Habitat Features Influence Aquatic Macroinvertebrates in the Cruces Wetland, a Ramsar Site of Southern Chile

Abstract

Coastal wetlands are highly threatened by human activities, leading to water quality degradation and biodiversity loss. This study assessed spatial variation in 27 water quality parameters, sediment organic matter, and macroinvertebrate assemblages across 12 sites in the estuarine Cruces River wetland (CRW Ramsar site, southern Chile) during summer 2019. Our analysis identified three areas of sampling stations in the wetland, categorized by trophic gradient and salinity: freshwater (n = 5), mixed (n = 3), and estuary (n = 4). Freshwater sites were characterized by low salinity, turbidity, and high nitrate concentrations. Estuarine sites were characterized by higher salinities and turbidity and low nitrates and total organic carbon (TOC) concentrations, and mixed sites had low salinities, high turbidities, high TOC, and low nitrates. Throughout the CRW, the richness and densities of different invertebrates were recorded. Freshwater stations had higher species richness, and estuary stations had higher abundance. Macroinvertebrates found in the lower reaches of the CRW included species characteristic of estuarine environments, whereas the upper stations were dominated by invertebrates inhabiting low-salinity environments. According to the ordination plot of distance-based redundancy analysis (dbRDA) and distance-based linear model (DistLM), our results indicate that macroinvertebrate assemblages differ significantly among areas of the CRW, primarily due to physicochemical variables (i.e., salinity, total carbon, and dissolved phosphorus). Total organic matter content in sediments was higher in freshwater sites and lower in estuarine sites. Our findings will be used to monitor the wetland and implement appropriate management measures for human activities, thereby protecting and conserving the estuarine Cruces River Ramsar wetland.

1. Introduction

Coastal wetlands, rank among the most productive aquatic ecosystems globally. However, estuaries are becoming increasingly polluted every day due to nearby human settlements, industrial activities, cattle raising, and agricultural land use, which release pollutants directly through sewage from the population or industrial waste, or indirectly through runoff or infiltration [1]. Additionally, estuaries are recipients of a diverse range of elements that rivers transport from their respective drainage basins. These elements, in conjunction with incoming tides, create environmental gradients throughout the central channel, serving as sinks for a variety of pollutants, nutrients, and organic matter [2]. Alterations in environmental variables, through increases or decreases in the concentration of specific elements, can adversely impact water quality. Thus, water quality can significantly impact aquatic communities; therefore, evaluating these sensitive ecosystems through water physicochemical parameters and biomonitoring becomes relevant to deliver data to decision-makers, enabling them to make informed decisions based on science and protect these ecosystems, thereby avoiding future damage [3].

Among soft-bottom-inhabiting macrofauna of wetlands, the most prominent are macroinvertebrates. Macroinvertebrates are a diverse group, with species that are highly tolerant to many environmental variables, whereas others are susceptible to both anthropogenic and natural perturbations [4]. They play a fundamental role in the ecosystem, transferring energy from primary producers to higher trophic levels [5]. Thus, the availability of macroinvertebrates is critical to vertebrates such as shorebirds, which depend directly on the abundance and biomass of macroinvertebrate prey, being even more crucial for migratory birds that travel long distances and come to feed on these macroinvertebrates [6,7]. In addition to birds, many of the fish that occur in nearshore and estuarine areas are supported by the quantity and quality of macroinvertebrate prey, which will have a direct effect on commercial fisheries carried out by artisanal fishers [8,9,10].

The assemblage of estuarine macroinvertebrates varies across both spatial and temporal scales, driven by biotic and abiotic factors. Biotic factors include predation, competition, reproductive condition, density, food availability, and habitat, among others [11,12]. In contrast, abiotic factors can be divided into natural and anthropogenic stressors. Salinity, organic matter, carbon, temperature, dissolved oxygen content, sediment type, and water depth can be considered as natural stressors [13]. Heavy metals, phosphates, nitrates, microplastics, deforestation, and land use, among others, are to be considered within the anthropogenic stressor category [14,15]. Considering the multiple environmental variables that can affect not only macroinvertebrates but also all aquatic assemblages, identifying the principal environmental variables is key to understanding the functioning of wetlands [16].

Along the southern Pacific estuaries, macroinvertebrates are characterized by high abundances and low diversity, primarily composed of amphipods (Paracorophium spp.), decapods (Hemigrapsus spp.), and polychaetes, including those of the families Spionidae, Capitellidae, and Nereidae, which significantly contribute to the total macroinvertebrate density and biomass [17,18,19,20]. These organisms have been directly affected by various types of pollutants found in Chilean estuaries. In particular, heavy metals (such as Cu and Pb) have been identified as incipient pollutants in the water [21] and have already been reported in elevated concentrations in estuarine fish and invertebrates [22,23,24]. Nutrients such as phosphates, nitrates, and organic carbon have also been shown to decrease macroinvertebrate richness, affecting taxa like crustaceans and mollusks. On the other hand, some polychaetes are more resilient to environmental perturbations and can increase their abundances [25]. All these changes produce a cascading effect that affects higher trophic levels, impacting fisheries and/or abundance and diversity of birds, which has repercussions for tourism activities (birdwatching), thus also impacting the economy of the basin [26]. For these reasons, not only are aquatic organisms directly affected by changes in water quality, but the human population is also indirectly affected.

