生物多样性 ›› 2021, Vol. 29 ›› Issue (12): 1700-1717. DOI: 10.17520/biods.2021134
收稿日期:
2021-04-12
接受日期:
2021-09-03
出版日期:
2021-12-20
发布日期:
2021-10-06
通讯作者:
李月辉
作者简介:
*E-mail: liyh@iae.ac.cn基金资助:
Received:
2021-04-12
Accepted:
2021-09-03
Online:
2021-12-20
Published:
2021-10-06
Contact:
Yuehui Li
摘要:
大中型兽类种群数量的估算是动物生态学中重要的基本问题, 受到研究者、管理者和公众的共同关注。国际上从20世纪中期开始研究该问题, 已出现了多种研究方法和相应案例, 且还在快速发展, 但世界各地仍有很多物种的种群数量尚未知晓。在我国, 从20世纪80年代开始调查大中型兽类种群数量, 取得了重要进展, 也还有很多物种的种群数量尚不清楚。因此, 有必要归纳国际上种群数量估算的研究进展, 同时, 总结国内研究的现状、优势和趋势, 供研究者参考。本文首先选择估算大中型兽类种群数量的原理、数据来源和模型这3个要素归纳出简明的研究框架, 将现有的多种方法置于其中予以阐述。在该框架下, 根据估算原理分为4大类方法, 为距离取样法、标志重捕法、基于遇见率法和遥感影像直接计数法。针对每一大类方法, 论述其基本原理模型和模型假设, 说明能实现该原理的相应数据来源(视觉观测、红外相机拍摄、DNA微卫星识别、卫星定位跟踪、声音监测或遥感影像)的特点及如何实现该原理, 评价其适用性及优缺点, 并选择其中具有可比性的方法予以比较评价。其次, 参照该研究框架, 总结我国的研究现状, 分析未来发展的优势和趋势: 我国的红外相机数据积累充分, 可以发展以此为数据源的距离取样法、标志重捕法和基于遇见率法; 发展以粪便样品为数据来源的距离取样法和粪便DNA标志重捕法; 相比地面调查数据, 获取高分辨率遥感影像数据更容易, 尽量以此估算符合适用条件的大中型兽类的种群数量。最后, 本文提出了适用于我国大中型兽类种群数量的估算方法的选择流程, 供研究者参考。
李月辉 (2021) 大中型兽类种群数量估算的研究进展. 生物多样性, 29, 1700-1717. DOI: 10.17520/biods.2021134.
Yuehui Li (2021) A review on estimating population size of large and medium-sized mammals. Biodiversity Science, 29, 1700-1717. DOI: 10.17520/biods.2021134.
估算原理 Theory | 数据来源 Data sources | 估算模型 Estimation models | 关键技术或参数 Key technology or parameter | 程序 Programs |
---|---|---|---|---|
距离取样法 Distance sampling method | 人视觉观测个体 To observe the animal individuals by insight | 距离取样模型 Distance sampling model | - | DISTANCE |
红外相机观测个体 To observe the animal individuals by infrared cameras | 距离取样模型 Distance sampling model | 动物与相机的距离 Distance between animals and cameras | ||
红外相机数据 + 卫星定位追踪数据 Infrared cameras data + satellite tracking data | 结合移动数据的距离取样法模型 Movement with distance sampling model | 跟踪数据 Satellite tracking data | ||
粪便数量和分布 Abundance and distribution of faeces | 距离取样模型 + 粪便数量与个体数量转化模型 Distance sampling model + conversion function from pellet group density to animal density | 粪便分解速率 Faeces decay rate | ||
动物鸣叫记录 Animal call records | 样点距离取样模型 Point-transect sampling model | 鸣叫个体与样点的距离Distances to detected animals | ||
标志重捕法 Capture- recapture method | 动物个体 Animal individuals | 非空间标志重捕模型 Non-spatial capture-recapture model | 非空间模型 Non-spatial capture-recapture model: Capture, Capwire, Program mark 空间模型 Spatial capture-recapture model: DENSITY, SPACECAP | |
动物DNA DNA from animal body | 非空间标志重捕模型、空间标志重捕模型 Capture- recapture model, spatial capture-recapture model | DNA微卫星技术识别个体 To distinguish by DNA microsatellite | ||
红外相机数据 Data from infrared cameras | 空间标志重捕模型 Spatial capture-recapture model | 利用照片识别个体Distinguishment of the target individuals in photos | ||
动物鸣叫记录 Animal call records | 空间标志重捕模型 + 鸣叫声数量与个体数量转化模型Spatial capture-recapture model + conversion function from call density to animal density | 个体的鸣叫次数和群体内鸣叫个体的数量比例 Call rate per individual and calling individual percentage of the group | ||
