Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

15

Distribution, Diversity, and Ecological Traits of Earth-

worms in Different Habitats: Implications for Conser-

vation and Management Practices

Mohd Hassan

1,2

*

1

Senior Research Fellow, Indian Institute of Integrative Medicine, Canal Road, Jammu, India

2

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India

*Corresponding author – mohdaatief37@gmail.com

https://doi.org/10.57098/SciRevs.Biology.4.1.3

Received October 18, 2024. Revised February 01, 2025. Accepted February 04, 2025.

Abstract: The present study investigated the distribution and diversity of earthworms in five different habitats,

comprising grassland, agricultural fields, forests, wetlands, and plant-associated soil in Jammu region, Jammu

and Kashmir, India. The study analyzed various environmental factors to understand their influence on the

abundance and diversity of earthworms, which notably observed silty clay loam texture for forest, grasslands,

and plant-associated habitat sites, whereas silt loam and silty clay were characteristic of wetland habitat and

agricultural fields, respectively. The soil pH and organic carbon were highest in plant-associated soil and lowest

observed in wetland habitat site. The agricultural field recorded the highest percentage of available nitrogen

and the lowest observed in wetland. The findings revealed the distribution of 36 different types of genus/species

across all habitats in which grassland habitats exhibited the highest abundance of earthworms, with 258

numbers followed by agricultural fields with 255, forests with 137, wetlands with 75, and plant-associated

habitats with 72. Furthermore, the study demonstrated that all the earthworm species were significantly

influenced by specific environmental factors in their respective habitats. However, in environments like

agricultural fields and grasslands, soil parameters had minimal impact on species abundance. The study also

identified the dominance of different ecological traits across habitats, highlighting the importance of

morphometric traits in understanding the ecological function of earthworms in different habitats. Overall, the

results could have practical implications for conservation and management practices in these ecosystems,

providing insights into the distribution and diversity of earthworms in different habitats and their relationship

with environmental factors.

Keywords: Earthworm, Diversity, Habitats, Environmental factors, Functional traits

Introduction

Earthworms are the major dominant decom-

poser group community and play a significant role

in ecosystem functioning through ingestion, respi-

ration, and egestion (Edwards & Arancon, 2022; Ta-

gliabue et al., 2023). Their feeding and burrowing

behavior increases the surface area of organic con-

tent, which helps to convert and promote vertical

transport of organic matters in soils (Capowiez et al.,

2021). They are known as "ecosystem engineers"

due to their ability to substantially change the phys-

ical and chemical properties of their soil environ-

ment (Zhang et al., 2023). They accomplish this by

consuming large amounts of dead plant material,

which they break down in their digestive systems

and excrete as nutrient-rich castings. These castings

enhance soil fertility and structure, promoting plant

growth and nutrient cycling (Reyes et al., 2023). Ad-

ditionally, earthworms enhance soil health and

productivity by burrowing through the soil, which

improves soil aeration, water infiltration and plant

root penetration and growth (Bayon et al., 2021).

Earthworms distribute organic matter and essential

nutrients like carbon and nitrogen throughout the

soil. This process enhances soil health and fertility,

and promotes biodiversity by creating various hab-

itats for different organisms (Edwards & Arancon,

2022a; Fonte et al., 2023). As they bring all these

changes in the soil ecologist referred them as the

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

16

biological indicators of soil quality (Ansari & Ismail,

2012; Fusaro et al., 2018). Earthworms are classified

into three main ecological categories based on their

feeding and burrowing strategies (S et al., 2016).

Epigeic earthworms, characterized by their small,

cylindrical bodies, live on the soil surface and in leaf

litter, where they consume decomposing plant ma-

terial and create shallow burrows. Anecic earth-

worms, with their larger and more robust bodies,

live in deeper soil layers, creating vertical burrows

up to several meters deep, where they transport and

consume surface organic matter. Endogeic earth-

worms, which have smaller bodies than epigeic and

anecic earthworms, live and feed within the soil,

creating horizontal burrows at the soil-litter inter-

face, consuming, and mixing soil, organic matter,

and mineral particles.

To assess the impact of earthworms on ecosys-

tem services, ecological classification has been used to

link their morphological traits with their ecological

functions (Bottinelli & Capowiez, 2021;Walia & Kaur,

2024). Traditional taxonomy-based methods may not

be sufficient to explain the diverse roles of earthworms

in ecosystem functioning, therefore incorporating

functional analysis was recommended (Andriuzzi et

al., 2016). Earthworm species in functional groups

share several morphological traits, and use of these

traits may provide additional information on changes

in biodiversity and facilitate better comparison with

other geographical regions. Functional traits or attrib-

utes are the quantitative traits at individual level such

as morphological, physiological, phenological or be-

havioral features, which defines the organisms with re-

spect to its ecological roles (McGill et al., 2006; Díaz et

al., 2013). Linking taxonomic framework and func-

tional trait approach could be more effective to explain

heterogeneity in community assembly and interspe-

cific effects on ecological processes (Funk et al., 2017).

Generally functional traits analysis was used to inves-

tigate species abundance and distribution across envi-

ronmental gradients (Bernhardt‐Römermann et al.,

2011;Violle et al., 2011).

Traits can vary substantially among individuals

of a given species, during growth for example, since

adults are often 15-40 times larger than newly hatched

individuals (Lavelle, 1978). Additionally, it can shed

light on relationships between community structure

and ecosystem processes and the impacts of climate

change on species range shifts.

Hence, a functional trait framework is now re-

garded as a promising way of revealing generalities in

species distribution, community assemblages and eco-

system processes (McGill et al., 2006;Violle et al., 2007).

In this study we considered earthworm traits that are

expected to influence soil processes and measured the

values or forms taken by these traits, (Violle et al., 2007).

The traits selected influence the ability to burrow and

bioturbated (an effect trait) or, like pigmentation (likely

a response trait), to survive in the litter and the surface

environment.

