Earthworm Density and Soil Properties across Land Uses: A Handsorting Quadrat Survey

What this study does. Earthworms are the soil's engineers: they decompose litter, restructure aggregates, and move nutrients through profiles — which is why ecologists read them as bioindicators of soil health: tillage cuts their numbers, organic amendments feed them, fallow land recovers them slowly. This project turns that ecological logic into a question answerable with a spade: how do earthworm density, biomass and community composition differ across three adjacent land uses, and which soil property explains the differences?

Thirty 0.25 m² quadrats — ten each in a cultivated field, a campus garden and fallow scrub on similar soil near the college — are sampled once, following the hand-sorting and expellant logic of ISO 23611-1, the soil-invertebrate sampling standard. Blocks are dug to 30 cm and hand-sorted on a sheet; a mustard-powder expellant then brings up deep individuals, replacing the standard's formalin with a humane alternative. Worms are counted, sorted into adults and juveniles, weighed fresh for biomass, and preserved for identification to genus or species with standard keys.

Each quadrat also yields soil data: gravimetric moisture, pH, organic matter by loss-on-ignition, bulk density and surface temperature. Density and biomass per m² are compared across land uses with a Kruskal-Wallis test (counts are rarely normal), and Spearman correlations relate worm numbers to the soil variables. The output is a small, defensible soil-zoology assessment with its sampling effort stated honestly — not a pile of worm counts.

Land around any growing Karnataka town is being converted between cultivation, gardening and fallow, but almost nothing is known about what those changes do to the soil's own fauna. Earthworms drive the decomposition and aggregation on which soil fertility depends, and their populations respond within a season to tillage, residues and moisture — yet neither the farmer nor the panchayat has any local data on them, and the Soil Health Card's chemical readings say nothing about biology.

At the student level, earthworm counts are usually demonstrated with a casually dug pit: no standard quadrat area, no fixed depth, no expellant for deep-burrowing species, no soil measurements taken alongside, and no statistics that could survive an examiner's question about sample size or normality. The result is an anecdote, not a survey.

This project therefore runs a designed quadrat survey across three land uses — cultivated, garden and fallow — with standardised sampling, a humane extraction protocol, per-quadrat soil covariates, and non-parametric analysis suited to counts. It delivers the missing local baseline: how earthworm density, biomass and community differ by land use, which soil property tracks them most closely, and with what uncertainty.

Abstract

This single-member field survey quantifies earthworm populations and their soil context across three land uses around the college: a cultivated field, a campus garden and fallow scrub. Thirty quadrats (50 × 50 cm, dug to 30 cm) are sampled once with hand-sorting followed by a mustard-powder expellant, a humane substitute for ISO 23611-1's formalin step. Earthworms are counted, staged as adult or juvenile, weighed fresh and preserved for identification with standard keys. Soil moisture, pH, organic matter (loss-on-ignition), bulk density and surface temperature are measured per quadrat. Density and biomass per m² are compared across land uses with Kruskal-Wallis tests, and Spearman correlations relate worm abundance to soil properties. The deliverable is a land-use comparison with an explicit sampling design, humane-handling protocol and honest identification limits.

Introduction

Under a square metre of healthy soil there may be dozens of earthworms and none at all under the next — the difference is made by moisture, organic matter, tillage and chemistry. Because they integrate those factors over seasons, ecologists use them as bioindicators, and ISO 23611-1 formalises the sampling. In peninsular India's soils the fauna mixes endemic megadriles with a few peregrine species, so local surveys are genuinely informative rather than textbook repeats.

Existing knowledge and the gap

Tropical earthworm ecology is well studied at research scale, and the Soil Health Card programme reports chemical parameters — but not the soil's fauna. Student projects typically count worms from two casually dug pits with no frame, no depth standard, no soil measurements and no statistics, concluding that 'earthworms like moist soil'. The gap filled here is a designed comparison: standard-area, standard-depth quadrats, a documented expellant protocol, per-quadrat soil covariates, non-parametric testing, and an honest account of what a one-season, single-observer survey can say.

Proposed study

1. Select three land uses on similar parent soil within a short radius; obtain farmer, campus and panchayat permissions in writing.
2. Lay ten quadrats per site on a rough grid, avoiding edges and recent disturbance.
3. Dig, hand-sort and expel per the protocol; count, stage, weigh and preserve worms; code every quadrat.
4. Take soil subsamples from each quadrat for moisture, pH, organic matter and bulk density; log surface temperature in situ.
5. Identify preserved adults to genus or species with keys; record what could not be identified and why.
6. Analyse: density and biomass per m² per site, Kruskal-Wallis across sites, Spearman correlations with soil variables, and a sampling-adequacy note.

Feasibility

• Technical: quadrat frames, expellant and soil tests are within B.Sc zoology practical scope; furnace access for loss-on-ignition is borrowed from the chemistry lab.
• Economic: frames, mustard powder, ethanol and containers cost under ₹700; sites are within walking or short bus distance.
• Operational: permissions are secured first, in writing. The 30-cm depth keeps effort manageable; the one-season design is declared a limitation. Worms surface when soils are moist, so sampling sits in the wet season; the season itself is recorded and compared honestly with drier-month expectations.

In scope

• Three land-use sites on similar soil, ten 0.25 m² quadrats each, one sampling season (wet season, date-stamped).
• Earthworm counts, staging, fresh biomass, preservation and key-based identification of adults.
• Per-quadrat soil properties: moisture, pH, organic matter, bulk density, surface temperature.
• Non-parametric comparison across sites and correlation with soil variables; sampling-adequacy assessment.