Understanding the environmental gradients and ecological processes of river–estuarine systems is essential for implementing effective management measures. The CRW, located at 40° S in southern Chile, represents a valuable case study for examining the relationship between aquatic macroinvertebrates and gradients of environmental variables. This wetland was designated in 1981 as a site of international importance under the Ramsar Convention (www.ramsar.org (accessed on 30 March 2025)). Despite its protected status, the CRW is subject to continuous anthropogenic pressures from upstream activities, including land-use changes, industrial development, and urban expansion. The main objective of this study is therefore to investigate the relationship between environmental variables and aquatic macroinvertebrates in the estuarine CRW. Conclusive data from this study will support decision-makers in establishing biomonitoring programs in the basin, particularly those based on aquatic macroinvertebrates, which not only vary spatially along the salinity gradient of coastal wetlands but also serve as sensitive indicators of aquatic ecosystem health.

2. Materials and Methods

2.1. Study Area

The Cruces River wetland (40° S) is an estuarine ecosystem with a surface area of 4877 hectares. Since 1981, it has been designated as a Ramsar site (Figure 1). The Cruces River, main tributary of the CRW, originates from several headwater streams in the Andean foothills. Upon entering the wetland, it is joined by seven smaller tributaries: Nanihue, Cudico, Santa María, Pichoy, Cayumapu, Tambillo, and San Ramón. The tidal range within the wetland is ±0.5 m and is classified as “positive microtidal,” and tidal movement takes place around 20 km inland of the river mouth [24]. The climate is a humid temperate one, with an annual average temperature of 12.9 °C and an average annual precipitation range of 1600–3500 mm [27]. The area is characterized by wet winters (intense rainfall occurs between May and July) and dry summers (between December and March). Wetland extensions reach more than 50 km to the north, bordering the so-called “Cordillera de la Costa”, edging multiple land cover types. In the eastern area, native forests are primarily composed of evergreen temperate rainforest, with exotic plantations and patches. Grasslands, native forest remnants, and urbanization to the south predominantly characterize the western region.

2.2. Sampling Sites

A total of 12 sampling sites were surveyed from the Cruces River (Figure 1). Water physicochemical parameters, macroinvertebrate samples, and sediments were collected during the austral summer (January 2019). This season was selected for sampling due to the stability of river flow and evidence that macroinvertebrate abundances are most significant during this period. The sampling sites were selected based on a natural salinity gradient present in the estuarine ecosystem of the wetland.

2.3. Environmental Datasets

At each site, 27 environmental variables were assessed (

Table 1. Summary of the physicochemical variables of the estuarine Cruces River wetland (mean) at 12 sampling sites.