We examined the earthworm community struc-

ture along the different habitat gradient using tradi-

tional diversity measures, taxonomic properties, and

the functional group concept based on biological traits

to answer the following questions:

Does the earthworm community structure and

functionality change as a result of different heteroge-

neous habitat gradient.

What are the trends and causes of variation in

the structural and functional diversity of earthworm

community throughout the different habitats of

Jammu regions; specifically, are the soil parameters the

primary cause or are other factors (such as sediment,

organic carbon, etc.) more significant?

Materials and method

Study area

The study was conducted in the Jammu region

of Jammu and Kashmir, India, in varied range of habi-

tats including Agricultural field (Old Satwari), Grass-

land (Chatha farm), Forest (Sitni Nagrota), Wetland

(Gharana wetland) and plant associated (IIIM field).

These habitats vary in their ecological characteristics

and provide unique environments for different species

for survival. Jammu is located at coordinates 32.7059°

N latitude and 74.8798° E longitude, indicating its pre-

cise geographical position. The temperature ranges

widely, fluctuating between 10-15°C during cooler pe-

riods and rising to 40-45°C during the hotter months

and the annual precipitation received in the region is

approximately 1332 mm.

Earthworm sampling

Earthworm specimens were collected by hand-

picking and digging methods from five different habi-

tats on a monthly basis. The sampling strategy fol-

lowed by selecting three stations from each habitat and

each station selected in a range of 100-400 meters apart.

However, the distance between each habitat sites

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

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varies from 2-5 km. The collected specimens were put

in the polybags labelled with habitat site and the date

of collection. In the laboratory, earthworms were

sorted from monoliths, rinsed with tap-water followed

by distilled water and gently dried with paper napkins.

Earthworms were then anesthetized with 20 % ethyl

alcohol and identified them by following the available

taxonomic keys (Stephenson, 1987; Julka, 1988). All

adult specimens were grouped by its morphology and

identified at species/genus level when possible.

Soil parameters

A differential GPS was used to measure the ele-

vation and geographic coordinates of the sample loca-

tions at the centre of the plots. Soil samples were also

collected from all habitat sites and physico-chemical

parameters were measured.

According to Baize and Jabiol's key, the coarse

material size distribution of the top 5 cm of soils was

visually evaluated on-site using gravels of various

sizes (big > 5 cm, medium > 2 cm, and small) following

the key of Baize and Jabiol (1995). Soil texture was

measured by Bouyoucos hydrometer method (Bouy-

oucos, 1962), For organic carbon (OC), and available ni-

trogen (N) measurements, soil samples were extracted

at each sampling site, homogenised and sieved at 2

mm, and measured following Chromic acid Digestion

(Walkley & Black, 1934) and Alkaline permanganate

method (Subbiah & Asija, 1956). Electric conductivity

(EC) and pH was measured by suspension method

(1:2.5) (Jackson, 1967). Bulk density was estimated by

following the Blake and Hartge method (Blake &

Hartge, 1986). Additionally, the meteorological infor-

mation, such as temperature, rainfall and humidity of

all sampling months was recorded to understand more

insight into the environment on the distribution pat-

tern of earthworms in varied ecosystems.

Functional traits and its attributes

We have measured five traits (Body length, An-

terior musculature (AM), Body Pigmentation, Ecologi-

cal category, and setae shape) of all the earthworms

and each trait was linked with certain specific ecologi-

cal function. Body length was associated with the over-

all strength and divided into two categories 10-15cm

and above 15 cm. Length was measured by fixed the

organisms in formalin. Anterior musculature (AM) is

also an indicator of burrowing ability and is well de-

veloped in deep burrowing earthworms. The differ-

ence between the body diameter prior to the clitellum,

where the AM is present, and posterior to it, when no

specific muscles are present, was used to determine the

relative strength of the AM. Based on the relative

strength of AM we divided into three categories as

poorly developed AM (0 mm), moderately developed

AM (0-4 mm) and well-developed AM (Above 4 mm).

Body pigmentation facilitates camouflage which pro-

vides protection from predators. The body was catego-

rized into three categories as uniformly pigmented,

dorsally pigmented, and non-pigmented based on

which earthworm performed different ecological strat-

egies. Earthworm mainly possessed three distinct eco-

logical categories (epigeic, anecic and endogeic) which

form a kind of ecological niche to earthworms. In our

study we selected the three main categories to under-

stand its ecosystem functioning. Setae are the chitinous

structures which help the organism to form grip with

soil while moving. We selected three categories of de-

grees of development of setae as not visible setae,

curved setae, and straight setae.

Statistical analysis

The Bray-Curtis dissimilarity (standardised,

square-root transformed) (Bray & Curtis, 1957), based

on the relative abundances of earthworm genera, and

ordination using the Jaccard similarity index, based on

presence or absence, were the two types of similarity

measures used in the species-level similarity analysis

(Clarke, 1993). Non-metric multidimensional scaling

(nMDS) plots were used to display the differences be-

tween the samples. To determine the statistical signifi-

cance of differences in pairwise comparisons of earth-

worm populations from various habitats, we used a

permutational multivariate analysis of variance (PER-

MANOVA) with two factors: "station" (all stations in

the habitat combined) and "zones" (habitats) (M. J. An-

derson, 2005; M. Anderson, 2008).

