Monitoring changes in species distribution and abundance is central to the sustainable management of natural resources and the definition of conservat

监测物种分布和丰度的变化对于自然资源的可持续管理和保护的定义至关重要

• 批准号: 1668473
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1668473
• 关键词: Monitoring; changes; species; distribution; abundance

Monitoring changes in species distribution and abundance is central to the sustainable management of natural resourcesand the definition of conservation goals. However for many rare, widespread and cryptic species, monitoring over largespatiotemporal scales remains a serious challenge. A growing and increasingly complex set of analytical tools exists thatcan be used to estimate the abundance, density or occupancy of species across landscapes. The technical literature onthese methods emphasises the absolute necessity of controlling statistically for variation in detectability. Without this, realtrends in abundance cannot be separated from confounding trends in detectability, potentially leading to mistakenconclusions. Robustly distinguishing variations in abundance from detectability requires that specific assumptions aresatisfied, which in turn requires rigorous design and application of field methods. In practice, this usually means thatsurveys are designed and executed by professional ecologists, and have very substantial labour costs, particularly whenexecuted over large scales.In response to this cost constraint, another strand of the monitoring literature emphasises practicality. While recognising thedesirability of robust, unbiased monitoring methods, these studies point out such approaches are pointless if they are tooexpensive to be applied over sufficiently large spatial and temporal scales to provide the information needed formanagement. This is particularly true in developing countries, where funding is usually limited and intermittent, andmanagement priorities often demand information over large areas of remote, inaccessible terrain.Tension thus exists between those advocating monitoring methods that are, above all, accurate, and those who rather emphasise long-term cost effectiveness. While monitoring methods can be both accurate and affordable in somecircumstances, the tradeoff between cost and accuracy is nonetheless a pervasive and unresolved problem in biodiversitymonitoring. One approach to more sustainable monitoring has been involving local people. The benefits of this can be twofold:reducing labour costs, and facilitating the translation of monitoring results into effective management action. However,it remains important to structure information gathering to maximise accuracy. While there are some good examples of theintegration of local participation into ecological monitoring, it remains underdeveloped, and many questions remain aboutits effective application.This study will develop a new method for monitoring widespread animal populations in developing countries; interviewbasedoccupancy analysis. We aim to: test the approach with a range of species at different levels of density and spatialdistribution; assess the sources of variation in detectability, both biophysical and observer-based; quantify trade-offsbetween cost, precision and accuracy for different species and observer types (e.g. rangers vs pastoralist vs NTFPcollectors); make recommendations for future implementation of the approach.The study will be carried out in partnership with a ZSL project in Benin, which aims to strengthen conservation of the WArly-Pendjari conservation complex, globally recognised as a conservation priority. That project aims to support ProtectedArea management and protection, improve understanding of local community use of natural resources and explore optionsfor integrating community centred resource management into land use planning. Specifically this PhD research will helpthe project meet key objectives regarding wildlife population monitoring and engaging local communities in management.More broadly this research will have widescale applicability by advancing methodologies appropriate for efficient monitoringof wildlife populations at a large spatial scale under limited time and financial resources.

