Environmental DNA Analysis and Biodiversity Assessment

Module: Sustainable Tech | Difficulty: Premium

Species Detection Probability

where is per-sample detection probability and is number of samples.

Shannon Diversity Index

where is species richness and is proportion of species .

Comparison

Python Implementation

import numpy as np

class EnvironmentalGenomics:
    def __init__(self, primer_set='12S'):
        self.primer = primer_set

    def detection_probability(self, p_per_sample, n_samples):
        return 1 - (1 - p_per_sample)**n_samples

    def shannon_diversity(self, counts):
        proportions = counts / counts.sum()
        proportions = proportions[proportions > 0]
        return -np.sum(proportions * np.log(proportions))

    def sample_size_calculation(self, target_species, current_coverage, confidence=0.95):
        p = current_coverage
        z = 1.96 if confidence == 0.95 else 2.58
        n = int(np.ceil(z**2 * p * (1-p) / (0.05)**2))
        return n

    def species_accumulation(self, sample_counts, n_iterations=100):
        n_samples = len(sample_counts)
        accumulation = np.zeros(n_samples)
        for _ in range(n_iterations):
            order = np.random.permutation(n_samples)
            seen = set()
            for i, idx in enumerate(order):
                seen.add(sample_counts[idx])
                accumulation[i] += len(seen)
        return accumulation / n_iterations

Research Insight: eDNA metabarcoding can detect 80-95% of species in aquatic environments, surpassing traditional surveys.