In order to show diversity, the expected number

of species in a sample, various diversity indices were

determined by using the Shannon-Wiener index (H0)

(Weaver, 1963) for species diversity by using natural

logarithm (loge), Pielou's index (Pielou, 1966) for spe-

cies evenness (J0), and Margalef's index (Margalef,

1968) for species richness (d). Principal component

analysis (PCA) was then used to identify the geograph-

ical patterns based on environmental data using envi-

ronmental variables. It was created a lower triangular

ordination related Euclidean distance matrix (Clarke &

Green, 1988). The data were examined for uniform dis-

tribution and normalised (by subtracting the mean and

dividing by the standard deviation, for each variable)

before analysis in order to prepare them for the crea-

tion of the Euclidean distance resemblance matrix. If

the distribution of the residuals was skewed, the re-

sponse variable underwent a natural logarithm

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

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modification until the best model's assumptions were

satisfied. The biota environment (BIOENV) procedure

(Clarke & Ainsworth, 1993), which computes rank cor-

relations between a similarity matrix derived from bi-

ological data and matrices derived from the environ-

mental variables, was used to examine the relation-

ships of taxonomic and functional traits with environ-

mental variables. This procedure defines a set of varia-

bles that "best explain" the biotic structure. To deter-

mine which set of environmental factors predicted the

multivariate variance in earthworm species assem-

blages, we used RELATE and a stepwise distance-

based linear model permutation test DistLM;

(McArdle & Anderson, 2001). To enable the best ex-

planatory environmental variables to be fitted into the

model, the adjusted R2 was employed as a selection

criterion. All DistLM techniques employed the Euclid-

ean distance as their similarity matrix. An analysis of

distance-based redundancy (dbRDA) was used to vis-

ualise the results (M. Anderson, 2008).

Furthermore, we used multi-level pattern anal-

ysis (De Cáceres et al., 2010) in the R environment (R

Development Core Team, 2015) with the "indicspe-

cies" function to perform the Indicator Species Analy-

sis, or IndVal (Dufrêne & Legendre, 1997) to identify

the species that would characterise the habitats com-

pared. Monte Carlo randomizations with 1000 per-

mutations were used to examine the statistical signifi-

cance of the connection between the species and site.

Dufrene and Legendre outline the specifics of the pro-

cedure (1997). The PERMANOVA+ module of the

PRIMER v6 software and the R Development Core

Team's (2015) and Dimitriadou et al., (2008) (Dimitri-

adou et al., 2008) software's procedures were used for

all of the studies (Clarke & Gorley, 2006). The taxo-

nomic and functional data set was used to create a

schematic diagram that showed the pattern in the var-

ious habitats of the Jammu region.

Results

Earthworm collection

A comprehensive sampling of earthworms was

conducted in Jammu regions from October 2020- Sep-

tember 2021 in five distint terrestrial ecosystems, in-

cluding agricultural fields, grassland, forest and wet-

land ecosystems. Inclusively across all the habitats, the

distribution of 36 different types of genus/species was

observed, and their numbers varied in all habitats.

Environmental parameters

Soil parameters estimated of all the selected hab-

itats, including agricultural fields, forests, Grasslands,

Plant-associated, Wetland ecosystems. The agricul-

tural field recorded the highest clay (46.66%) and avail-

able nitrogen (175.62 kg/hac), whereas the wetland

habitat reorded the lowest clay (6.66%), bulk density

(1.43 Mg m

-3

), and available nitrogen (62.72 kg/hac).

Plant associated soil has the highest pH (7.75) and or-

ganic carbon (2.36%), whereas the wetland habitat has

the lowest pH (6.3) and organic carbon (0.09%). Simi-

larly, Forest habitat soil estimated the highest electrical

conductivity (0.71 dS/m), whereas grassland soil ob-

served the highest sand contents (30%). The bulk den-

sity values range from 1.19 Mg m

-3

for plant-associated

habitat to 1.44 Mg m

-3

for grassland habitat (Table 1).

The soil texture varied, with silty clay loam being typi-

cal of grassland, plant-associated soil, and forest soil,

whereas silt loam and silty clay were characteristic of

wetland habitat and agricultural fields, respectively.

Table 1. Soil parameter analysis of all distinct terrestrial habitat sites

Soil parameters

Habitats

Grassland

Agricultural

field

Forest

Wetland

Plant associ-

ated

Latitude

32.6838°N

32.6624°N

32.8119°N

32.7983° N

32.7387°N

Longitude

74.8244° E

74.8302°E

74.9094° E

74.9152° E

74.8525° E

Sand %

30

26.66

14

26.65

30

Silt %

34.66

26

53.33

66.66

34.66

Clay %

33.33

46.66

32.66

6.66

35.33

pH

6.8

7.07

6.4

6.3

7.75

Ec (dS/m)

0.49

0.54

0.71

0.47

0.68

O.C. (%)

0.68

1.14

0.59

0.09

2.36

Available N

(kg/ha)

125.44

175.62

137.98

62.72

112.9

B.D. (Mg m-3)

1.44

1.35

1.29

1.43

1.19

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

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Texture Class

Silty clay loam

Silty clay

Silty clay loam

Silt loam

Silty clay loam

PCA ordination plot was constructed on five en-

vironmental parameters (Soil texture, pH, Organic car-

bon, Available N, Bulk density, electrical conductivity

(EC)) that influencing the ecological traits showed 92%

of variability in the data by PC1 and remaining was by

PC2.

Results of the DistLM based on the dbRDA plot

are displayed in Fig 2 along with information on spe-

cies abundance and soil parameter values. Sand plays

a significant role in the forest site and bulk density in

the wetland, according to the vectors of the environ-

mental variables that the DistLM procedure retained

as best explaining the model, whereas available N, clay,

and organic carbon (OC) played a significant role in the

plant-associated habitat site. However, in environ-

ments like agricultural fields and grasslands, the soil

parameters had little effect on the species abundance

(Fig.1 & 2).

Figure 1: Principal-component analysis (PCA) derived from the contribution of soil parameters in all habitats zone.

PCA plot accounted 92 % of total variation by PC1

Figure 2: Distance-based redundancy (dbRDA) bubble plot illustrating the DistLM model based on the species

assemblage data and fitted environmental variables.

To gain more insight, the meteorological infor-

mation revealed that the highest temperature was

observed in June, while the highest humidity and rain-

fall were recorded in August and July respectively (Ta-

ble 2).

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

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Table 2. Meteorological data of all the sampling months

Meteorolog-

ical infor-

mation

Sampling months

Oct-

20

Nov

-20

Dec

-20

Jan

-21

Feb-

21

Mar-

21

Apr-

21

May-

21

Jun-

21

Jul-

21

Aug-

21

Sep

-21

Avg. Tem-

perature °C

(°F)

21.6

°C

(70.

