Data analysis
We evaluated the efficiency of our overall sampling effort for
basimontane and premontane levels using rarefaction
curves and the Chao1 species
estimator for data pooled across sample years (Chao, 1984).
Extrapolating a species accumulation curve to its asymptote and
estimating species richness via rarefaction and the Chao 1,
respectively, both provide an estimate of the performance of the
proposed sampling method (Magurran, 2004; Chao et al. , 2009)
We evaluated diversity components using both univariate and multivariate
analyses. We used generalized linear mixed effects models to evaluate
the effect of altitude on species richness, total abundance, and
effective diversity (i.e., eH’, where H’ is the
Shannon diversity index; Jost 2006). Sampling year was a random effect
because we used a repeated measures sampling design. Sample sites were
also included as a random effect to address unmeasured differences in
sites. As a result of this analytical model, results are general for
altitudinal effects on fish diversity in the Caquetá River through
years, including pre and post conflict time-periods, and among sites.
Alternative models were compared using the corrected Akaike’s
Information Criterion (AICc) with the bbmle package (Bolker, Team and
Giné-Vázquez, 2022), where we emphasized AICc weights to identify the
most plausible model after discounting for model complexity (Burnham and
Anderson, 2002). Different alternative residual distributions (e.g.,
Gaussian, Gamma, negative binomial) in generalized linear models were
iteratively evaluated and compared to log-transforms of response
variables to best meet model assumptions (using check_model in the
performance package; Lüdecke 2023). Given a chosen distribution,
alternative models were then compared by AICc, where compared models
included a null, random effects only, potential fixed effects (i.e., a
dummy variable representing pre- and post-cease-fire conditions and
altitude effects), and combinations of fixed and random effects.
Finally, we used nonmetric multidimensional scaling (NMDS) with
PERMANOVA to confirm differences in community structure between
basimontane and premontane sites.
Data management and statistical analyses were performed in R (R Core
Team, 2021) using functions from the glmmTMB (Magnusson et al. ,
2020), vegan (Oksanen et al. , 2020), devtools (Hadley, Hester and
Chang, 2022), iNEXT (Hsieh, Ma and Chao, 2016), ggplot2 (Kassambara,
2018), MASS (Ripley et al. , 2019), multcompView (Graves and
Piepho, 2022), and performance (Lüdecke, 2023) packages.
Results
Samples included 4216 fish, belonging to 100 species, 58 genera, 24
families, and six orders (Supplementary file F1). Rarefaction curves
reached asymptotes for both basimontane and premontane levels (Figure
3a). Premontane sites had >3 times more fish and
>5 times more species than those recorded in basimontane
sites (Figure 3b). In addition, basimontane sites had a different
taxonomic composition than premontane sites. Basimontane sites had
similar numbers of Characiformes and Siluriformes and some
(<10%) of the Blenniiformes (mainly in the Cichlidae family;
Figure 3c). In contrast, the premontane level was clearly dominated
(>75%) by the Characiformes fishes which comprised a
higher diversity at the order level (Figure 3c). Fish community
structure disparities between altitudinal levels are confirmed by the
PERMANOVA (F = 3.04, R = 0.23, P<0.05 ), and the NMDS in
which two clear groups, corresponding to the basimontane and premontane
sites, are depicted in the multidimensional space representing the
analysis (Figure 3d).
Species richness was most efficiently modeled as a power law (i.e.,
log-log) function of altitude and the random effects of year and site
(supplementary Table S1; Table 2). Although altitude alone has a good
predictive power (R2 = 0.42) predictions improve with
the random effects (R2 = 0.62), as confirmed by the
model performance procedure (supplementary Figure S1). The model output
suggests a significant mean decrease by 0.98 log(species richness) per
unit of log-altitude (Table 2; see Figure 4a for regression line).
As for species richness, a power law model for total abundance using
altitude as a fixed effect and the random effects was most predictive
compared to other models (Supplementary Table S2; Table 3). Altitude
alone represented 42% of variation in species richness, but model
predictions improve with random effects (R2 = 0.62;
supplementary Figure S2). The model output suggests a 0.72 significant
decrease in log(fish abundance) per unit of log-altitude (Table 3; see
Figure 4b for regression line).
