Inﬂuence of heavy metals on nematode community structure in deteriorated T

Overview

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soil nematodes. Measured environmental variables together explained 60% of the variation in nematode as-
explained 24%. Some genera of predacious and omnivorous nematodes, which are generally expected to be
Small-scale mining produces about 80% of the Philippines’ annual and nutrient cycling (Freckman, 1988; Yeates, 2003); their abundance
disposal of wastes (van Straaten, 2000). Despite its economic con- Shao et al., 2008). Nematode responses to pollution range from sensi-
end up in the soil or river, and ﬁnally into Murcielagos Bay, a semi- area into ﬁve sampling sites – S1, S2, S3, S4 and S5 (Table 1). Five
Mean values followed by diﬀerent letters on the same row indicate signiﬁcant diﬀerences according to a post hoc Tukey HSD test (P < 0.05).
strategies, and range from 1 (colonizers, tolerant to disturbance) to 5 patterns in nematode communities. Distance-based redundancy ana-
system. MI, MI2-5, and other indices such as Structure index (SI) and at least 5% of the average dissimilarity among the sites (Mirto et al.,
of variance (ANOVA) using the Statistica software package version 7.0. sites. Median grain sizes in S2, S3 and S4 were signiﬁcantly smaller (all
Data were ﬁrst checked for normality with a Kolmogorov–Smirnov test P < 0.05) compared to S1 and S5 (Table 2). In terms of grain size, in
visualize spatial patterns of nematode assemblages. The multivariate (Fig. 2), PCO1, explaining 29.6% of the observed variation, showed that
The largest dissimilarity was between S3 and S5 (75.57%), while S1 and
S2 were the least dissimilar (63.03%), but only slightly less so than the
from the diﬀerent sampling sites in the Sibutad small-scale mining area. See tes.dbRDA1 explained 17.7% of the total variation in the nematode
Table 2 for an overview of environmental variables included in the analysis. data and generally distinguished S5 from the other four sites (Fig. 4).
accounted for 28.4% of the observed variation and positioned 2 re- negative correlation with Cd (r = −0.87) (Fig. 4B). On the other hand,
axis was positively associated with increasing Hg (r = 0.72), Fe the undisturbed sites, S1 and S2, while explaining 14.9% of variation.
mental variables explained 60.4% of the ﬁtted variation (i.e. 32.6% of
three variables, Pb, Hg and N, explained 24.5% of the ﬁtted variation of
cept the two undisturbed sites, S1 and S2 (Table 3). PERMANOVA also
were hints of subtle diﬀerences in other soil properties (e.g., OM, N, pH S4, had signiﬁcantly ﬁner grain sizes (mean of 24 µm and 28.8 µm,
to the locally higher concentrations of heavy metals, such as in S4 and Due to a lack of established allowable ranges of heavy metals in the
Table 4 from developed countries (Teh et al., 2016), except Hg when compared
Multiple genera contributed to the site diﬀerences. Listed below are all the commends an acceptable range from 0.07 mg kg−1 to 0.3 mg kg−1. In
genera contributing up to a cumulative contribution (Cum. cont. %) of ≥75%
acceptable levels as deﬁned by UNEP (2013), indicating a mining his-
Genera Average abundance Cum. cont. (%) tory in all sites except S1.
root exudates, and soil type also need to be taken into account since characteristic of the disturbed sites (Table 4). While Šalamún et al.
MI2-5) suggest a more stable and less disturbed environment (Bongers mining-related disturbance, because based on a community analysis,
nounced contribution of Eudorylaimus (> 10%). A high MI value in S5 found to be sensitive to environmental disturbance in view of their
et al., 2011; Gutiérrez et al., 2016). In fact, 40% of the nematode Dorylaimellus in the disturbed sites suggest that their distribution was
genera, and between 25 and 40% of the abundances in our study were more inﬂuenced by their host plants, rather than by metal eﬀects.
bility between replicate samples. For instance, mean diﬀerences of can increase soil microbial biomass (Alon and Steinberger, 1999). Al-
range of 0.4–38.4 ppm), resulting in much more localized pollution Gutiérrez et al., 2016). Our results suggest that not only single heavy
using acid-extractable zinc and “titrable alkalinity” values. Soil Sci. 88, 275–283. northern Tanzania. Sci. Total Environ. 259, 45–53.

Methods (brief)

Moderate pollution and their assemblages are commonly used to reﬂect soil health. In October 2014, we collected soil samples from
tailings). The lack of proper waste storage can cause Hg and tailings to Soil samples were taken in October, 2014. We divided the study
enclosed bay adjacent to the mined sites. At present, there are ap- replicate soil samples, each composed of 3 composite samples, were
proximately 500 small-scale miners in the area of Sibutad who can randomly collected with approximate interdistances of 8–10 m from
Nematodes are important biological components in the soil eco- Five replicate composite samples, each consisting of 500 g (a com-
system due to their functional roles in organic matter decomposition posite of 3 samples combined), were collected from the upper 5 cm
using a hand shovel. Soil samples were placed in ziplocked plastic bags reference or ‘external standard’ for method validation and determina-
each soil sample, 200 g were kept at 4 °C and utilized for the determi- Fe, Pb, Zn and Hg were 0.002, 0.003, 0.006, 0.01, 0.001 and
sulfuric acid (Walkey and Black, 1934). Total N was determined by the From each homogenized soil sample, 100 g was taken for nematode
(Nelson et al., 1959) and measured by Atomic Absorption Spectro- Andrássy (2005) and assigned ‘colonizer-persister’ scores according to
metry, while Hg was measured by Cold Vapor Atomic Absorption Bongers (1990, 1999). Nematodes were designated into trophic groups,
Spectrometry (CVAAS). We used empty sample cups treated in exactly namely bacterivores, fungivores, omnivores-predators and plant para-
the same way as real samples as blanks, and NIST (National Institute of sites (Pen-Mouratov et al., 2008).
independent of sample size; however, this resulted in nearly identical UK) was then used to detect diﬀerences between nematode assemblages
become proportionally more abundant under organic enrichment, and ables across samples using Pearson correlation. Similarity percentage
(r = −0.58) (Supplemental Material – ESM 1). Samples for all sites Cephalobus (r = 0.53), Pratylenchus (r = 0.49), Bursilla (r = 0.48), and
bility between replicate samples. For instance, mean diﬀerences of can increase soil microbial biomass (Alon and Steinberger, 1999). Al-
plicate samples at a single location – are usually considered high; such trend of lower N in the disturbed sites compared to S1 and S2 was

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The five most recent substantive edits to this page, classified major (evidence or structure moved), correction (a published value or statement was wrong and has been fixed), or minor (narrative rewritten without changing the underlying evidence). Each description is derived from what the edit did to this page; the linked commit is the authoritative record, routine regeneration passes are excluded, and the full version history lives in git. When DOI minting comes online (see schema docs), each entry below will also link to a version-pinned DataCite DOI.

Commit	Date	Change	Description
b01ec52c	2026-08-04	major	2 sections added
d49e450f	2026-08-03	major	5 sections added; narrative text revised