Station	Abbreviation	R12	R15	R16	R17	R18	R19	R20	R21	R22	R23	R25	R26
Temperature (°C)	T°	19.5	21.6	23.4	24.5	19.4	23.4	23.8	23.3	22.8	22.2	22.2	20.4
Conductivity (µS/cm)	Cond	131.4	118.8	111.4	69.9	129.1	49.9	276.0	159.4	349.0	822.0	822.0	384.0
pH	pH	7.3	7.4	7.8	7.6	7.9	7.6	7.0	6.9	7.6	7.3	7.3	7.2
Dissolved oxygen (mg/L)	DO	8.6	8.6	9.0	8.8	9.4	8.9	9.2	8.2	9.0	9.1	9.1	8.7
Oxygen saturation (%)	DOS	93.0	98.0	105.7	105.3	103.7	106.1	109.3	95.3	107.8	104.7	104.7	96.8
Salinity (PSU)	Sal	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.1	0.3	0.3	0.1
Turbidity (NTU)	Tur	0.0	3.3	2.7	3.9	3.9	5.8	4.2	5.0	4.9	5.9	5.9	2.2
Color (CU Pt Co)	Col	9.2	14.6	16.1	21.5	16.9	28.4	23.0	19.2	14.6	12.3	12.3	6.9
DIC (mg/L)	DIC	3.5	2.6	2.0	0.9	2.1	1.2	1.0	1.6	1.2	1.1	2.1	1.6
DOC (mg/L)	DOC	0.9	0.9	1.3	1.2	1.1	1.0	1.2	1.2	1.2	1.1	0.8	0.7
DC (mg/L)	DC	4.4	3.6	3.2	2.1	3.2	2.2	2.2	2.8	2.5	2.3	2.9	2.3
TIC (mg/L)	TIC	4.0	3.5	2.4	1.0	2.7	1.1	1.3	1.3	1.6	1.6	1.9	1.7
TOC (mg/L)	TOC	1.0	1.2	1.4	1.3	1.3	1.0	1.3	1.3	1.2	1.1	0.7	0.8
TC (mg/L)	TC	5.0	4.6	3.8	2.3	4.0	2.1	2.5	2.6	2.8	2.7	2.7	2.5
POC (mg/L)	POC	0.1	0.2	0.1	0.1	0.2	0.1	0.1	0.0	0.0	0.0	0.0	0.1
DQO (mg/L)	DQO	46.2	7.1	13.2	10.2	9.3	8.7	8.8	11.3	10.8	11.4	14.8	5.9
N-NH4 (µg/L)	NH4	11.1	10.6	13.3	10.6	6.2	9.0	3.7	3.0	4.4	4.4	13.8	7.2
N-NO3 (µg/L)	NO3	57.8	29.8	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	4.1
N-NO2 µg/L	NO2	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0
N-TOTAL (µg/L)	N	195.2	207.2	216.4	233.9	214.9	224.7	220.8	250.0	229.0	243.6	255.3	133.3
P-PO4 (µg/L)	PO4	2.0	2.4	2.9	3.2	3.3	3.3	2.2	3.4	3.6	2.7	4.5	3.3
P-TOTAL (µg/L)	P	15.9	15.1	19.2	18.5	20.8	24.9	19.6	23.6	23.4	23.5	33.4	15.3
Ca (µg/L)	Ca	960	792	2534	1011	2461	2436	1451	1616	2073	1462	3169	3574
Mn (µg/L)	Mn	3.5	3.5	15.6	4.8	13.5	13.3	10.7	8.3	12.4	2.8	8.5	5.7
Fe (µg/L)	Fe	91	51	273	107	114	176	120	155	147	159	106	46
Cu (µg/L)	Cu	3.8	0.7	0.8	0.9	3.2	1.9	1.2	1.7	1.5	3.2	1.1	1.7
Pb (µg/L)	Pb	0.8	0.7	0.5	0.8	1.3	0.6	0.9	0.8	0.8	2.2	0.6	1.0

). These parameters were selected because they represent critical physicochemical determinants widely recognized for shaping the composition, distribution, and functioning of aquatic communities. Water temperature (°C), electrical conductivity (µS/cm), pH, salinity (PSU), and dissolved oxygen (mg/L) were measured in situ with a WTW 340 multiparameter instrument (Weilheim, Germany). Water quality samples were collected in duplicate (1 L) from the center of the river channel, below the water surface (0.5 m), and transported in coolers to 4 °C in the laboratory for chemical analysis.

These water samples were used to analyze nutrients: Ammonium nitrogen (N-NH₄), Nitrate nitrogen (N-NO₃), Nitrite nitrogen (N-NO₂), Total nitrogen (N-TOTAL), Orthophosphate phosphorus (P-PO₄), total phosphorus (P-TOTAL), dissolved and particulate organic and inorganic carbon, Ca, and heavy metals (i.e., Fe, Cu, Pb). Shortly, nitrate was determined by the cadmium reduction method [28], and nitrite was determined by diazotizing with sulfanilamide and coupling with N-(1-naphthyl)-ethylenediamine dihydrochloride [28]. Ammonium was determined by the modified Berthelot reaction using Salicylate and Dichloroisocyanurate, and total nitrogen was determined by the sodium hydroxide and persulfate digestion method, followed by the determination of total nitrate using the reduction method. Total phosphorus was measured using the sodium hydroxide and persulfate digestion method, followed by the determination of soluble reactive phosphorus using the blue indophenol technique [28].

Samples for dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and dissolved organic matter (DOM) quality were filtered (GFF, nominal pore size = 0.7 µm and 0.22 µm) to analyze DOM optical spectroscopy and DOC replicates were filtered and fixed by adding 100 µL of fuming HCl (Merck, Darmstadt, Germany) to stop microbial activity, and transported at 4 °C to the laboratory for subsequent analysis using high-temperature catalytic oxidation (HighTOC, Elementar Systems, Langenselbold, Germany) [29]. For the determination of Ca and heavy metals, water samples (volume: 15 mL) were filtered using a 0.2 µm syringe filter and acidified with Suprapur nitric acid (Merck). Finally, the samples were analyzed using total-reflection X-ray fluorescence spectrometry (TRXF) following procedures described in [30]. Acidified water samples (10 µL) were prepared on quartz carriers, and an internal Ga standard (5 ng, suspended in Suprapur^® nitric acid for trace analysis, Sigma-Aldrich, St. Louis, MO, USA) was added. After drying on a hot plate (15 min, 60 °C), trace elements were determined using a total reflection X-ray fluorescence spectrometer Picotax (BRUKER, Berlin, Germany).

