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Belmont Forum Collaborative Research: Conservation policy in a changing world: integrating citizen science data from national monitoring schemes to model impacts of global change s

贝尔蒙特论坛合作研究：不断变化的世界中的保护政策：整合来自国家监测计划的公民科学数据来模拟全球变化的影响

基本信息

批准号：
1927646
负责人：
Wesley Hochachka
金额：
$ 17.9万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2023-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1927646&HistoricalAwards=false
关键词：
Belmont Forum Collaborative Research Conservation

项目摘要

Innovative research on the complex interaction of socio-economic and global environmental trends on biodiversity and ecosystem services is needed to help develop more informative scenarios for addressing environmental and human development challenges. To overcome these challenges coupled natural-human systems approaches and analyses are needed. These provide improved scenarios of biodiversity and ecosystem services that couple the outputs of direct and indirect drivers such as land use, invasive species, overexploitation, biodiversity, environmental change, and pollution. The resulting models provide a methodological state-of-the art that results in more accurate quantitative assessments, better land use, and more effective ecosystem services. Employing this methodology, this research project, which is an international coalition between US scientists and those from Fennoscandinavian nations, seeks to use birds as bioindicators of environmental health on large scales such as changes to farming or forestry practices and on smaller scales such as environmental recovery from localized severe weather or pollution events. This choice of indicator is because birds are valuable indicators of environmental conditions because they are ubiquitous in most environments, with different species having different food and habitat requirements. Thus, birds, as a group, sample environments in different ways during the process of acquiring food which can range from small organisms, such as plankton, to animals larger than rabbits, depending on the species of bird and its evolved food requirements. Additionally, when environmental conditions make food scarce, most species of birds simply fly away and seek more conducive environs. As a result, the response of birds to changing conditions can be far more rapid than the responses of less mobile organisms. Birds are also typically visually and vocally obvious and there are bird-watching hobbyists (i.e. citizen scientists) across the globe who observe and record the birds they see throughout the year and what those birds are doing. Thus, large amounts of data exist from which we can learn about the environmental conditions preferred by a large number of species of birds. Project goals are to: (1) create methods for identifying a set of bird species that are good indicators of environmental conditions in habitats such as alpine/arctic tundra, highly managed and natural forests, and farmland and (2) use this information to anticipate changes in physical conditions (e.g., weather) and those caused by people (e.g., land use and farming practices). Broader impacts of this research include international collaboration scientists in Norway, Sweden, and Finland and the use of citizen science and the collection of data by the birdwatching public. Impacts also include those that are societal and economic in terms of the relation of study results to achieving sustainable harvests and fisheries. Other impacts include development of a planning tool for minimizing losses of key ecosystem services from birds in forest regeneration, pest management, and sustainable harvests that can be used by resource managers. Results of the study will be valuable for the development of science-based policies where avian species play a role.This award supports US researchers participating in a project competitively selected by a coalition of 26 funding agencies from 23 countries through the Belmont Forum call for proposals on "Scenarios of Biodiversity and Ecosystem Services". The call was a multilateral initiative designed to support research projects that contribute to the development of scenarios, models, and decision-support tools for understanding and solving critical issues facing our planet. The goal of the competition was to improve and apply participatory scenario methods to enhance research relevance and its acceptance and to address gaps in methods for modelling impact drivers and policy interventions. It was also to develop and communicate levels of uncertainty associated with the models, to improve data accessibility and fill gaps in knowledge. Using this methodology, the funded project will address knowledge gaps on the links between biodiversity and habitat alteration using birds as indicator species. Project objectives are to improve methods for predicting the responses of birds to changes in their environments. Instead of merely looking at correlations between where species live and features of the environments they inhabit or travel though, this work examine the causal associations between birds and their environments by looking at functional traits (i.e., those that lead birds to respond to changes in their environment). To accomplish this, the project makes use of year-round data from a large geographic area, i.e., Europe, to track migratory bird species and their habitat associations in their summer and winter ranges and along their migratory routes to determine when and where responses to environmental change are strongest, thus improving our ability to accurately forecast responses to environmental changes. This is a "whole-life-cycle" approach to assessing population health and is only now being explored by ecological researchers. The US component of the project focuses on developing computationally intensive machine-learning methods by investigators who have extensive expertise in working with very large citizen science data sets. The parts of the project carried out by scientists from other countries will be funded by those countries. This work will, in addition to anticipating consequences of physical conditions and anthropogenic land-use practices across Europe, aid in the development of new conservation strategies in response to environmental change, for example by identifying needs or opportunities to change the areas targeted for management actions such as habitat protection or restoration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

