Biodiversity Experimental Design | 生物多样性实验设计

📚 Biodiversity Experimental Design | 生物多样性实验设计

Designing experiments to measure biodiversity is a core practical skill in A-level biology. This article explores step-by-step how to plan, carry out and analyse investigations into species richness, species evenness, and diversity indices, covering quadrat sampling, transects, capture-mark-recapture, Simpson’s Index, and statistical testing.

设计测量生物多样性的实验是 A-level 生物的核心实践技能。本文逐步探讨如何计划、实施和分析关于物种丰富度、物种均匀度及多样性指数的探究活动，涵盖样方取样、样线、标记重捕法、辛普森指数和统计检验。

1. Planning a Field Experiment | 规划野外实验

Start by formulating a clear, testable research question, such as ‘Does plant species diversity differ between a mown lawn and an unmown meadow?’ or ‘How does invertebrate diversity change along a rocky shore transect?’. Define the null hypothesis (there is no significant difference in diversity) and the alternative hypothesis.

首先要提出一个清晰、可检验的研究问题，例如 ‘修剪草坪与未修剪草地的植物物种多样性是否有差异？’ 或 ‘无脊椎动物多样性如何沿着岩岸样带变化？’。确定零假设（多样性无显著差异）和备择假设。

Identify independent, dependent and control variables early. The independent variable is usually location or habitat type, while the dependent variable is a measure of diversity, such as the number of species or Simpson’s Index. Control variables might include sampling time of day, equipment type, sampler effort and weather conditions.

尽早确定自变量、因变量和控制变量。自变量通常是地点或栖息地类型，因变量是多样性的度量，如物种数或辛普森指数。控制变量可能包括一天的取样时间、设备类型、取样努力和天气条件。

Produce a detailed equipment list and a risk assessment. Typical equipment for plant sampling includes frame quadrats (0.25 m² or 1 m²), transect tape, identification guides, clipboards and a random number generator. For mobile animals you will need nets, pitfall traps, non-toxic marking materials and appropriate containers.

制作详细的器材清单和风险评估。植物取样常用器材有样方框（0.25 平方米或 1 平方米）、样带尺、鉴定指南、书写板和随机数生成器。对于移动动物，你需要捕网、陷阱、无毒标记材料及合适的容器。

2. Quadrat Sampling for Stationary Organisms | 固定生物的样方取样法

Quadrat sampling is the go‑to method for sessile or slow‑moving species, particularly plants and many intertidal animals. Choose an appropriate quadrat size – 0.25 m² frames work well for short grassland; 1 m² frames are better for woodland ground flora or sparse shrub communities.

样方取样是固着或缓慢移动物种（尤其是植物和许多潮间带动物）的首选方法。选择合适的样方大小——0.25 平方米样方适用于矮草地；1 平方米样方更适用于林地地被植物或稀疏灌木群落。

Place quadrats randomly to avoid bias. Divide the study area into a grid using two tape measures at right angles and generate coordinates with a random number table or smartphone app. For each quadrat, record every species present (species richness) and, if abundance data are needed, count individual numbers or estimate percentage cover using a point‑frame or visual assessment.

随机放置样方以避免偏差。用两条垂直的卷尺将研究区域划分成网格，用随机数表或手机应用生成坐标。对于每个样方，记录出现的每个物种（物种丰富度），如需多度数据，则统计个体数量或用点框或目测估计覆盖百分比。

The number of quadrats must be sufficient for reliable conclusions. A pilot study or species‑area curve can help determine the minimum number needed. When plotting cumulative species number against quadrat number, the curve levels off when sampling is adequate.

样方数量必须充足才能得出可靠结论。预实验或种—面积曲线可帮助确定所需最小数量。当绘制累积物种数对应样方数时，曲线趋于平缓即表明取样已充分。

3. Using Transects to Study Zonation | 使用样线研究带状分布

A belt transect or line transect is ideal when an environmental gradient exists, such as from the low‑tide mark to the high‑tide mark on a shore or from the edge of a woodland into its interior. Lay a tape measure along the gradient and place quadrats at regular intervals (systematic sampling) or continuously record every organism touching the line (interrupted belt transect).

当存在环境梯度时，如从海岸低潮线到高潮线或从林地边缘到内部，带状样带或线样带是理想选择。沿梯度铺设卷尺，按固定间隔放置样方（系统取样），或连续记录触及样线的每个生物（间断带状样带）。

This method reveals how species composition and abundance shift with changing abiotic factors like light intensity, soil moisture, salinity or trampling. Data can be displayed as kite diagrams or stacked bar charts to visualise zonation patterns.