8)

°F

16.4

°C

(61.

6) °F

12

°C

(53.

6) °F

10.5

°C

(50.

8)

°F

13

°C

(55.

4)

°F

17.7

°C

(63.9

) °F

23.9

°C

(75)

°F

29.1

°C

(84.3)

°F

30.7

°C

(87.3

) °F

28.4

°C

(83.2)

°F

27.3

°C

(81.1)

°F

25.6

°C

(78.

1) °F

Min. Tem-

perature °C

(°F)

14.6

°C

(58.

3)

°F

9.6

°C

(49.

3) °F

5.4

°C

(41.

7) °F

4

°C

(39.

3)

°F

6.2

°C

(43.

1)

°F

10.1

°C

(50.2

) °F

15.5

°C

(59.9

) °F

20.3

°C

(68.6)

°F

23.5

°C

(74.3

) °F

24.4

°C

(76)

°F

23.7

°C

(74.7)

°F

20.7

°C

(69.

2) °F

Max. Tem-

perature °C

(°F)

28.8

°C

(83.

8)

°F

23.8

°C

(74.

8) °F

19.1

°C

(66.

3) °F

17

°C

(62.

6)

°F

19.6

°C

(67.

3)

°F

25

°C

(77)

°F

31.6

°C

(88.8

) °F

36.5

°C

(97.7)

°F

36.7

°C

(98.1

) °F

32.4

°C

(90.4)

°F

31 °C

(87.9)

°F

30.5

°C

(87)

°F

Rainfall

(mm)

17

25

46

74

129

113

71

29

108

321

265

115

Humidity

(%)

62%

66%

70

%

67%

58%

41%

33%

43%

74%

81%

76%

Diversity indices and species richness

A total of 36 earthworm genus/species be-

longing to different families were found across all

the habitats. The highest diversity and abundance

of earthworms were observed in grassland habitats,

followed by agricultural fields, forests, wetlands,

and plant-associated habitats (Table 3). The most

dominant species found across all habitats was Ei-

senia fetida with the density of 72 ind. per m

2

fol-

lowed by Bimastos rosea with the density of 36 ind.

Per m

2

and

Lampito mauritii with the density of 35

ind. Per m

2

. Some species, including Millsonia

anomala, were exclusively found in single habitat,

such grasslands, whereas Dichogaster saliens,

Metaphire posthuma, Octolasion lacteum, and Pel-

logaster bengalensis were found in both agriculture

areas and grassland habitats. Similarly, Allolobo-

phora parva and Amynthas diffringens were only

found in agriculture fields and forests, however, no

restricted species were found in wetlands or plant-

associated habitats.

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

21

Table 3. Earthworm abundance data collected across five different habitats revealing grassland exhibited

the highest richness in terms of numbers

Serial No.

Species numbers

Habitats

Grassland

Agricultural

field

Forest

Wetland

Plant as-

sociated

1

Allolobophora parva

0

7

4

0

2

Amynthas diffringens

0

9

3

0

3

Amynthas morrisi

11

9

4

3

4

Amynthas spp.

13

0

3

0

5

Aporrectodea caliginosa

0

8

4

5

0

6

Aporrectodea rosea

9

6

7

8

6

7

Dendrobaena octaedra

10

7

8

5

0

8

Dichogaster bolaui

0

8

5

0

7

9

Dichogaster saliens

11

8

0

10

Drawida calebi

9

4

6

4

11

Drawida ghilarovi

0

5

3

4

12

Drawida willsi

4

9

0

3

13

Eisenia fetida

21

23

9

10

14

Eudrilus eugeniae

8

10

3

0

3

15

Eutyphoeus incommodus

0

10

9

5

0

16

Eutyphoeus nicholsoni

12

10

5

0

17

Eutyphoeus sp.

9

3

0

4

18

Eutyphoeus waltoni

11

7

0

4

5

19

Lampito mauritii

8

11

6

7

3

20

Lennogaster pusillus

10

12

0

5

6

21

Lumbricus rubellus

7

6

0

5

22

Lumbricus terrestris

8

6

12

4

0

23

Metaphire posthuma

9

8

0

24

Millsonia anomala

9

0

25

Octochaetona beatrix

8

9

4

3

2

26

Octochaetona serrate

8

9

5

0

27

Octochaetona surensis

3

6

0

28

Octolasion lacteum

11

2

0

29

Pellogaster bengalensis

9

6

0

30

Perionyx excavates

7

4

0

31

Perionyx gravely

6

5

0

2

32

Perionyx sansibaricus

7

5

0

5

0

33

Pheretima alexandri

7

4

6

0

34

Polypheretima elongata

10

13

10

0

35

Pontodrilus bermudensis

3

8

4

0

4

36

Pontoscolex corethrurus

5

6

9

4

As per the Bray–Curtis nMDS similarity index of

earthworm abundance and presence/absence data, it

clearly illustrates that all habitats were differ to each

other; the explored habiats were 40% dissimilar to each

other, except for agriculture fields and forests, which

were 30% dissimilar in terms of their taxonomic abun-

dance however, agriculture field and grassland habi-

tats were resembled 80% to each other with respect to

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

22

species abundance and presence/absence of species

(fig. 3 & 4). Amynthas sp had the highest contribution to

similarity within agriculture field and grassland habi-

tats with 10.07% similarly D. saliens, E. waltoni and O.

lacteum had the highest contribution to similarity

within grassland and forest with 5.6% and the mean

dissimilarity value was 40.38%. In agriculture field and

forest the SIMPER analysis showed that L. pusillus was

the highest contribution to similarity with the value of

7.69% and the average dissimilarity value was 30.04%.