需要对社会经济和全球环境趋势对生物多样性和生态系统服务的复杂相互作用进行创新研究，以帮助开发更多信息丰富的情景，以应对环境和人类发展挑战。为了克服这些挑战，需要结合自然-人类系统的方法和分析。这些方案提供了生物多样性和生态系统服务的改进情景，将土地利用、入侵物种、过度开发、生物多样性、环境变化和污染等直接和间接驱动因素的产出结合起来。由此产生的模型提供了一种最先进的方法，可以实现更准确的定量评估、更好的土地利用和更有效的生态系统服务。采用这种方法，这个由美国科学家和北欧国家科学家组成的国际联盟的研究项目，寻求将鸟类作为环境健康的生物指标，在大范围内，如农业或林业实践的变化，在小范围内，如局部恶劣天气或污染事件的环境恢复。之所以选择这一指标，是因为鸟类在大多数环境中都是有价值的环境条件指标，不同的物种对食物和栖息地的要求不同。因此，鸟类作为一个群体，在获取食物的过程中以不同的方式对环境进行采样，从浮游生物等小型生物到比兔子大的动物，这取决于鸟类的种类及其进化的食物需求。此外，当环境条件使食物稀缺时，大多数鸟类只是飞走，寻找更有利的环境。因此，鸟类对不断变化的环境的反应可能比流动性较差的生物的反应要快得多。鸟类在视觉和声音上也很明显，全球各地都有观鸟爱好者（即公民科学家），他们观察并记录他们全年看到的鸟类以及这些鸟类的行为。因此，有了大量的数据，我们可以从中了解大量鸟类喜欢的环境条件。项目目标是：(1)创建识别一组鸟类物种的方法，这些鸟类物种是栖息地环境条件的良好指标，如高山/北极苔原、高度管理的天然林和农田；(2)利用这些信息预测物理条件（如天气）和人为因素（如土地利用和耕作方式）的变化。这项研究的广泛影响包括挪威、瑞典和芬兰的国际合作科学家，以及公民科学的使用和观鸟公众的数据收集。就研究结果与实现可持续捕捞和渔业的关系而言，影响还包括社会和经济方面的影响。其他影响包括开发一种规划工具，以最大限度地减少鸟类在森林再生、病虫害管理和可持续收获方面的关键生态系统服务损失，供资源管理者使用。该研究结果将为制定基于科学的政策提供有价值的参考。该奖项支持参与由来自23个国家的26个资助机构组成的联盟通过贝尔蒙特论坛征集“生物多样性和生态系统服务情景”提案竞争性选择的项目的美国研究人员。该呼吁是一项多边倡议，旨在支持有助于开发情景、模型和决策支持工具的研究项目，以了解和解决我们星球面临的关键问题。竞赛的目标是改进和应用参与式情景方法，以提高研究的相关性和接受度，并解决影响驱动因素和政策干预建模方法方面的差距。它还开发和交流与模型相关的不确定性水平，以改善数据可访问性并填补知识空白。利用这一方法，该资助项目将利用鸟类作为指示物种，解决生物多样性与栖息地变化之间联系的知识空白。该项目的目标是改进预测鸟类对环境变化的反应的方法。这项工作不仅仅是研究物种生活的地方和它们居住或旅行的环境特征之间的关系，而是通过观察功能特征（即那些导致鸟类对环境变化做出反应的特征）来研究鸟类和环境之间的因果关系。为了实现这一目标，该项目利用来自大地理区域（如欧洲）的全年数据，跟踪候鸟物种及其栖息地在夏冬范围内及其迁徙路线的关联，以确定对环境变化的反应最强烈的时间和地点，从而提高我们准确预测对环境变化反应的能力。这是一种评估人口健康的“全生命周期”方法，直到现在才由生态学研究人员进行探索。该项目的美国部分侧重于开发计算密集型机器学习方法，研究人员在处理非常大的公民科学数据集方面具有广泛的专业知识。该项目由其他国家的科学家进行的部分将由这些国家资助。这项工作除了预测整个欧洲的自然条件和人为土地使用做法的后果外，还将有助于制定新的保护战略，以应对环境变化，例如查明需要或机会改变生境保护或恢复等管理行动的目标地区。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Double machine learning trend model for citizen science data

公民科学数据的双重机器学习趋势模型

DOI：
10.1111/2041-210x.14186
发表时间：
2023
期刊：
Methods in Ecology and Evolution
影响因子：
6.6
作者：
Fink, Daniel;Johnston, Alison;Strimas‐Mackey, Matt;Auer, Tom;Hochachka, Wesley M.;Ligocki, Shawn;Oldham Jaromczyk, Lauren;Robinson, Orin;Wood, Chris;Kelling, Steve
通讯作者：
Kelling, Steve

Outstanding challenges and future directions for biodiversity monitoring using citizen science data

DOI：
10.1111/2041-210x.13834
发表时间：
2022-03-18
期刊：
METHODS IN ECOLOGY AND EVOLUTION
影响因子：
6.6
作者：
Johnston, Alison;Matechou, Eleni;Dennis, Emily B.
通讯作者：
Dennis, Emily B.

The future distribution of wetland birds breeding in Europe validated against observed changes in distribution

根据观察到的分布变化验证了欧洲湿地鸟类繁殖的未来分布

DOI：
10.1088/1748-9326/ac4ebe
发表时间：
2022
期刊：
Environmental Research Letters
影响因子：
6.7
作者：
Soultan, Alaaeldin;Pavón-Jordán, Diego;Bradter, Ute;Sandercock, Brett K;Hochachka, Wesley M;Johnston, Alison;Brommer, Jon;Gaget, Elie;Keller, Verena;Knaus, Peter
通讯作者：
Knaus, Peter

Considerations for fitting occupancy models to data from eBird and similar volunteer-collected data

将占用模型与 eBird 数据和类似志愿者收集的数据进行拟合的注意事项