基于遇见率法 Encounter-based method | 红外相机数据 Data from infrared cameras | 随机遇见模型、随机遇见-停留时间模型、空间-事件模型、时间-事件模型 Random encounter model, random encounter and staying time model, space-to-event model, time-to-event model | 动物移动的速度 Animal movement speed | - |
遥感影像直接计数法 Direct count method from remotely sensed imagery | 高分辨率卫星遥感影像或航拍影像 Very high-resolution satellite imagery or aerial imagery | 人工目视识别计数、监督识别、非监督识别、利用多期影像识别 Manual counts, image segmentation, supervised classification, unsupervised classification, multi-temporal image classification | 从所处景观中辨别出动物个体 To detect the target individuals from background landscapes | - |
表1 大中型兽类种群数量估算方法框架
Table 1 Framework of methods estimating the population size of large and medium-sized mammals
估算原理 Theory | 数据来源 Data sources | 估算模型 Estimation models | 关键技术或参数 Key technology or parameter | 程序 Programs |
---|---|---|---|---|
距离取样法 Distance sampling method | 人视觉观测个体 To observe the animal individuals by insight | 距离取样模型 Distance sampling model | - | DISTANCE |
红外相机观测个体 To observe the animal individuals by infrared cameras | 距离取样模型 Distance sampling model | 动物与相机的距离 Distance between animals and cameras | ||
红外相机数据 + 卫星定位追踪数据 Infrared cameras data + satellite tracking data | 结合移动数据的距离取样法模型 Movement with distance sampling model | 跟踪数据 Satellite tracking data | ||
粪便数量和分布 Abundance and distribution of faeces | 距离取样模型 + 粪便数量与个体数量转化模型 Distance sampling model + conversion function from pellet group density to animal density | 粪便分解速率 Faeces decay rate | ||
动物鸣叫记录 Animal call records | 样点距离取样模型 Point-transect sampling model | 鸣叫个体与样点的距离Distances to detected animals | ||
标志重捕法 Capture- recapture method | 动物个体 Animal individuals | 非空间标志重捕模型 Non-spatial capture-recapture model | 非空间模型 Non-spatial capture-recapture model: Capture, Capwire, Program mark 空间模型 Spatial capture-recapture model: DENSITY, SPACECAP | |
动物DNA DNA from animal body | 非空间标志重捕模型、空间标志重捕模型 Capture- recapture model, spatial capture-recapture model | DNA微卫星技术识别个体 To distinguish by DNA microsatellite | ||
红外相机数据 Data from infrared cameras | 空间标志重捕模型 Spatial capture-recapture model | 利用照片识别个体Distinguishment of the target individuals in photos | ||
动物鸣叫记录 Animal call records | 空间标志重捕模型 + 鸣叫声数量与个体数量转化模型Spatial capture-recapture model + conversion function from call density to animal density | 个体的鸣叫次数和群体内鸣叫个体的数量比例 Call rate per individual and calling individual percentage of the group | ||
基于遇见率法 Encounter-based method | 红外相机数据 Data from infrared cameras | 随机遇见模型、随机遇见-停留时间模型、空间-事件模型、时间-事件模型 Random encounter model, random encounter and staying time model, space-to-event model, time-to-event model | 动物移动的速度 Animal movement speed | - |
遥感影像直接计数法 Direct count method from remotely sensed imagery | 高分辨率卫星遥感影像或航拍影像 Very high-resolution satellite imagery or aerial imagery | 人工目视识别计数、监督识别、非监督识别、利用多期影像识别 Manual counts, image segmentation, supervised classification, unsupervised classification, multi-temporal image classification | 从所处景观中辨别出动物个体 To detect the target individuals from background landscapes | - |
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