Species E. nicholsoni had the highest value of similarity

within grassland and wetland habitats with 5.36% and

the average dissimilarity value between them was

52.86%, in agriculture field and wetland P elongate

showed the highest contribution value to similarity

with 5.61% and the average dissimilarity value was

51.11%. In habitats forest and wetland P. elongata

showed the highest contribution to similarity with the

value of 8.23% and the mean dissimilarity value be-

tween the habitats was 40.74% whereas Amynthas sps

had the highest similarity contribution value of 6.01%

within grassland and plant associated habitats and the

mean dissimilarity value was 50.54%.

Figure 3: nMDS ordination based on earthworm species presence or absence according to the Bray-Curtis similarity

index.

Figure 4: nMDS ordination-based Bray-Curtis similarity index to estimate the degree of similarity in species

abundance

The SIMPER dissimilarity value between agri-

culture field and plant associated was 47.68% and

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

23

highest value of similarity contribution which is 6.01%

was by Polypheretima elongate, whereas the highest sim-

ilarity contribution within forest and plant associated

habitats was contributed by L. terrestris by the value of

7.45% and the average dissimilarity value was 49.24%.

In wetland and plant associated the highest contribu-

tion to similarity was observed by D bolaui and the av-

erage dissimilarity value of 42.21% was observed be-

tween the habitats. The details of SIMPER analysis

were described in the Table 4.

Table 4. Simper anlysis of earthworms across all habitats

Average dissimilarity between grassland (GL) and agricultural field (AF) (20.11%)

Serial

No.

Species

Avg. abun-

dance (GL)

Avg. abun-

dance (AF)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Amynthas spp.

3.61

0

2.03

10.07

2

Eutyphoeus incom-

modus

0

3.16

1.78

8.83

18.9

3

Amynthas dif-

fringens

0

3

1.69

8.38

27.28

4

Millsonia anomala

3

0

1.69

8.38

35.66

5

Aporrectodea caligi-

nosa

0

2.83

1.59

7.9

43.56

Average dissimilarity between grassland (GL) and forest (F) (40.38%)

Serial

No.

Species

Avg. abun-

dance (GL)

Avg. abun-

dance (F)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Dichogaster saliens

3.32

0

2.26

5.6

2

Eutyphoeus waltoni

3.32

0

2.26

5.6

11.21

3

Octolasion lacteum

3.32

0

2.26

5.6

16.81

4

Lennogaster pusillus

3.16

0

2.16

5.34

22.16

5

Eutyphoeus incom-

modus

0

3

2.05

5.07

27.22

Average dissimilarity between agricultural field (AF) and forest (F) (30.04%)

Serial

No.

Species

Avg. abun-

dance (AF)

Avg. abun-

dance (F)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Lennogaster pusillus

3.46

0

2.31

7.69

2

Drawida willsi

3

0

2

6.66

14.35

3

Dichogaster saliens

2.83

0

1.89

6.28

20.62

4

Metaphire posthuma

2.83

0

1.89

6.28

26.9

5

Eutyphoeus waltoni

2.65

0

1.76

5.87

32.77

Average dissimilarity between agriculture field (AF) and wetland (WL) (51.11%)

Serial

No.

Species

Avg. abun-

dance (AF)

Avg. abun-

dance (WL)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Polypheretima elon-

gata

3.61

0

2.87

5.61

2

Eudrilus eugeniae

3.16

0

2.51

4.92

10.53

3

Eutyphoeus nichol-

soni

3.16

0

2.51

4.92

15.45

4

Amynthas dif-

fringens

3

0

2.39

4.67

20.12

5

Drawida willsi

3

0

2.39

4.67

24.79

Average dissimilarity between forest (F) and wetland (WL) (40.74%)

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

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Serial

No.

Species

Avg. abun-

dance (F)

Avg. abun-

dance (WL)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Polypheretima elon-

gata

3.16

0

3.35

8.23

2

Octochaetona suren-

sis

2.45

0

2.6

6.38

14.61

3

Pheretima alexandri

2.45

0

2.6

6.38

20.98

4

Dichogaster bolaui

2.24

0

2.37

5.82

26.8

5

Eutyphoeus nichol-

soni

2.24

0

2.37

5.82

32.62

Average dissimilarity between grassland (GL) and Plant associated (PA) (50.54%)

Serial

No.

Species

Avg. abun-

dance (GL)

Avg. abun-

dance (PA)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Amynthas spp.

3.61

0

2.94

5.82

2

Eutyphoeus nichol-

soni

3.46

0

2.83

5.6

11.42

3

Dichogaster saliens

3.32

0

2.71

5.36

16.78

4

Octolasion lacteum

3.32

0

2.71

5.36

22.14

5

Dendrobaena octae-

dra

3.16

0

2.58

5.11

27.24

Average dissimilarity between agricultural field (AF) and plant associated (PA) (47.68%)

Serial

No.

Species

Avg. abun-

dance (AF)

Avg. abun-

dance (PA)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Polypheretima elon-

gata

3.61

0

2.86

6.01

2

Eutyphoeus incom-

modus

3.16

0

2.51

5.27

11.27

3

Eutyphoeus nichol-

soni

3.16

0

2.51

5.27

16.54

4

Amynthas dif-

fringens

3

0

2.38

5

21.54

5

Octochaetona ser-

rate

3

0

2.38

5

26.53

Average dissimilarity between forest (F) and Plant associated (PA) (49.24%)

Serial

No.

Species

Avg. abun-

dance (F)

Avg. abun-

dance (PA)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Lumbricus terrestris

3.46

0

3.67

7.45

2

Polypheretima elon-

gata

3.16

0

3.35

6.8

14.24

3

Eutyphoeus incom-

modus

3

0

3.18

6.45

20.69

4

Dendrobaena octae-

dra

2.83

0

2.99

6.08

26.77

5

Lennogaster pusillus

0

2.45

2.59

5.27

32.04

Average dissimilarity between wetland (WL) and plant associated (PA) (42.21%)

Serial

No.