2.4. Macroinvertebrate Sampling and Processing

Benthic macroinvertebrates (>0.5 mm) were sampled from each study site. At each site, three separate samples were taken using an Emery drag net (with a mouth opening of 0.025 m²) at depths of approximately 5–10 m. We sampled in the center of the channel, rather than on the banks (<1 m), because both zones present different compositions of macroinvertebrate assemblages [10]. We washed all samples in the field through a 0.5 mm sieve bucket, fixed them in situ with 70% ethanol, and placed them in plastic containers, then transported them to the laboratory.

In the laboratory, samples were washed, sorted, and all macroinvertebrates were separated from the detritus (sand, leaves, woody residues, and algae), and then preserved in 90% ethanol. All individuals from each taxon were identified and counted under a stereomicroscope (Olympus, model SZ51, 40x, Tokyo, Japan). Organisms were identified to the lowest taxonomic level possible resolution using identification keys [31] and reference collections from the Benthos Laboratory of Universidad Austral de Chile.

2.5. Sediment Analysis

Grain size composition and organic matter (OM) content were characterized at each sampling station, to which three replicated samples were taken using the same Emery dragnet. Samples were frozen (−20 °C) before being stored, and the methodology was followed by Bertrán and collaborators [17]. The samples were sieved using mesh sizes of −1.0 Ø to separate the gravel and 4 Ø to separate the sand from the mud fraction. Samples were dried to 60 °C for 12 hr on a laboratory oven, VWR Oven model 1325-2 (Pittsburgh, PA, USA). The OM content was determined for each sample by loss on ignition at 500 °C for 3 h using a muffle furnace, Thermo Scientific model 62,700 Furnace (Waltham, MA, USA).

2.6. Data Analysis

We conducted a principal component analysis (PCA) using all physicochemical variables listed in Table 1 to order the sampling sites along environmental gradients, and salinity classes (i.e., freshwater, mixed, estuary) as factors. The physicochemical data were first transformed (using the fourth root) and then normalized, after which a matrix of Euclidean distances was constructed.

Biological data (abundance of macroinvertebrates) were transformed (log (x + 1) to construct a Bray–Curtis similarity matrix [32], which was analyzed using non-metric multidimensional scaling (nMDS) as the ordination method. Using a Permutational multivariate analysis of variance (PERMANOVA; 9999 permutations), we test significant differences (p < 0.05) between the three salinity/trophic degree classes. The structure of macroinvertebrate assemblages was analyzed using the Shannon-Weaver index and Pielou’s evenness.

Relationships of macroinvertebrate assemblage composition to physicochemical variables were examined using a distance-based linear model (DistLM) procedure [33]. The final model included the most relevant physicochemical variables and was run with 9999 permutations based on the adjusted R² selection criteria and forward selection procedure (p < 0.05). The analysis was based on the Bray–Curtis similarity matrix of macroinvertebrate data and physicochemical variables. Model-selected environmental data were used in a constrained ordination to model the relationship between measured physicochemical variables and macroinvertebrate assemblages using distance-based redundancy analysis (dbRDA) [33]. Before DistLM and dbRDA analysis, the environmental features, except pH, were square root-transformed, and highly correlated variables (Pearson’s r > 0.8) were removed (conductivity, DIC, and TIC). Lastly, a supported analysis using spatial data through the Mantel test was performed to determine significant correlations (Spearman’s R) between the physical and chemical parameters of the macroinvertebrate community. We performed all multivariate analyses in PRIMER version 6, using the 6 PERMANOVA+ add-on package [33], which included routines for PCA, MDS, PERMANOVA, DistLM, and dbRDA.

3. Results

3.1. Environmental Assessments

A summary of the results obtained for the wetland water samples is presented in Table 1. All sites had water temperatures (between 19.5 and 24.5 °C), pH close to neutral, and well-oxygenated waters (>8.2 mg/L). Conductivity and salinity showed a pattern of increasing concentrations from the upper reach to the estuary. The different carbon fractions (DOC, DIC) generally had high concentrations in the upper reach of the wetland. Nutrients (P and N) were high across the study area. Heavy metal concentrations varied throughout the study area, with generally low values.

Principal component axis 1 (PC1) accounted for 32.5% of the variance. In contrast, PC axis-2 explained 18.3% (cumulated variance 50.8%) (Figure 2). PC axis-1 appeared to represent the influence of turbidity (Tur) and nitrates (NO₃), both negative loads. In contrast, PC axis-2 seemed to embody the salinity (Sal) in the negative loading, and total organic carbon (TOC) in the positive loading. Based on this analysis, we established three groups of sampling stations according to trophic degree and salinity. Freshwater sites (R12, R15, R16, R17, R18) with low salinity and turbidity and high nitrates concentrations; estuarine sites (R22, R23, R25, R26) with higher salinities and turbidity, low nitrates and TOC concentrations; and mixed sites (R19, R20, R21) with low salinities, high turbidites and TOC and low nitrates concentration (Figure 2). The characterization of each site according to the water parameters are shown in Table 1.