该方法揭示物种组成和多度如何随光照强度、土壤湿度、盐度或践踏等非生物因素的变化而改变。数据可绘制成风筝图或堆积柱形图，以直观展示带状分布模式。

4. Recording Species Abundance and Evenness | 记录物种多度和均匀度

Simply counting species (richness) overlooks community structure. Two sites can have the same richness yet very different evenness if one is dominated by a single species. Abundance data can be collected as counts, percentage cover, or using semi‑quantitative scales such as the DAFOR scale (Dominant, Abundant, Frequent, Occasional, Rare).

仅计数物种（丰富度）会忽略群落结构。两个地点物种数相同，但如果其中一个由单一物种主导，均匀度则截然不同。多度数据可以采集为计数、百分比盖度或使用半定量尺度，如 DAFOR 等级（优势、丰盛、常见、偶见、稀有）。

Percentage cover is common for plants and encrusting species where individual counts are impractical. Use a point quadrat (a frame with evenly spaced pins) to record each touch as a hit; percentage cover = (number of hits for a species / total pins) × 100. For animals, direct counts or sweep‑net catches per unit effort are typical.

对于个体计数不切实际的植物和壳状物种，常用百分比盖度。使用点样方（带有均匀分布针的框架）记录每次接触为一次击中；盖度百分比 =（某物种击中数 / 总针数）× 100。对动物，常用直接计数或单位努力的扫网捕获。

5. Simpson’s Index of Diversity (D) | 辛普森多样性指数 (D)

Simpson’s Index quantifies biodiversity by accounting for both richness and evenness. The formula is:

辛普森指数通过同时考虑丰富度和均匀度来量化生物多样性。公式为：

D = 1 – Σ (nᵢ / N)²

where nᵢ = the total number of individuals of species i, and N = the total number of individuals of all species. The value ranges from 0 (low diversity, near‑monoculture) to 1 (infinite diversity in theory, but approaching 1 indicates high evenness and many species).

其中 nᵢ = 物种 i 的总个体数，N = 所有物种的总个体数。数值范围从 0（低多样性，接近单一栽培）到 1（理论上无限多样性，但接近 1 表示高均匀度和众多物种）。

Calculate Σ(nᵢ/N)² by squaring the proportional abundance of each species and summing them. Subtract this sum from 1. For example, if a sample contains 40 daisies, 30 buttercups and 30 clovers (N=100), then Σ(nᵢ/N)² = (0.4)² + (0.3)² + (0.3)² = 0.16 + 0.09 + 0.09 = 0.34, so D = 1 – 0.34 = 0.66. Always show intermediate workings in exam questions.

计算 Σ(nᵢ/N)²，即先计算每个物种的比例丰度再平方，然后求和。从 1 中减去该总和。例如，一个样本含 40 株雏菊、30 株毛茛和 30 株三叶草（N=100），则 Σ(nᵢ/N)² = (0.4)² + (0.3)² + (0.3)² = 0.16 + 0.09 + 0.09 = 0.34，因此 D = 1 – 0.34 = 0.66。考试中务必展示中间计算步骤。

6. Capture-Mark-Recapture for Mobile Species | 移动物种的标记重捕法

For motile animals such as woodlice, snails or fish, the Lincoln index provides an estimate of population size (N):

对于木虱、蜗牛或鱼类等活动的动物，林肯指数提供种群大小（N）的估计：

N = (M × C) / R

where M = number of individuals captured, marked and released in the first sample, C = total number captured in the second sample, and R = number of already‑marked individuals recaptured in the second sample. The method relies on several assumptions: marks are not lost or overlooked, marked individuals mix evenly with the unmarked population, there is no migration, no births or deaths between sampling, and the marking itself does not affect survival or catchability.

其中 M = 第一次取样捕获、标记并释放的个体数，C = 第二次取样捕获的总数，R = 第二次取样中已被标记的个体数。该方法依赖几个假设：标记不丢失或被忽略、标记个体与未标记个体充分混合、无迁移、两次取样间无出生或死亡、标记本身不影响存活或可捕性。

Practically, use non‑toxic paint or numbered tags and handle animals gently to minimise stress. Release at the exact capture point and allow sufficient time for remixing. Violation of assumptions leads to over‑ or underestimation; discuss these limitations in evaluations.