Out of scope

• Deep-dwelling species beyond 30 cm and below-quadrat lateral movement — the expellant partially compensates, and the limit is stated.
• Enchytraeids, termites, ants and other soil invertebrates — a separate survey family.
• Seasonal time-series and tagging experiments — one season is the declared design.
• Molecular (DNA-based) identification; microbiological soil analysis; chemical nutrient panel beyond the five measured properties.

Research design: a stratified comparative field survey with a fixed sampling protocol, per-unit covariates and pre-planned non-parametric analysis. Individual study, 14 weeks at 8 h/week, sampling in the wet season.

Phase 1 — Sites and permissions (Weeks 1–3). Three land uses are chosen on visually similar parent soil within a short radius of the college: a cultivated field (crop recorded; tillage and amendment history noted from the farmer), a campus garden/lawn (management noted), and fallow scrub (dominant plants noted). Written permission from the farmer, campus authorities and panchayat; each site mapped with a rough sketch and GPS-free landmarks.

Phase 2 — Quadrat layout and pilot (Weeks 4–5). Ten quadrats per site are laid on a rough grid spanning the plot, coded C-01…C-10, G-01…, F-01…, avoiding edges, paths and heaps. A pilot on two spare quadrats calibrates the protocol: digging time, expellant concentration and waiting time, and preservation workflow.

Phase 3 — Sampling (Weeks 6–10, one site per week with rain-date buffer). Per quadrat: (1) surface temperature logged; (2) the 50 × 50 cm frame set level; (3) soil dug in 10-cm layers to 30 cm, hand-sorted on a polythene sheet, all worms collected to ethanol vials; (4) the pit walls and base doused with mustard expellant, worms surfacing over 15 minutes collected; (5) a soil subsample bagged for lab properties; (6) bulk-density core taken. Worms are relaxed, counted, staged and weighed fresh the same day, then stored in 70% ethanol with quadrat codes.

Phase 4 — Laboratory (Weeks 9–11, interleaved). Moisture by gravimetric drying (105 °C to constant mass), pH 1:2.5 suspension with calibrated meter, organic matter by loss-on-ignition (440 °C, furnace borrowed from chemistry), bulk density from core dry mass. Adults identified to genus or species with Julka's keys and the department's reference collection; juveniles staged only.

Analysis plan (Weeks 12–13): density = count/0.25 m² → per m²; biomass similarly; per-site mean ± SD and medians; Kruskal-Wallis across the three sites with a post-hoc pairwise note; Spearman rank correlations of density and biomass against moisture, organic matter, pH, bulk density and temperature; scatter plots with jitter for counts; sampling-adequacy judged by how the per-quadrat counts distribute (many zeros discussed explicitly). All computations duplicated once in Excel as a cross-check.

Timeline: W1–3 permissions and site selection; W4–5 layout and pilot; W6–10 field sampling; W9–11 lab work; W12–13 analysis; W14 report, slides, viva.

The survey is a field-to-lab pipeline in which every earthworm count is tied to a coded quadrat and its measured soil context. The workflow below is the report's methods spine.

flowchart TD
  A["Select 3 land uses on similar parent soil"] --> B["Written permissions: farmer, campus, panchayat"]
  B --> C["Lay 10 quadrats per site on rough grid"]
  C --> D["Pilot: calibrate dig, expellant, preservation"]
  D --> E["Per quadrat: set 50 x 50 cm frame, dig 30 cm in layers"]
  E --> F["Hand-sort worms; mustard expellant for deep individuals"]
  F --> G["Count, stage, weigh fresh; preserve in 70 pct ethanol"]
  E --> H["Soil subsample + bulk-density core + surface temperature"]
  G --> I["Identify adults with keys; juveniles staged only"]
  H --> J["Lab: moisture, pH, loss-on-ignition, bulk density"]
  I --> K["Density and biomass per m2; Kruskal-Wallis across sites"]
  J --> L["Spearman correlations with soil properties"]
  K --> M["Land-use assessment with sampling-adequacy note"]
  L --> M

Data organisation

One row per quadrat: code, site, date, weather note, worm counts (adult/juvenile, by morphospecies), fresh mass per stage, expellant yield, and the five soil measurements. Density, biomass and statistics regenerate from this table; two quadrats are hand-calculated in the appendix. Identification notes (which couplets in the key decided a genus) are recorded so the examiner can retrace every name.

Core calculations (abridged)

Density (per m2)      = count / 0.25
Biomass (g per m2)    = fresh mass / 0.25
Site comparison       = Kruskal-Wallis on per-quadrat densities
Soil relationships    = Spearman rank correlation (counts vs properties)
Zero-quadrat handling = kept, never dropped; discussed as zero-inflation

Results tables to fill (no numbers are pre-filled)

• Seasonal rounds: dry-season resampling to quantify how strongly the population tracks monsoon moisture.
• Depth extension: a 60 cm pit series per site to capture deep-burrowing species the 30 cm protocol misses.
• Full soil-biology panel: enchytraeids, termites and microbial biomass for a complete bioindicator set.
• Amendment trial: a paired vermicompost-amended vs unamended plot comparison, continuing the density story into a manipulative experiment.
• Chemistry linkage: adding Soil Health Card parameters (NPK, micronutrients) through the local soil-testing lab to join the chemical and biological views.
• A one-page farmer summary in Kannada and English translating the density findings into residue-management advice, given to the panchayat.