3.2. Benthic Macroinvertebrates

There were 23 macroinvertebrate taxa collected in the study area, including three polychaeta, one Oligochaeta, three Crustacea, one Malacostraca, two Arachnida, seven Insecta, four Gastropoda, one Bivalvia, and one Turbellaria. The most abundant occurring taxa were the crustacean Paracorophium hartmannorum, Phoxorgia sp., the annelids Prionospio patagonica, Tubificidae, and the insect Orthocladiinae (

Table 2. Abundances (ind/m²) and diversity metrics for macroinvertebrates at the 12 sampling sites in the austral summer of 2019.

	R12	R15	R16	R17	R18	R19	R20	R21	R22	R23	R25	R26
Polychaeta
Prionospio patagonica	0	0	0	0	0	27	0	0	0	107	2640	173
Perinereis gualpensis	0	0	0	0	0	0	0	0	0	0	13	0
Capitellidae	0	0	13	0	0	560	67	0	80	0	0	0
Oligochaeta
Tubificidae	27	40	187	13	80	0	0	0	0	13	0	0
Crustacea
Paracorophium hartmannorum	0	0	0	0	0	0	0	0	1920	787	93	3933
Phoxorgia sp.	0	0	0	0	0	0	0	0	27	0	1520	27
Aegla sp.	0	0	0	0	0	0	13	0	0	0	0	0
Malacostraca
Isopoda	0	0	0	0	0	0	0	0	0	0	27	0
Arachnida
Hydracarina	0	0	0	0	0	0	13	0	0	0	0	0
Araneae	0	0	0	0	13	0	0	0	0	0	0	0
Insecta
Antarctoperla michaelseni	0	0	0	0	13	0	0	0	0	0	0	0
Limnoperla jaffueli	0	0	0	0	13	0	0	0	0	0	0	0
Smicridea sp.	0	0	13	0	0	0	0	0	0	0	0	0
Orthocladiinae	0	0	0	27	187	0	0	0	0	0	0	67
Tanypodinae	0	13	0	0	0	0	0	0	0	0	0	0
Chironominae	0	0	0	13	13	0	0	13	0	0	0	0
Empididae	13	0	0	0	0	0	0	0	0	0	0	0
Gastropoda
Physa sp.	0	0	13	0	0	0	27	0	0	0	0	0
Chilina sp.	0	0	0	0	0	0	0	13	40	0	0	0
Uncancylus sp.	0	0	13	0	0	0	0	0	0	0	0	0
Littoridina sp.	0	13	0	0	0	0	0	0	0	0	0	0
Bivalvia
Pisidium sp.	0	0	0	0	0	0	13	80	13	13	0	0
Turbellaria
Dugesia sp.	0	0	27	0	0	13	0	0	0	0	0	0
Taxa Richness	2	3	6	3	6	3	5	3	5	4	5	4
Total abundance (N/m2)	40	66	266	53	319	600	133	106	2080	920	4293	4200
Evenness (J′)	0.9	0.9	0.6	0.9	0.7	0.3	0.8	0.7	0.2	0.4	0.5	0.2
Shannon Diversity (H′)	0.6	0.9	1.1	1	1	0.3	1	0.7	0.4	0.5	0.8	0.3

).

Community parameters revealed that taxa richness varied between two and six taxa, with abundance ranging from 40 to 4293 individuals/m². The highest abundances were found in estuarine sites (R22 to R26). The Pielou evenness ranged between 0.2 and 0.9, and the values of Shannon-Weaver diversity ranged between 0.3 and 1.1 for both indices, with the highest values in freshwater and mixed sites (

Table 3. Sediment fraction and organic matter (OM) content (%) for the 12 Cruces River wetland sampling sites. Data represent the mean ± standard deviation (SD) (n = 3).