Effective diversity was also most plausibly modeled as a power law
(Supplementary Table S3; Table 4). Altitude alone has substantial
predictive power (R-squared = 0.433), but adding year as a random effect
slightly improved fit (R-squared = 0.456; Supplementary Figure S3). The
model output suggests a significant 0.834 mean significant decrease in
log(effective diversity) per unit of log-altitude (Table 4; see Figure
4c for regression line).
Overall, for all of the diversity components evaluated herein, using
altitudinal level as fixed and site and year as mixed effects was rather
predictive, and no pre- and post-conflict difference was apparent in
results (i.e., results here represent conditions before further human
land use effects). Fish diversity predictably decreased with altitude as
a power law function.
Discussion
Our study is the first of its kind to evaluate fish community structure
in the Colombian Andes-Amazon transition zone. Results here provide a
baseline for conservation of regional streams across premontane and
basimontane zones because data represent the period when armed conflict
ended but before potential development of formerly avoided lands
(Calle-Rendón, Moreno and Hilário, 2018).
Our results confirmed that altitudinal gradients in fish community
assembly are important (van der Hammen and dos Santos 1995) and that
fish diversity is greater at lower altitudes, no matter how we estimated
diversity (e.g., Jaramillo-Villa et al. 2010, Lomolino et al. 2010,
Lujan et al. 2013). Considering that effective mitigation of
anthropogenic pressures on streams and fish assemblages should account
for site-specific conditions and at different scales (Poiani et
al. , 2000; Newbold et al. , 2015), altitudinal gradients in the
study area may be predictive for conservation and management. We note
that the basimontane streams are important to conserve despite their
relatively low diversity because fishes there are notably different from
those downstream.
Changes in community composition through time are typically complex and
depend on spatial and land use contexts (Allen et al. , 2019; Hillet al. , 2021). We expect that fish diversity might be most
heavily affected at the premontane level over time due to human
activities that will stronger and earlier at lower altitudes.
Conservation practices (e.g., riparian buffer zones, runoff settling
ponds) to maintain stream conditions can be implemented early in
regional land changes to best conserve diversity.
Given species extinction rates due to habitat degeneration in ecosystems
similar to those sampled here (Manjarrés-hernández et al. , 2021),
this study is valuable as a baseline of barely-impacted conditions soon
after the conflict ended in Colombia and before encroaching development
of formerly avoided lands (Calle-Rendón, Moreno and Hilário, 2018). We
expect future sampling will compare results to those reported here to
document changes in fish assemblages due to land use changes. We also
expect land use to be most changed at lower altitudes, where soils and
slopes are more amenable to agriculture, roads, and housing. If so, then
it is possible that fish assemblages will be degraded by increased land
use to become simpler and later affected by upstream effects (Figure 1).
If ongoing deforestation and encroaching anthropogenic land use in the
hyper-diverse Amazon basin is to be managed to minimize species losses,
then some lands and streams must be preserved (Mckinney and Lockwood,
1999; Granado-Lorencio, Cerviá and Lima, 2007; Rull, 2007). Results here
suggest that land surrounding premontane streams should take priority to
conserve the most species in areas that are most vulnerable. Upstream
catchments in basimontane areas can also be preserved to maintain water
quality flowing into premontane streams and conserve unique fishes in
those upstream reaches(Booth and Jackson 1997, Klauda et al. 1998,
Araújo and Tejerina-Garro 2009, de Melo et al. 2009). Future work in the
study area should evaluate relative effects of changing land use in
upper and lower catchments on fish diversity in the lower reaches.
So far, most emphasis on ecological studies on understanding diversity
has been on spatial patterns of biological diversity rather than
analyzing temporal patterns. Understanding temporal changes is essential
to predict possible scenarios of the most diverse world’s biota in
natural ecosystems of the Amazon. Fish assemblages are affected by
processes occurring at multiple scales, including those covered in our
analyses (Livingstone, Rowland and Bailey, 1982; Jackson, Peres-Neto and
Olden, 2001; Tedesco et al. , 2005; Oberdoff et al. , 2011).
Future surveys could integrate data at scales obtained here with even
greater spatial and temporal extents. We regard results here as a
potential baseline for future work in the same drainages, where future
work may reveal effects of coming anthropogenic land use in the Amazon
basin.