Species

Avg. abun-

dance (WL)

Avg. abun-

dance (PA)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Dichogaster bolaui

0

2.65

3.77

8.93

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

25

2

Aporrectodea caligi-

nosa

2.24

0

3.18

7.54

16.47

3

Dendrobaena octae-

dra

2.24

0

3.18

7.54

24.01

4

Eutyphoeus incom-

modus

2.24

0

3.18

7.54

31.55

5

umbricus rubellus

0

2.24

3.18

7.54

39.1

Average dissimilarity between grassland (GL) and wetland (WL) (52.86)

Serial

No.

Species

Avg. abun-

dance (GL)

Avg. abun-

dance (WL)

Avg.dissim-

ilarity

Similarity

Contribution

%

Cum.%

1

Eutyphoeus nichol-

soni

3.46

0

2.83

5.36

2

Dichogaster saliens

3.32

0

2.71

5.13

10.49

3

Octolasion lacteum

3.32

0

2.71

5.13

15.62

4

Polypheretima elon-

gata

3.16

0

2.59

4.89

20.51

5

Eutyphoeus sp.

3

0

2.45

4.64

25.15

The IndVal index produced a list of indicator

species for each group of sites: Millsonia anomala (p =

0.005; statistical value: 0.751) was a greater indicator of

the grassland, whereas Allolobophora parva sp. was

strongly correlated (p = 0.005; statistical value: 0.950)

with the agriculture. Lumbricus terrestris (p = 0.005; sta-

tistical value: 1.000) was significantly associated with

the forest. The conditional probability or positive pre-

dictive value of the species and the conditional proba-

bility of finding the species at sites and those species

with the highest IndVal value for the set of all the sam-

ples from each habitat (e.g. Amynthas spp., Octolasion

lacteum, Dichogaster saliens, Polypheretima elongate).

However, the species like Eisenia fetida, Aporrectodea

rosea, Drawida calebi, Lampito mauritii, Lumbricus ter-

restris, Octochaetona beatrix were not amenable to statis-

tical testing because of the lack of an external group for

comparison.

The five habitats differed significantly in the di-

versity indices, with grassland having the highest spe-

cies richness (S) with 29 species, and the wetland

recorded the lowest richness with 15 species. The high-

est abundance (N) was also observed in the grassland

(258), and the lowest in the wetland (75). Density (d)

refers to the number of individuals per unit area,

where grassland has a density of 0.03921, which is rel-

atively low compared to wetland with 0.0752. Even-

ness (J') measures how evenly the individuals are dis-

tributed across the species. Values close to 1 indicate

even distribution, and values closer to 0 indicate more

dominance by a few species. All habitats have high

evenness, ranging from 0.9608 (grassland) to 0.9248

(wetland). Shannon-Weiner Index (H'): The diversity

index considers both species richness and evenness,

with grassland observed to have the highest diversity

with an H' value of 3.301, and the wetland has the low-

est with 2.647. Similarly, Simpson’s Index of Diversity

(1 – Lambda) estimates the probability that two indi-

viduals randomly selected from the sample belong to

different species. Higher values indicate higher diver-

sity, where grassland and agricultural fields observed

the highest values, 0.9608 and 0.9622, respectively, in-

dicating more diversity (Table 5).

Table 5. Average values of diversity indices in each habitat

Habitats

Diversity indices

S

N

d

J'

H'(loge)

1-Lambda'

Grassland

29

258

0.03921

0.9805

3.301

0.9608

Agricultural field

32

255

0.03782

0.9733

3.373

0.9622

Forest

24

137

0.04854

0.9761

3.102

0.9515

Wetland

15

75

0.0752

0.9774

2.647

0.9248

Plant associated

16

72

0.07446

0.9683

2.685

0.9255

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

26

Functional traits analysis

In this study, five morphometric traits were se-

lected (ecological category, body length, setae shape,

development of anterior musculature, and body color)

and their association with ecological function in earth-

worms was investigated. Based on the three ecological

categories, it was revealed that epigeic earthworms

were typically uniformly pigmented, had medium

body length, poorly developed anterior musculature,

and straight setae. In contrast, anaeic earthworms were

characterized by a dorsally pigmented body, smaller

body length, well-developed anterior musculature,

and curved setae. Edogeic earthworms, on the other

hand, were non-pigmented, had large body size, well

developed anterior musculature and well-developed

straight setae. These results suggest that morphometric

traits can provide valuable information about the eco-

logical function of earthworms.

Our analysis of earthworms in the agricultural

field habitat revealed that the dominant traits were

epigeic, large body length, not visible setae, poorly de-

veloped anterior musculature, and uniformly pig-

mented body. The epigeic earthworms were closely as-

sociated with traits such as uniformly pigmented, not

visible setae and weak anterior musculature (AM). In

contrast, anaeic earthworms were characterized by

dorsally pigmented body and curved setae (Fig. 5).

Similarly, endogeic earthworms were identified as

non-pigmented, with straight setae and well-devel-

oped anterior musculature (Fig. 5). These observations

suggest that morphometric traits can provide valuable

insights into the characteristics of earthworms in dif-

ferent habitats. Similarly, in grassland habitats, anecic

and endogeic earthworms were found to be dominant,

with moderate body length, non-developed or well-

developed anterior musculature (AM), not visible or

curved setae, and dorsally pigmented or non-pig-

mented bodies. Endogeic worms were characterized

by non-pigmented bodies, straight setae, and

welldeveloped anterior musculature, while anecic spe-

cies were characterized by dorsally pigmented bodies

and curved setae. The traits of uniformly pigmented,

not visible setae, and weak anterior musculature

closely resembled those of epigeic earthworms (Fig. 6).

Figure 5: Traits distribution pattern in agricultural field

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

27

Figure 6: Traits distribution pattern in grassland habitat

Forest habitat was not dominated by any specific

trait; however, endogeic traits were found in lower

numbers, while the remaining traits were found in

moderate numbers. According to the Bray-curtis

nMDS similarity index (Fig.7), trait attributes like dor-

sally pigmented body, curved setae, and developed

AM were associated with anecic species, while trait at-

tributes like uniformly pigmented body, not visible se-

tae, and weak AM were associated with epigeic species.

