MEVE 014: Unit 04 - Inventory and Monitoring of Biodiversity

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 UNIT 4: INVENTORY AND MONITORING OF BIODIVERSITY

4.0 Introduction

The systematic inventory and monitoring of biodiversity are critical for understanding, conserving, and managing biological resources. Biodiversity includes the variety of life at the genetic, species, and ecosystem levels. By collecting and analyzing biological data, we can track species populations, detect threats, and assess the effectiveness of conservation programs. With growing biodiversity loss worldwide, inventory and monitoring have become essential tools in ecological research, policy planning, and global biodiversity assessments.

4.1 Objectives

After studying this unit, you will be able to:

  • Understand the importance and methods of biodiversity estimation.
  • Explain techniques for estimating species, genetic, and ecosystem diversity.
  • Describe data collection methods for population estimation and monitoring.
  • Analyze population and species diversity data.
  • Recognize international efforts and periodic biodiversity monitoring programs.
  • Learn about inventory database management and GIS-based approaches.

4.2 Biodiversity Estimation

Biodiversity estimation involves the quantification of various components of biodiversity, including species, genetic, and ecosystem diversity. It provides baseline data for conservation, ecological studies, and environmental management.

4.2.1 Estimation of Species Diversity

Species diversity refers to the variety and abundance of different species within a particular region or ecosystem.

4.2.1.1 Why Estimating Relative Abundance of Species is Important

  • Helps determine dominant and rare species.
  • Aids in identifying ecological balance or imbalance.
  • Useful for monitoring the effects of habitat change, pollution, or invasive species.

4.2.1.2 Species Richness and Species Diversity

  • Species Richness: The number of different species present in a given area.
  • Species Diversity: Considers both species richness and their relative abundance (evenness). Common indices include Shannon-Weiner and Simpson’s Index.

4.2.2 Estimation of Ecosystem Diversity

  • Measures the variety of ecosystems in a landscape or region.
  • Includes forests, wetlands, grasslands, deserts, marine, and agro-ecosystems.
  • Methods: Remote sensing, GIS analysis, ecological classification.

4.2.3 Estimation of Genetic Diversity

  • Examines the genetic variation within and between species populations.
  • Tools include molecular markers like RAPD, AFLP, SSR, and DNA sequencing.
  • Important for breeding programs, conservation of endangered species, and maintaining population resilience.

4.3 Population Estimation and Analysis

Understanding species populations is key to effective conservation planning.

4.3.1 The Major Ways of Collecting Data to Estimate a Population

4.3.1.1 Collection of Distribution and Occurrence Data

  • Involves mapping species’ presence/absence in different regions.
  • Used to determine habitat preference and range limits.

4.3.1.2 Population Estimation to Regularly Monitor Species under Conservation Threat (Fitness Data)

  • Collects data on reproduction, survival, body condition, and behavior.
  • Useful for endangered species management and reintroduction programs.

4.3.2 Methods to Collect Population Data

4.3.2.1 Quadrat Sampling

  • A square area is randomly placed to count species and individuals.
  • Best for vegetation and sessile organisms.

4.3.2.2 Point Count

  • Observers record all individuals seen or heard from fixed points.
  • Widely used in bird surveys.

4.3.2.3 Line Transect

  • Observer walks a line and records species along a fixed distance.
  • Useful in open habitats like grasslands or forests.

4.3.2.4 Visual Encounter Survey (VES)

  • Observer systematically searches a given area for species.
  • Commonly used for amphibians, reptiles, and mammals.

4.3.2.5 Capture-Mark-Recapture (CMR)

  • Animals are captured, marked, and released; recaptures estimate population size.
  • Used for elusive or mobile species.

4.3.2.6 Genetic Analysis

  • Uses DNA from hair, feces, or tissue to identify individuals.
  • Non-invasive and accurate for cryptic or endangered species.

4.3.3 Analyses of Population Data

4.3.3.1 Species Occurrence and Distribution

  • Analysis of where and how frequently a species is found.
  • Identifies habitat preferences and range shifts.

4.3.3.2 Species Abundance

  • Examines the number of individuals per species.
  • Helps detect population trends and potential declines.

4.4 Species Diversity & Its Measurements

4.4.1 Measuring Species Richness

  • Count of total species in an area.
  • Can be improved with sampling effort and rarefaction techniques.

4.4.2 Measuring Species Diversity

  • Combines species richness and evenness.
  • Shannon-Weiner Index (H'):

H′=−∑(pi⋅ln⁡pi)H' = -\sum (p_i \cdot \lnp_i)H′=−∑(pi​⋅lnpi​)

wherepip_ipi​ = proportion of species iii.

  • Simpson’s Index:

D=1−∑pi2D = 1 - \sum p_i^2D=1−∑pi2​

4.5 Local, Regional, National, and Global Biodiversity Estimates

4.5.1 International Biodiversity Monitoring

  • Global programs: Global Biodiversity Information Facility (GBIF), IUCN Red List, GEO BON.
  • Support data sharing, capacity building, and standardization.

4.5.2 Periodic Monitoring

  • Regular surveys to track biodiversity trends.
  • Helps evaluate conservation strategies and inform policy decisions.

4.5.3 India’s Biodiversity Initiatives

  • Biodiversity hotspots: Western Ghats, Himalayas, Indo-Burma.
  • National Biodiversity Authority (NBA), State Biodiversity Boards, People’s Biodiversity Registers (PBRs).

4.6 Inventory Database Management

Proper data management ensures long-term usability and accessibility of biodiversity information.

4.6.1 Approaches to Inventory

4.6.1.1 All Biota Taxonomic Inventory (ABTI)

  • Comprehensive listing of all known species in a region.
  • Supports taxonomic research and gap analysis.

4.6.1.2 Database Management

  • Use of structured databases (e.g., SQL) for storage and retrieval.
  • Examples: India Biodiversity Portal, GBIF.

4.6.1.3 Geographic Information System (GIS) and Image Processing

  • Mapping species distribution, habitat suitability, and changes over time.
  • Tools: QGIS, ArcGIS, satellite imagery, drone data.

4.7 Statistical Analyses

  • Essential for interpreting biodiversity and population data.
  • Techniques: ANOVA, regression, cluster analysis, ordination.
  • Software: R, SPSS, PAST, Excel.

4.8 Let Us Sum Up

  • Biodiversity monitoring involves species, genetic, and ecosystem assessments.
  • Field techniques (quadrats, transects, CMR) and molecular tools are critical for population estimation.
  • Data analysis and GIS help understand trends, threats, and guide conservation action.
  • Periodic monitoring and international databases promote coordinated biodiversity conservation.
  • Proper inventory and database management are vital for long-term ecological research and policy planning.

4.9 Keywords

  1. Species Richness – Number of species in a given area.
  2. Species Diversity – Combination of species richness and evenness.
  3. Quadrat Sampling – Method to estimate population density.
  4. Line Transect – Survey along a straight path for species count.
  5. Capture-Mark-Recapture (CMR) – Estimating population using marked individuals.
  6. Genetic Diversity – Variation of genes within a species.
  7. GIS – Tool to map and analyze spatial biodiversity data.
  8. ABTI – Comprehensive species listing initiative.
  9. Biodiversity Monitoring – Continuous tracking of biodiversity trends.
  10. Inventory – Systematic documentation of species or ecosystems.

 

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