实际操作中，使用无毒涂料或编号标签，轻柔处理动物以最大限度减少胁迫。在确切捕获点释放，并给予充足的重新混合时间。违反假设会导致高估或低估；评估中应讨论这些局限性。

7. Controlling Variables and Ensuring Validity | 控制变量与确保有效性

Key abiotic variables – light intensity, temperature, soil pH, moisture content and wind speed – can strongly influence biodiversity. Measure these at each sampling point using a light meter, thermometer, soil pH probe or moisture meter, so that their effects can be separated from the habitat‑type effect.

关键非生物变量——光照强度、温度、土壤 pH、含水量和风速——会强烈影响生物多样性。在每个取样点使用光照计、温度计、土壤 pH 探头或湿度计进行测量，以便将其影响与栖息地类型的影响区分开。

Keep sampling effort identical: the same size quadrant, same time spent per quadrat, same identification criteria, and same number of net sweeps. Use the same observer(s) throughout to minimise subjective bias in plant cover estimation or animal identification.

保持取样努力一致：相同大小的样方、每个样方花费相同时间、相同的鉴定标准以及相同次数的扫网。全程使用同一个观察者（或同一组观察者），以最大限度减少植物盖度估计或动物鉴定中的主观偏差。

Conduct all fieldwork within a narrow time window to avoid diurnal or seasonal changes. If comparing two sites, sample them alternately rather than completing one site first, reducing the influence of changing weather conditions.

在较窄的时间窗口内完成所有野外工作，以避免昼夜或季节性变化。如果比较两个地点，交替取样而不是先完成一个地点，以减少天气条件变化的影响。

8. Replication, Randomisation and Reliability | 重复、随机化与可靠性

A single quadrat or one capture–recapture cycle cannot give reliable estimates. Take many replicates (e.g. at least 10–20 quadrats per site) and calculate a mean diversity index with its standard deviation or standard error. The standard error (SE = SD / √n) shrinks as sample size increases, showing improved precision.

单个样方或一次标记重捕循环无法给出可靠估计。进行多次重复（例如每个地点至少 10–20 个样方），并计算多样性指数的均值及其标准差或标准误。标准误（SE = SD / √n）随样本量增加而缩小，表明精度提高。

Randomisation is essential to avoid sampling bias. Use a random number generator to place quadrats or determine transect start points. In systematic transect sampling, randomness is introduced by choosing a random start point along the baseline before establishing the regular interval.

随机化对于避免取样偏差至关重要。使用随机数生成器放置样方或确定样线起点。在系统样带取样中，可通过在基线上选择随机起点，然后以此为基准设定固定间隔来引入随机性。

Carry out repeat runs of capture‑mark‑recapture over multiple days or sites to assess consistency. Pooled data can yield a more trustworthy population estimate and allow a discussion of the precision of the Lincoln index.

在多个日期或地点重复进行标记重捕，以评估一致性。合并数据可得出更可信的种群估计，并能讨论林肯指数的精确性。

9. Statistical Analysis of Biodiversity Data | 生物多样性数据的统计分析

When comparing two mean Simpson indices (e.g. from two habitats), a suitable test is the Mann‑Whitney U test, because biodiversity indices are often not normally distributed and based on rank‑like data. It tests the null hypothesis that there is no significant difference in median diversity between the two groups.

比较两个平均辛普森指数（例如来自两个栖息地）时，合适的检验是曼‑惠特尼 U 检验，因为生物多样性指数常不呈正态分布且基于类似秩的数据。该检验的零假设是两个组的中位数多样性无显著差异。

If the data meet parametric assumptions (normal distribution, equal variances, independent samples), a two‑sample t‑test could be used. However, always justify the choice: species count data are often skewed, making non‑parametric tests safer options. Report the U statistic, critical value at p = 0.05, and state whether the null hypothesis is rejected.

如果数据满足参数假设（正态分布、方差齐性、独立样本），可以使用双样本 t 检验。但始终要说明选择的理由：物种计数数据常有偏态，因此非参数检验更为稳妥。报告 U 统计量、p = 0.05 时的临界值，并说明是否拒绝零假设。

For investigating association between species distribution and an abiotic factor, a Spearman’s rank correlation or a chi‑squared test may be appropriate. Always link the analytical method to the experimental design and the nature of the data collected.