Stations		Fraction (%)		SD	OM (%)		SD
Station R12	gravel	0.85	±	0.40	88.40	±	1.59
	sand	85.35	±	0.89	6.54	±	0.43
	mud	13.80	±	1.19	12.12	±	0.34
Station R15	gravel	3.51	±	2.52	75.42	±	10.12
	sand	59.05	±	2.74	12.15	±	2.20
	mud	37.43	±	4.60	16.33	±	0.06
Station R16	gravel	0.26	±	0.04	67.63	±	17.04
	sand	46.49	±	11.36	22.58	±	1.42
	mud	53.24	±	11.37	16.57	±	0.30
Station R17	gravel	5.25	±	3.29	80.18	±	3.13
	sand	63.85	±	25.00	16.16	±	1.21
	mud	30.90	±	26.94	20.59	±	0.62
Station R18	gravel	33.41	±	48.29	54.02	±	44.65
	sand	45.51	±	30.52	14.93	±	2.02
	mud	21.07	±	18.37	46.66	±	44.73
Station R19	gravel	0.11	±	0.06	63.73	±	34.42
	sand	89.02	±	6.13	5.30	±	0.18
	mud	10.87	±	6.14	10.50	±	0.15
Station R20	gravel	58.44	±	2.97	3.30	±	1.11
	sand	34.62	±	3.46	7.65	±	2.33
	mud	6.95	±	2.19	19.45	±	1.15
Station R21	gravel	0.02	±	0.03	3.70	±	6.42
	sand	10.19	±	0.46	7.09	±	0.29
	mud	89.79	±	0.44	9.08	±	0.80
Station R22	gravel	0.56	±	0.24	33.13	±	5.49
	sand	51.38	±	3.91	20.92	±	0.29
	mud	48.05	±	3.83	16.59	±	0.15
Station R23	gravel	0.22	±	0.15	57.73	±	19.11
	sand	52.72	±	3.52	9.51	±	0.37
	mud	47.07	±	3.41	10.38	±	5.13
Station R25	gravel	3.92	±	0.16	1.11	±	0.07
	sand	95.90	±	6.13	5.30	±	0.05
	mud	0.18	±	6.14	10.50	±	2.54
Station R26	gravel	17.09	±	0.71	0.83	±	0.05
	sand	79.37	±	25.00	1.18	±	0.03
	mud	3.54	±	26.94	12.99	±	0.50

). Estuarine stations showed the lowest values in both Pielou evenness and Shannon-Weaver indices, respectively.

Like physicochemical parameters of water, sampling points based on macroinvertebrate assemblage composition were divided into three groups (Figure 3), which were separated according to a trophic salinity gradient. There were statistical differences in species composition among sites subjected to different grades of trophic salinity (PERMANOVA, Pseudo-F = 4.14, p = 0.0001). Estuarine species P. hartmannorum, Phoxorgia sp., and P. patagonica registered the highest abundances in stations 22, 23, 25, and 26, whereas freshwater taxa Tubificidae and Orthocladiinae were more abundant in stations 12, 15, 16, 17, and 18. In stations 19, 20, and 21, taxa from both environments (freshwater and estuary) were found with low abundances (Figure 3).

3.3. Sediment Characteristics

All three fractions of sediments are present in the study area, varying in percentages at each sampling station, making the sand fraction the most common in the wetland. The highest rates of gravel, sand, and mud occurred at stations R20 (58.44%), R25 (95.9%), and R21 (89.79%), respectively (Table 3). Generally, the organic matter content was higher in freshwater sites, particularly at stations R17 and R16. The stations with the lowest OM in the entire study area were the estuarine stations R25-R26 (

Table 4. Percentage of Total Organic Matter in the sediments of the estuarine Cruces River wetland. Data represent the ±standard deviation mean (n = 3).

Stations	Total Organic Matter (%)
R12	8.00 ± 0.60
R15	16.05 ± 2.93
R16	19.42 ± 0.34
R17	20.93 ± 3.21
R18	15.31 ± 10.49
R19	3.76 ± 0.26
R20	5.89 ± 1.69
R21	8.87 ± 0.75
R22	18.91 ± 0.28
R23	9.99 ± 2.34
R25	1.01 ± 0.05
R26	1.54 ± 0.04

).

3.4. Relationship Between Environmental Variables and Macroinvertebrate Assemblages

The DistLM explained 98% of the variation in the macroinvertebrate assemblages, and the contribution of 10 variables achieved the best solution, in which Salinity, Total Carbon, and Phosphate were significant (

Table 5. Results of the distance-based linear model (DistLM) sequential tests indicate that key physicochemical variables explain macroinvertebrate assemblages. In bold, p-values < 0.05.

Variable	Sum of Squares (Trace)	Pseudo-F	p-Value	Cumulative Proportion
Salinity	11,580.0	3.688	0.001	0.269
TC	6984.9	2.575	0.013	0.432
NH4	3882.4	1.513	0.146	0.522
Mn	3526.1	1.451	0.196	0.604
PO4	5090.3	2.563	0.038	0.723
DC	3163.5	1.807	0.123	0.796
Tur	2406.3	1.517	0.222	0.852
NO3	2276.4	1.678	0.224	0.905
Pb	1720.8	1.465	0.312	0.945
Cu	1493.0	1.745	0.371	0.980

). The sampling sites were clearly separated into three groups in the dbRDA model (Forward). Freshwater sites were located to the left of axis one (explaining 32.4% of the total variation), and estuarine sites were to the right. In contrast, mixed sites were located between the two groups (Figure 4). Vectors for salinity were aligned parallel to axis one and close to estuarine stations, where typical estuarine species, such as amphipods and polychaetes, are found. Whereas vectors to TC and PO₄ were in orientation to axis two (explaining 20.2% of the total variation) and close to freshwater stations, where oligochaetes and larval insects were dominant. Total organic matter in the sediments was not a key variable in structuring the composition of the macroinvertebrates. Environmental variables mainly estimated by physical and chemical parameters through Spearman’s R Mantel test were correlated to the spatial gradient of the wetland (Figure 5). Conductivity, total inorganic carbon (TIC), and PO₄ show the highest positive correlations with community variations. Conductivity (ρ = 0.3) and salinity (ρ = 0.24) are the most strongly correlated environmental variables across spatial gradients, indicating a significant implication for macroinvertebrate distribution.