Endogeic species shared a well-developed AM,

straight setae, and a non-pigmented body. The distri-

bution pattern of traits is shown in Fig. 7.

Figure 7: Traits distribution pattern in forest ecosystem

In wetland ecosystem the endogeic trait catego-

ries earthworms were absent and the remaining traits

were found to be in lower numbers. The distribution

pattern of traits revealed that epigeic species were

associated with uniformly pigmented, poorly devel-

oped anterior musculature (AM), and non-visible setae,

anecic species with dorsally pigmented body, moder-

ately developed anterior musculature (AM) and

curved setae, whereas endogeic species were

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

28

attributed by non-pigmented body and strong straight

setae. Figure 8 depicts the pattern of trait distribution.

We discovered that species with endogeic traits were

absent from plant associated sites, and the remaining

ecological traits were in short supply. However, the

distribution pattern revealed that uniformly pig-

mented and not visible setae were closely related to

epigeic worms, whereas dorsally pigmented, curved

setae, and moderately developed AM were closely re-

lated to anecic species. Endogeic earthworms were as-

sociated with non-pigmented bodies and straight setae,

as with other habitats (Fig. 9)

Figure 8: Traits distribution pattern in wetland ecosystem

Figure 9: Traits distribution pattern in plant associated habitat

The schematic model represents the exact trend

of each functional trait of each habitat. The relative

abundance of each trait was plotted as an area graph,

and a schematic figure was prepared to show the

pattern according to the habitats. For example, the ag-

riculture field and grassland habitats favour the dom-

inance of all ecological traits whereas forest, wetland

and plant associated ecosystems were not favouring

the dominance of any trait (Fig. 10).

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

29

Figure 10: Schematic model illustrating the functional traits distribution pattern of earthworms in each habitat

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

30

Graphical abstract

Discussion

The highest and lowest abundance and diversity

of earthworms were observed in grassland site and

plant associated habitat site respectively. The earth-

worm abundance in all the habitats vary in number

ranging from only few individuals to more abundant,

which depends on the physicochemical characteristic

of the soil and the climatic condition of that habitat

(Kale & Karmegam, 2010; Lee, 1985). The results of the

DistLM analysis indicate that soil parameters play a

significant role in determining species abundance in

various environments. In forest and wetland habitats,

the presence of sand and bulk density, respectively,

have the greatest impact. In a study, Yvan et al., (2012)

observed that soil texture influences the activity and

growth of earthworm (Yvan et al., 2012). In the current

study we observed higher clay content favors the

growth and abundance of earthworm which similarly

reported in the study of Singh et. al., (2021) (Singh et al.,

2021). Meanwhile, available N, clay, and organic car-

bon are important factors in plant-associated habitats.

Agricultural fields and grasslands, on the other hand,

show little effect from soil parameters on species abun-

dance. Soil properties such as texture and pH can vary

significantly across habitats, with agriculture fields

having the highest sand and clay content and wetland

having the highest silt content. Higher clay content and

slightly alkaline pH (near 8.07) were found to promote

earthworm growth and abundance in this study, simi-

lar to findings by other researchers. Most studies show

that earthworms can thrive in a pH range of 5.0 to 8.0,

with neutral pH promoting the greatest abundance

(De Wandeler et al., 2016).

The levels of organic carbon and available N

play a crucial role in determining earthworm abun-

dance and diversity across habitats, as highlighted by

several studies in the literature (Xie et al., 2022). Our

study found that the highest levels of organic carbon

and available N were present in agricultural fields and

were associated with increased earthworm abundance

and diversity (Bartz et al., 2013; Jänsch et al., 2013). This

observation is consistent with the findings of several

studies that have reported a positive relationship be-

tween soil organic carbon content and earthworm pop-

ulations (Bartz et al., 2013; Jänsch et al., 2013) However,

the relationship between organic carbon levels and

earthworm populations is not always straight forward

(Lavelle & Spain, 2001). In our study, we also found

that plant-associated soil had high levels of organic car-

bon, but earthworm abundance and diversity were

low. This finding is in line with the results of other

studies, which have shown that earthworm popula-

tions are influenced by a range of factors, including soil

structure, pH, and nutrient availability (De Wandeler

et al., 2016). Moderate to high rainfall, temperature and

humidity promote the earthworm abundance that

might be favoring their metabolic and reproductive

rate.

Similarly, our study found that earthworm pop-

ulations were abundant and diverse in grasslands, de-

spite low organic carbon levels. This observation

Science Reviews - Biology, 2025, 4(1), 15-35 Мohd Hassan

31

supports the idea that earthworms can thrive in a

range of conditions, as long as other essential factors,

such as soil structure and nutrient availability, are fa-

vorable(De Wandeler et al., 2016). The results indicate

that soil parameters and earthworm species play a cru-

cial role in shaping earthworm populations in different

habitats. The specific patterns of earthworm diversity

and abundance varied among habitats, suggesting that

soil parameters and earthworm species interact differ-

ently in different habitats. Overall, all habitats were

found to be significantly different from each other, em-

phasizing the importance of considering the unique

characteristics of each habitat when studying earth-

worm populations.

The findings of the study provide insight into

the distribution of earthworm species and their abun-

dance across different habitats. The study showed

that grassland habitats had the highest levels of earth-

worm diversity and abundance followed by agricul-

tural fields, forests, wetlands, and plant-associated

habitats. This highlights the important role that differ-

ent habitats play in shaping earthworm populations.

The significant observation was the dominance of Ei-

senia fetida as the most common species across all hab-

itats. Hussain et al. (2022) also reported similar find-

ings, suggesting the resilience and adaptability of E.

fetida in different climatic conditions and its high re-

productive rate as key factors contributing to its dom-

inance (Hussain et al., 2022).