对于探究物种分布与非生物因子之间的关联，可采用斯皮尔曼秩相关或卡方检验。务必将分析方法与实验设计及所收集数据的性质联系起来。

10. Ethical and Safety Considerations | 伦理与安全考量

Minimise habitat disturbance by using pre‑existing paths for access and avoiding trampling rare plant communities. Return lifted stones or logs to their original positions in intertidal or woodland studies. When handling animals, wear gloves or use pooters, trays and soft brushes to reduce harm.

使用已有路径进入样地并避免践踏稀有植物群落，从而最大限度减少对栖息地的干扰。在潮间带或林地研究中，将掀开的石头或木头恢复原位。处理动物时，佩戴手套或使用吸虫管、托盘和软刷以减少伤害。

Adhere to legal protections: some species and habitats are protected under national or international legislation. Obtain necessary permits, particularly when working in nature reserves. Follow ethical guidelines such as those from the Association for the Study of Animal Behaviour (ASAB) by minimising pain, distress and time in captivity.

遵守法律保护规定：有些物种和栖息地受国家或国际法规保护。特别是在自然保护区工作时，需获取必要许可。遵循如动物行为研究协会（ASAB）的伦理指南，尽量减少疼痛、痛苦及关押时间。

Complete a thorough risk assessment before fieldwork. Consider hazards such as uneven terrain, adverse weather, deep water, sharp objects and allergic reactions to plants or stinging insects. Always work in pairs or groups and carry a first‑aid kit.

野外工作前完成全面的风险评估。考虑不平地形、恶劣天气、深水、尖锐物体以及植物过敏或刺蜇昆虫等危险因素。始终二人或多人一组工作，并携带急救包。

11. Common Limitations and How to Overcome Them | 常见局限性及克服方法

Species misidentification inflates or deflates richness measurements. Use up‑to‑date field guides and consult experts or smartphone identification apps. Photograph unknown specimens for later confirmation. Practise identification skills before the main experiment to increase accuracy.

物种错误鉴定会夸大或压低丰富度测量值。使用最新的野外指南，并咨询专家或智能手机识别应用。拍摄未知标本照片以供后续确认。在主实验前练习鉴定技能以提高准确性。

Small‑scale heterogeneity – patches of dense vegetation next to bare ground – can produce highly variable data. Increase sample size and use stratified random sampling: divide the area into visibly different sub‑habitats and randomly sample within each stratum proportional to its area.

小尺度异质性——如裸地旁边密植被斑块——可产生高度变异的数据。增加样本量并使用分层随机取样：将区域划分为外观各异的亚生境，并按其面积比例在每个层内进行随机取样。

Capture‑mark‑recapture suffers from trap‑shy or trap‑happy individuals. Use multiple trapping methods and mark discreetly. Apply a corrected Lincoln index (e.g. the Chapman estimator) for small samples: N = (M+1)(C+1)/(R+1) – 1, which reduces bias when R is low.

标记重捕法受个体陷阱回避或陷阱偏好影响。使用多种诱捕方法并谨慎标记。对小样本使用校正林肯指数（如查普曼估算式）：N = (M+1)(C+1)/(R+1) – 1，可在 R 较低时减少偏差。

12. Exam-Style Questions and Tips | 考试题型与技巧

Typical exam questions ask you to outline an experiment to compare biodiversity in two areas, evaluate a given method, or calculate and interpret Simpson’s Index. Always frame your answer around a clear aim, a justified sampling technique, control of variables, replication and a named statistical test with reasons.

典型考题要求你概述一个比较两地生物多样性的实验、评估给定方法或计算并解释辛普森指数。回答时始终围绕清晰的目标、合理的取样技术、变量控制、重复以及指定统计检验及其理由展开。

When evaluating, state both the strengths and weaknesses of quadrat or transect methods, comment on sample size, bias, and validity of abundance measurements. Suggest specific improvements such as increasing the number of quadrats, using a GPS for precise relocation, or incorporating a pilot study to refine methodology.

评估时，既要说明样方或样线方法的优点，也要指出缺点，并对样本量、偏差和多度测量的有效性进行评论。提出具体改进措施，如增加样方数量、使用 GPS 精确定位，或融入预实验以优化方法。

Practice calculating Simpson’s Index with a variety of data sets to become efficient under time pressure. Remember to show the formula, substitute values correctly, and give D to two or three decimal places. In interpretation, link the D value to the level of biodiversity and discuss what it implies about community stability and ecosystem function.

多练习不同数据集的辛普森指数计算，以在时间压力下高效作答。记住写出公式、正确代入数值，并将 D 值计算到小数点后两到三位。解释时，将 D

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Biodiversity Experimental Design | 生物多样性实验设计