4. Discussion

Understanding environmental gradients and their influence on aquatic biota in coastal wetlands is essential for making informed management decisions in these ecosystems. This study took place in a Ramsar site, which is constantly threatened by human activities, including industrial and urban discharges, as well as land use for forestry and grazing. Our findings highlight that the estuarine CRW maintains an elevated influence of the estuary over a distance of 30 km from the mouth, exhibiting a clear spatial gradient in both physicochemical water parameters and macroinvertebrate assemblages along the river-estuary continuum. The middle stations (R19-R20-R21) exhibit characteristics of an ecotone between freshwater and estuary.

A high variability of water quality parameters characterizes coastal wetlands. The estuarine CRW has been described as exhibiting high annual fluctuations in water quality parameters [34]. However, the average values of water parameters in this study were similar to those previously reported for the same wetland [24,35]. The concentrations of heavy metals (Mn, Fe, Cu, Pb) and Ca reported in this study were lower than those reported from other estuary systems in South America near cities [2]. Consequently, concentrations in Cruces River wetlands are currently within the maximum levels permitted by Chilean water quality regulations regarding heavy metals, indicating a low environmental risk to the wetlands due to heavy metal contamination. Similar results were found in the same study area [24], indicating water heavy metals concentrations in the study area have not increased significantly enough to exceed regulatory limits.

The composition of macroinvertebrate assemblages depends strongly on water quality status [36]. In this study, salinity, phosphates, and total carbon were the primary environmental variables structuring the composition of estuarine macroinvertebrates. An increase in salinity and phosphate concentrations in the water was associated with stations near the mouth of the estuary (i.e., downstream stations). In contrast, an increase in total carbon concentration was related to stations near the Cruces River (i.e., upstream stations). Salinity is highly related to water conductivity and is considered a natural stressor in estuarine wetlands. High values of conductivity recorded in the offshore (349–822 µS/cm) wetland could be due to the intrusion of large volumes of water from the sea.

In contrast, the values observed in both parameters decrease as one moves upstream. Values in freshwater zones (69.9–131.4 µS/cm) can be attributed to surface runoff from adjacent land use. Land use in the Cruces River wetland basin is dominated by cattle-feeding prairies and forestry, accounting for 57.9% of the basin surface [34]. Both land uses are considered a principal stressor to aquatic ecosystems, responsible for nutrient input, which causes eutrophication in the system. Consequently, phosphate was another variable that explained the variation of macroinvertebrates in the wetland. Nutrients, such as phosphorus and nitrates, tend to increase downstream in watersheds, associated with agricultural and urban activities [37,38].

Sand is a fraction predominantly found in estuaries subjected to strong energy from estuarine waves [39]. In this study, sand and mud were the principal fractions of the wetland sediments, consistent with findings from nearby estuaries and coastal lagoons [17,40,41]. This pattern is associated with the geomorphology of basin soils, characterized by high clay content and limited riparian vegetation cover, which facilitates sediment transport into aquatic systems. Higher organic matter concentrations in the estuary sediments were predominantly found in freshwater stations compared to offshore stations, suggesting input from the river and tributaries. Organic matter can originate from cattle-feeding prairies and forestry land uses, which occur mainly from the middle part of the wetland to upstream. The estuary studied here is classified as positively tidal, having a strong influence on tidally forced saltwater intrusions, especially during the summer season, when the river flows are lower [42]. The organic matter content is primarily controlled by hydrodynamics in sediment estuaries [43], so the lower reaches of the estuary are impacted mainly by the tides, which suggests that the sediments would be in greater movement than the upper reaches of the estuary. This would explain the lower organic matter in the sediments, both in gravel, sand, and mud. Thus, our results suggest that the wetland, up to its middle part (stations between fresh and saltwater), acts as a trap for organic matter. This situation has been described for certain types of estuaries [44]. Large amounts of organic matter found in coastal wetlands can be beneficial as harmful. In the first instance, it can be used as a source of food for detritivore invertebrates; however, in excess, organic matter in sediments may become detrimental because decomposition, in addition to warmer temperatures, causes oxygen depletion [45].

