Results
Overall fish diversity
We recorded a total of 29 benthic species during 252 surveys over the
three-year study. Raw sample species richness ranged from 0 to 13 and
average richness at sites was 4.2. There were two occasions that we
recorded no fish and these events were discarded in the analysis. The
inter- and intra- annual differences in richness were not significant (p
= 0.411 and 0.542 for monthly and annually richness, t-test), however,
the richness difference between habitat types was significant with more
species recorded at natural sites (Carex sedges and open waters)
than at plantation sites (t-test, p = 0.002 and <0.001 forCarex sedges and open waters, respectively). For abundance,
although there was no significant inter-annual difference (p = 0.452,
t-test), the catch was significantly higher in May than other months (p
= 0.028, t-test), coincident with the breeding season. In contrast to
richness, fish abundance at Carex sedge sites was significantly
higher than that at plantation sites (P <0.001, t-test) and
open water sites (P = 0.044, t-test), which had comparable abundance (p
= 0.200, t-test).
Temporal community variation and its
drivers
Synchrony, variance ratio and stability varied greatly across habitat
types and between sampling years (Table 1). The total β-diversity showed
great spatial and temporal variations (Table 1). Specifically, the
temporal variation of benthic fish communities was significantly lower
in the flooding year (i.e. 2017) than in normal years (i.e. 2018 and
2019) (p < 0.01, t-test). In plantations, the total
temporal β-diversity was significantly lower than open waters andCarex sedges (p < 0.01, t-test). Although the
difference in temporal β-diversity was significant (p = 0.04,
t-test) in the flooding year, it became non-significant in normal years.
The best model fitted for temporal β-diversity included water total
phosphorus concentration (TP) and habitat type. This model explained
68% of the variations of β-diversity across the sampling sites (Table
2). The estimated model coefficient indicated that temporal β-diversity
decreased significantly among the TP gradients, and was significantly
lower in plantations than in the natural habitat of Carex sedges
and open waters.
The observed synchrony of fish abundance ranged from 0.09 to 0.90, and
in 10 occasions out of the total of 36, the synchrony was significantly
greater than null expectations. These results suggested that most taxa
abundances were changing in the same direction, especially in the
modified habitat (Table 1).
We did not detect any spatial or temporal patterns in synchrony
variations (Table 2). The best model describing the synchrony variation
included a single environmental variable (i.e. TN, Table 2), which
explained 38% of the variation in the spatial and temporal variation of
community synchrony (Table 2). Total nitrogen had a significantly (at
0.05 level) negative effects on synchrony (the lower 2.5% and upper
97.5% intervals do not include zero). Other tested environmental
variables such as water depth, TP, and water clearance had no
statistically significant relationship to species synchrony.
The calculated VR ranged from 0.30 – 2.83 with the majority cases
greater than one (Table 1), of which seven were significantly higher
than the null VR. Similar to species synchrony, these results indicated
that the benthic fish community largely positively covaried, especially
at the plantation sites. As for variation ratio, there was no clear
spatial or temporal patterns. In addition, no model with environmental
variables was better than the null based on the loo model selection
procedure.
Community stability had a weakly negative relationship with TN. The
relationship was not significantly at 0.05 level (Table 2), but was at
0.1 level (the lower 5% and upper 95% interval of the coefficient for
TN was -0.12 to -0.01, data not shown). Like synchrony and VR, other
tested environmental variables had no significant impacts on community
stability.
Biotic mechanisms of community temporal
dynamics
Species synchrony and the variance ratio were significant predictors for
community stability (53% and 66% of the total variation was explained
by the VR and synchrony model, respectively, Table 3). In comparison,
both α and β diversity models had considerably lower explanatory power
with a mean Bayes-R2 of 0.33 (0.30, 0.54) and
0.23 (0.06, 0.40) (Table 3). This lower performance was also reflected
in the relatively larger confidence interval of the response curve,
especially when abundance stability was high (Fig. 3). While the
modelled relationship with VR and β diversity was linear, stability had
non-linear relationships with synchrony and α diversity (Table 3 and
Fig. 3). Community stability decreased with both VR and synchrony,
however, the marginal effect curve of the stability – α diversity was
hump-shaped unimodal, suggesting lower stability at both the extreme
ends. In contrast, the relationship with β-diversity was linear and
community abundance stability increased significantly with β-diversity
(Table 3, Fig. 3).
Habitat type was also included in these models. The estimated model
coefficients suggested that the plantation sites had significantly
higher community stability than the sedge sites (the 95% interval did
not include zero for all models, Table 3). However, the difference
between plantation and open water was not significant when the effects
of species variance rate, synchrony or α-diversity were accounted for
(zero was within the bracket of the 95% confidence interval, Table 3).
Ecological Stochasticity and its effects on community
dynamics
There were no inter- and intra- annual patterns in spatial ecological
stochasticity in benthic fish community. However, there were strong
spatial patterns: the modified sites had significantly lower
stochasticity than the more natural sites (Fig. 4). The modelled
coefficient indicated that ecological stochasticity was the predominant
process at natural sites (mean ecological stochasticity greater than
0.50, Fig. 4), whereas deterministic processes were prevailing at the
modified sites (mean ecological stochasticity was 0.37, Fig. 4). In
addition, none of the tested environmental variables had a significant
effect on ecological stochasticity and the best regression model
included only habitat types as explanation variable. The model had a
relatively high Bayse-R 2 of 0.42 (95%
confidence interval was 0.20 - 0.57).
The temporal ecological stochasticity was a strong predictor of all
investigated metrics of community temporal dynamics (the mean
Bayes-R 2 and its 95% confidence interval were
0.41 [0.22, 0.55], 0.30 [0.08, 0.50], 0.59 [0.42, 0.69] and
0.67 [0.55, 076] for stability, variance rate, synchrony, and total
temporal β-diversity respectively, Table 4). While the normalized
ecological stochasticity had significantly positive effects on species
variance rate and synchrony, it had significantly negative effects on
community stability (Fig. 5). The effects of stochasticity on temporal
β-diversity was highly non-linear: the β-diversity increased with
stochasticity at low level but stayed more or less stationary when the
NST reached ~ 0.4.
The community stability was significantly higher in the plantation
habitat than in the sedge habitat while the difference between
plantation and open water was not significant (Table 4). Moreover,
community stability was significantly lower in the flooding year of 2017
than in the normal water years of 2018 and 2019. For species synchrony
and variance rate, the difference between habitat types was not
significant (Table 4). Regarding the yearly variation, species synchrony
was significantly lower in flooding year of 2017, and the between-year
difference for species variance rate was not significant (Table 4).