microbial community, hydrology, desalination, and renewable power
INFEWS/T2:通过经济高效地整合微生物群落、水文、海水淡化和可再生能源来提高作物产量和土壤盐分
  • 批准号:
    1856052
  • 财政年份:
    2019
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Continuing Grant
SG: The demographic and life-history consequences of re-colonizing secondary habitats
SG:重新殖民次生栖息地的人口和生活史后果
  • 批准号:
    1754401
  • 财政年份:
    2018
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
RET Site: Research Experiences for Teachers in Sensor Networks
RET 网站:传感器网络教师的研究经验
  • 批准号:
    1132585
  • 财政年份:
    2011
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
CI-TEAM Demonstration Project: Engaging Local Governments, Teachers and Students in CI for Environmental Monitoring and Modeling
CI-TEAM示范项目:让地方政府、教师和学生参与CI环境监测和建模
  • 批准号:
    0636421
  • 财政年份:
    2006
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
BE/CNH: Biocomplexity: Integrating Models of Natural and Human Dynamics in Forest Landscapes Across Scales and Cultures
BE/CNH:生物复杂性:跨尺度和文化的森林景观中自然和人类动态的整合模型
  • 批准号:
    0216722
  • 财政年份:
    2002
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
U.S.-Spain Cooperative Research: Modeling Grass and Shrub Vegetation Recovery After Disturbance
美国-西班牙合作研究:模拟干扰后草和灌木植被的恢复
  • 批准号:
    0104728
  • 财政年份:
    2001
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
QEIB: Uncertainty Analysis, Spatial Interaction and Response Functions in Scaling-up Models of Forest Ecosystems
QEIB:森林生态系统放大模型中的不确定性分析、空间相互作用和响应函数
  • 批准号:
    0108563
  • 财政年份:
    2001
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant

相似国自然基金

基于深度森林(Deep Forest)模型的表面增强拉曼光谱分析方法研究
  • 批准号:
    2020A151501709
  • 批准年份:
    2020
  • 资助金额:
    10.0 万元
  • 项目类别:
    省市级项目
兴安落叶松林(Larix gmelinii forest) 土壤微生物对火干扰的响应机制研究
  • 批准号:
    31870644
  • 批准年份:
    2018
  • 资助金额:
    60.0 万元
  • 项目类别:
    面上项目

相似海外基金

Forest Conservation by Payment for Ecosystem Services (PES): A Comprehensive Analysis of the Policy Outcome to Subsidize the Cooking Fuel in Teknaf-Ukhia, Bangladesh
通过生态系统服务付费 (PES) 进行森林保护:孟加拉国 Teknaf-Ukhia 烹饪燃料补贴政策结果的综合分析
  • 批准号:
    24K20975
  • 财政年份:
    2024
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Building a Conservation Strategy of Forest Ecosystem Services by Socio-Ecological System Approach
通过社会生态系统方法制定森林生态系统服务保护战略
  • 批准号:
    23K11541
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
The simulation of forest management for sustainable provision of ecosystem services under climate change.
气候变化下可持续提供生态系统服务的森林管理模拟。
  • 批准号:
    22KJ0029
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
CAREER: From the forest to the stream: Exploring forest land cover controls on dissolved organic matter character and aquatic ecosystem respiration in headwater streams
职业:从森林到溪流:探索森林土地覆盖对源头溪流中溶解有机物特征和水生生态系统呼吸的控制
  • 批准号:
    2333030
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Continuing Grant
Liana impact on net ecosystem production in a temperate forest
藤本植物对温带森林净生态系统生产的影响
  • 批准号:
    23KJ0255
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
Muddy Waters, Africa's uncharted forest ecosystem
Muddy Waters,非洲未知的森林生态系统
  • 批准号:
    2894254
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Studentship
Elements: Science-i Cyberinfrastructure for Forest Ecosystem Research
要素:森林生态系统研究的 Science-i 网络基础设施
  • 批准号:
    2311762
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Standard Grant
NSF Engines Development Award: Advancing forest ecosystem management and forest product innovations (NH, ME, VT)
NSF 引擎发展奖:推进森林生态系统管理和林产品创新(新罕布什尔州、缅因州、佛蒙特州)
  • 批准号:
    2303493
  • 财政年份:
    2023
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Cooperative Agreement
Wood functional trait variation as a critical driver of forest ecosystem processes and biogeochemical cycles
木材功能性状变异是森林生态系统过程和生物地球化学循环的关键驱动因素
  • 批准号:
    569069-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Postgraduate Scholarships - Doctoral
Ecosystem-based FORest management in a Changing Environment (EFORCE)
变化环境中基于生态系统的森林管理 (EFORCE)
  • 批准号:
    566416-2021
  • 财政年份:
    2022
  • 资助金额:
    $ 16.02万
  • 项目类别:
    Alliance Grants
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了