In the Cruces River wetland, we reported low macroinvertebrate diversity (Shannon diversity index < 1). In contrast, Pielou’s Evenness index values were disparate, with high values recorded in the upper reaches (>0.6), whereas in the lower reaches, evenness was low (<0.5). Our results are typical of wetlands that drain into estuaries, where low species richness in coastal wetlands has been attributed mainly to fine sediments, uniformity of habitats, and greater environmental extremes (salinity, anoxia) [46]. The macroinvertebrate assemblages composition was similar to previous studies in the Valdivia-Cruces estuary and inclusive of those found in southern estuaries, which are characterized by a significant sand fraction and high organic matter in sediments, showing low diversity dominated by the polychaetes P. patagonica, Capitellidae, the oligochaete Tubificidae, and crustacean P. hartmannorum [10,17,19,40,41,47]. Spionidae and Capitellidae are typically opportunistic and cosmopolitan polychaete families in coastal marine and estuarine soft sediments, deposit-feeding detritus consumers. Therefore, it is common to find them in estuaries and lagoons with high organic matter and eutrophic conditions, often accompanied by hypoxic events [25,48]. Furthermore, they are tolerant to stressful conditions, spionids and capitellids are used worldwide as bioindicators of polluted water [36]. The presence of high densities of Tubificidae in the upstream Cruces wetland was not surprising, since the habitat of this family is eutrophic flats and polluted water, and dense populations in high amounts of organic matter in the sediments is natural [49,50]. The presence of this worm in the study stations indicates a suitable habitat for these taxa. The habitat of the corophiids amphipods Paracorophium is quite varied, inhabiting intertidal sandflats, as well as associated with the upper reaches of estuaries, where salinities are diluted with freshwater input, tolerating a wide range of salinities [51], and high concentrations of organic matter in the sediments, on which it feeds [43]. Specifically, Paracorophium hartmannorum is a species that inhabits estuaries and coastal wetlands in the study area, preferring (along with P. patagonica) muddy-sand sediments [40]. Their occurrence and abundance in this study were limited to the lower reaches section of the wetland, in the estuary stations, where high salinities, higher PO₄ concentrations, lower total carbon concentrations in the water, and relatively low organic matter in the sediments were present compared to the upper reaches wetland.

Natural stressors and human activities can have direct effects on water quality and aquatic biota in coastal wetlands in the southern Pacific [52,53]. In the Cruces River wetland, the primary human activities are associated with land use in the basin, including prairies for cattle grazing, exotic forest plantations of Eucalyptus and Pinus, dairy industries, pulp and paper industries, and towns located in both the upper and lower basins. All these activities are recognized by altered water quality, sediments, and aquatic biota, which have adverse effects on marine ecosystems [54,55,56]. Our results showed a strong structure in environmental variables as well as in the aquatic biota in the wetland, being able to clearly differentiate three zones (freshwater, mixed, and estuary). Our study has some limitations that must be considered. For example, it was carried out during the period of lower flow (summer), when the estuary operates as a partially mixed system. Future research should be conducted in the contrasting period of higher flow (winter), when the estuary becomes a saline wedge [57]. Additionally, we sampled relatively few sites along the CRW; therefore, new sampling efforts at other sites should be considered. For instance, it is essential to account for additional anthropogenic disturbances, such as wastewater discharges from upstream towns and effluents from pulp mills releasing industrial wastewaters into the CRW.

5. Conclusions

The Cruces River wetland Ramsar site is an area that drains into the temperate estuarine system. The present study provides valuable information on the spatial trends in water quality, sediments, and macroinvertebrate assemblages within a Ramsar site. The Cruces River wetland represents a clear transition between freshwater and saline water. We clearly demonstrate a tidal gradient reflected by environmental variables that affect the macroinvertebrate assemblages. The Cruces River is the main tributary of the Cruces River wetland, contributing substantial freshwater inputs. This was evident at the upstream stations, which exhibited environmental variables characteristic of freshwater systems and macroinvertebrate assemblages dominated by taxa typical of these environments.

In contrast, the lower portion of the wetland flows into the estuarine section, where an evident marine influence was reflected in higher salinity levels and in macroinvertebrate taxa characteristic of brackish waters. Finally, between the freshwater and estuarine zones, we identified three sampling stations with similar water quality characteristics. These stations supported only a few macroinvertebrate taxa, and in low abundances, indicating a clear ecotone between the two environments.

The estuary is currently subject to multiple anthropogenic pressures. If these pressures intensify in the future, combined with reduced water flow driven by climate change, which would decrease the dilution capacity of pollutants, a loss of aquatic biodiversity and cascading effects on higher trophic levels can be expected. Our results provide essential baseline information to support long-term monitoring of the wetland and to inform science-based management strategies aimed at protecting and conserving this Ramsar site. Studies evaluating the ecological health of coastal ecosystems through water quality and aquatic fauna are particularly needed in high-conservation-value wetlands. By enhancing our understanding of wetland functioning, this study contributes to the development of effective management measures for human activities occurring within or near wetlands, ultimately supporting biodiversity conservation.