监测物种分布和丰度的变化对于自然资源的可持续管理和保护目标的定义至关重要。然而，对于许多稀有、广泛和神秘的物种来说，大时空尺度的监测仍然是一个严峻的挑战。越来越多且日益复杂的分析工具可用于估计整个景观中物种的丰度、密度或占有率。关于这些方法的技术文献强调了对可检测性变化进行统计控制的绝对必要性。如果没有这一点，真实的丰度趋势就无法与可检测性的混杂趋势区分开来，从而可能导致错误的结论。强有力地区分丰度变化与可检测性需要满足特定的假设，这反过来又需要严格的设计和现场方法的应用。在实践中，这通常意味着调查是由专业生态学家设计和执行的，并且具有非常可观的劳动力成本，特别是在大规模执行时。针对这种成本限制，另一股监测文献强调实用性。虽然认识到需要稳健、公正的监测方法，但这些研究指出，如果这些方法过于昂贵而无法在足够大的空间和时间尺度上应用以提供管理所需的信息，那么这些方法就毫无意义。在发展中国家尤其如此，因为这些国家的资金通常有限且间歇性，管理重点往往需要大片偏远、难以到达的地区的信息。因此，主张准确监测方法的人和强调长期成本效益的人之间存在着紧张关系。虽然监测方法在某些情况下既准确又经济实惠，但成本和准确性之间的权衡仍然是生物多样性监测中普遍存在且尚未解决的问题。实现更可持续监测的一种方法是让当地人参与。这样做的好处是双重的：降低劳动力成本，并促进将监测结果转化为有效的管理行动。然而，构建信息收集以最大限度地提高准确性仍然很重要。虽然有一些将地方参与纳入生态监测的好例子，但它仍然不发达，并且其有效应用仍然存在许多问题。这项研究将开发一种监测发展中国家广泛分布的动物种群的新方法；基于访谈的占用率分析。我们的目标是：用不同密度和空间分布水平的一系列物种来测试该方法；评估生物物理和基于观察者的可检测性变化的来源；量化不同物种和观察者类型（例如护林员、牧民和 NTFP 收集者）的成本、精度和准确度之间的权衡；为未来实施该方法提出建议。这项研究将与贝宁的 ZSL 项目合作进行，该项目旨在加强对 WArly-Pendjari 保护综合体的保护，该综合体被全球公认为保护优先事项。该项目旨在支持保护区管理和保护，提高对当地社区对自然资源使用情况的了解，并探索将以社区为中心的资源管理纳入土地利用规划的方案。具体来说，这项博士研究将帮助该项目实现野生动物种群监测和让当地社区参与管理的关键目标。更广泛地说，这项研究将通过推进适合在有限的时间和财政资源下在大空间范围内有效监测野生动物种群的方法而具有广泛的适用性。

项目成果

Power to the people: Analysis of occupancy models informed by local knowledge

权力为民：根据当地知识分析入住模型

• DOI: 10.1111/csp2.12753
• 发表时间: 2022
• 期刊: Conservation Science and Practice
• 影响因子: 3.1
• 作者: Brittain S

Comparing interview methods with camera trap data to inform occupancy models of hunted mammals in forest habitats

将访谈方法与相机陷阱数据进行比较，以了解森林栖息地中被猎杀的哺乳动物的占用模型

• DOI: 10.1111/csp2.12637
• 发表时间: 2022
• 期刊: Conservation Science and Practice
• 影响因子: 3.1
• 作者: Brittain S

High performance machine learning models can fully automate labeling of camera trap images for ecological analyses

高性能机器学习模型可以完全自动标记相机陷阱图像以进行生态分析

• DOI: 10.1101/2020.09.12.294538
• 发表时间: 2020
• 作者: Whytock R

Robust ecological analysis of camera trap data labelled by a machine learning model

• DOI: 10.1111/2041-210x.13576
• 发表时间: 2021-02
• 期刊: Methods in Ecology and Evolution
• 影响因子: 6.6
• 作者: Robin C. Whytock;J. Świeżewski;J. Zwerts;Tadeusz Bara‐Słupski;Aurélie Flore Koumba Pambo;Marek Rogala;L. Bahaa-el-din;K. Boekee;S. Brittain;Anabelle W. Cardoso;P. Henschel;David Lehmann;B. Momboua;Cisquet Kiebou Opepa;Christopher Orbell;Ross T. Pitman;H. Robinson;K. Abernethy

Using scenarios-based interviews to predict changes in wild meat hunting and consumption in response to different alternatives projects

使用基于场景的访谈来预测野生肉狩猎和消费的变化，以应对不同的替代项目

• DOI: 10.1111/csp2.12777
• 发表时间: 2022
• 期刊: Conservation Science and Practice
• 影响因子: 3.1
• 作者: Brittain S