Additionally, the study found that certain spe-

cies, such as Millsonia anomala, were only present in

specific habitats, whereas, Dichogaster saliens,

Metaphire posthuma, Octolasion lacteum and Pellogaster

bengalensis, were found in multiple habitats. This spe-

cies-specific distribution was previously reported in

studies of earthworm species compositions in various

grassland, agricultural, and forest soils (Satchell, 1983).

Apart from taxonomic information studying

morphological traits of earthworms helps us to under-

stand the adaptation of earthworms to different habi-

tats and to know the specific function of earthworms in

each habitat (Blakemore, 2000). This can lead to a better

understanding of the role of earthworms in maintain-

ing soil health and fertility, and their importance as in-

dicator of soil quality (Satchell, 1983). The morpholog-

ical traits of earthworms, such as body length, setae

shape, development of anterior musculature (AM),

and body color, are directly related to their ability to

perform specific functions, such as burrowing and

feeding within the soil ecosystem. By understanding

the correlation between morphological traits and eco-

logical function, researchers can better understand the

role that earthworms play in maintaining soil health

and fertility.

The morphological traits of earthworms are im-

portant to study because they are related to their eco-

logical function. It has been found that different eco-

logical categories of earthworms, such as epigeic, an-

ecic, and edogeic, were characterized by different mor-

phological traits, such as body pigmentation, body

length, development of anterior musculature, and se-

tae shape. These morphological traits are associated

with different functions such as protection from pred-

ators, burrowing, and camouflage etc (Hsu et al., 2023).

For example, epigeic earthworms were uni-

formly pigmented and had medium body length,

poorly developed anterior musculature, and not visi-

ble setae, which were adaptations for their surface-

dwelling lifestyle. Anecic earthworms were dorsally

pigmented, had smaller body length, well-developed

anterior musculature, and curved setae, which were

adaptations for their burrowing lifestyle. Edogeic

earthworms were non-pigmented, had large body size,

well-developed anterior musculature, and straight se-

tae, which adapted for the deep soil burrowing lifestyle.

The study was conducted by consulting the previous

studies of Bouche (1977) who investigated the influ-

ence of body size on the burrowing activity of earth-

worm (Bouché, 1977) and Marichal et al. (2017) who in-

vestigated the impact of morphological traits on the

burrowing and foraging behaviors (Marichal et al.,

2017). Some other studies conducted by Satchell (1983),

and Julka and Senapati (1987), explored the relation-

ship between earthworm species composition and

habitat type. These studies provided a foundation for

understanding the role of morphological traits in

earthworm ecology and highlighted the need of fur-

ther research in this area. the results of this study pro-

vide important insights into the relationship between

morphological traits and ecological function in earth-

worms and contribute to our understanding of earth-

worm diversity and distribution in different habitats.

Further research is needed to fully understand the

mechanisms driving the evolution of these traits and

their impacts on earthworm populations and ecosys-

tem functioning (Satchell, 1983;Julka & Senapati, 1987).

In the present study, it was observed that the

morphometric traits of earthworms vary depending

Мohd Hassan Science Reviews - Biology, 2025, 4(1), 15-35

32

on their habitat. Previously numerous studies were

conducted to understand the the relationship be-

tween earthworm morphology and habitat (Edwards

et al., 1995)(Marichal et al., 2017). In the case of agri-

cultural fields, earthworms were found with inclined

traits such as epigeic, uniformly pigmented bodies,

not visible setae, and weak anterior musculature. The

presence of these traits supports the presence of high

organic content in the upper soil surface. This is be-

cause of the frequent tillage practices that increase the

organic matter inputs into the soil (Edwards et al.,

1995). In contrast, grasslands favor anecic and en-

dogeic earthworms, which display a range of traits,

including moderate body length to large body length,

non-developed to well-developed anterior muscula-

ture, and dorsally pigmented to non-pigmented bod-

ies (Edwards et al., 1995). This dominance of anecic

and endogeic earthworms in grasslands might be due

to the low risk of predators and disturbance from an-

thropogenic activities, compared to agricultural fields.

Forests were observed with no dominance of any spe-

cific trait, whereas wetland habitats lack endogeic spe-

cies due to anoxic conditions created by deep ground

water (Edwards et al., 1995).

Additionally, the distribution of morphometric

traits varied depending on the habitat, with endogeic

earthworms being absent from plant-associated sites.

Epigeic earthworms were closely related to uniformly

pigmented bodies, not visible setae, and weak ante-

rior musculature, while anecic earthworms were

closely related to dorsally pigmented bodies, curved

setae, and moderately developed anterior

musculature. Endogeic earthworms were closely re-

lated to non-pigmented bodies and straight setae

(Marichal et al., 2017). Further, this study highlights

the importance of morphometric traits in determining

the ecological function of earthworms and the inclina-

tion towards their habitat.

Conclusion

This study provides a comparative and compre-

hensive understanding of the distribution pattern of

earthworms and their morphometric traits across dif-

ferent terrestrial ecosystems. The study revealed that

grassland habitats had the highest levels of earthworm

diversity and abundance, followed by agricultural

fields, forests, wetlands, and plant-associated habitats.

The earthworm community structure and functional-

ity are influenced by diverse habitat gradients, with

species composition and abundance varying signifi-

cantly across different habitat types, indicating envi-

ronmental responsiveness. The study emphasizes the

role of soil parameters like texture, pH, organic carbon,

and nitrogen in determining earthworm populations.

It observes Eisenia fetida as the most common species

and highlights the species-specific distribution of

earthworms. It also highlights the importance of un-

derstanding earthworm morphological traits and their

adaptation to different environmental conditions.

Acknowledgement: The author gratefully

acknowledges the Director CSIR- Indian Institute of

Integrative Medicine (IIIM), for his constant support

and the facilities provided to carry out this work. I also

express my sincere gratitude to my supervisor Dr.

Ravail Singh for allowing me to communicate the

present manuscript as single author.

References

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Primer-E Limited.

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