Urban effluents affect the invasive bivalve Limnoperna fortunei (Dunker 1857) fitness in a large Pampasic river (Río Negro, Uruguay).

Invasive alien species (IAS) exert a negative impact on native ecosystems and on various human activities. Limnoperna fortunei (Dunker 1857), a sessile mytilid introduced from Asia in the Río de la Plata, demonstrates a high dispersal capacity, growing over other organisms and artificial structures. Understanding its behavior is crucial for developing appropriate control and mitigating its detrimental effects. This study investigated the population dynamics of this mollusk in response to urban effluents in a large river. Water and population parameters of L. fortunei were measured both upstream and downstream of a small town from July to December 2020. Downstream areas exhibited increased temperature and decreased transparency compared to upstream locations, while pH, conductivity, and dissolved oxygen remained relatively constant. However, downstream, the L. fortunei population comprised fewer and smaller individuals, displaying high width-to-length ratios. Most measured water parameters exhibited significant differences between sampling months. The abundance of L. fortunei remained relatively stable over time due to its nearly continuous reproduction in Uruguay. Nonetheless, shell elongation (15.3-22.8 mm) coincided with an increase in dry weight (0.009-0.038 g) from winter to spring. Allometric relationships, primarily following a power-law model, varied between months, ranging from H = 0.39L1.04 to H = 1.36L0.57. This study contributes to the comprehension of the population dynamics and life history of L. fortunei, thereby aiding in the conservation of invaded aquatic systems. Moreover, it provides valuable insights into the effects of urban effluents on this species, contributing to our understanding of its potential role as a bioindicator.

Ecological integrity assessment of streams in the light of natural ecoregions and anthropic land use.

Reference conditions for river bioassessment should be established inside ecoregions. Our objectives were (1) to implement a bioassessment methodology for Uruguayan prairie streams regarding ecoregions and land use and (2) to assess the ecological integrity of streams of the Río Negro basin in Uruguay. Due to logistical constraints, sampling was divided into two collection trips: one including the upper basin in fall 2015 and the other including the lower basin in spring 2016. Basins were analyzed separately due to seasonal and geographical differences. In the streams sampled in fall 2015, conductivity, total nitrogen (TN), and total phosphorus (TP) were higher in sedimentary ecoregions than in crystalline ones, independent on land use. In those sampled in spring 2016, these variables showed the highest values in the ecoregions dominated by agriculture. Eighty percent of the sampled streams presented the impact of cattle in their riparian zone. Discriminant analysis showed a similar composition of macroinvertebrates among ecoregions in 2015, but different composition between land uses. Conversely, in 2016, there were differences among some ecoregions, but not between land uses. Agriculture was correlated with tolerant invertebrates, while natural land use and afforestation were correlated with sensitive ones. The BMWP-Colombia showed the impact of livestock on streams, but in general good water quality, while an index of genera for Uruguay, indicated that all streams are eutrophic, thereby confirming the importance of using different types of metrics. Due to its geographical homogeneity and small size, a smaller number of ecoregions could be defined for stream assessments in the Río Negro basin.

Predicting cyanobacterial biovolume from water temperature and conductivity using a Bayesian compound Poisson-Gamma model.

Eutrophication and climate change scenarios engender the need to develop good predictive models for harmful cyanobacterial blooms (CyanoHABs). Nevertheless, modeling cyanobacterial biomass is a challenging task due to strongly skewed distributions that include many absences as well as extreme values (dense blooms). Most modeling approaches alter the natural distribution of the data by splitting them into zeros (absences) and positive values, assuming that different processes underlie these two components. Our objectives were (1) to develop a probabilistic model relating cyanobacterial biovolume to environmental variables in the Río de la Plata Estuary (35°S, 56°W, n = 205 observations) considering all biovolume values (zeros and positive biomass) as part of the same process; and (2) to use the model to predict cyanobacterial biovolume under different risk level scenarios using water temperature and conductivity as explanatory variables. We developed a compound Poisson-Gamma (CPG) regression model, an approach that has not previously been used for modeling phytoplankton biovolume, within a Bayesian hierarchical framework. Posterior predictive checks showed that the fitted model had a good overall fit to the observed cyanobacterial biovolume and to more specific features of the data, such as the proportion of samples crossing three threshold risk levels (0.2, 1 and 2 mm³ L-1) at different water temperatures and conductivities. The CPG model highlights the strong control of cyanobacterial biovolume by nonlinear and interactive effects of water temperature and conductivity. The highest probability of crossing the three biovolume levels occurred at 22.2 °C and at the lowest observed conductivity (∼0.1 mS cm-1). Cross-validation of the fitted model using out-of-sample observations (n = 72) showed the model's potential to be used in situ, as it enabled prediction of cyanobacterial biomass based on two readily measured variables (temperature and conductivity), making it an interesting tool for early alert systems and management strategies. Furthermore, this novel application demonstrates the potential of the Bayesian CPG approach for predicting cyanobacterial dynamics in response to environmental change.

Agriculture and elevation are the main factors for Pampasic stream habitat and water quality.

Streams of the Pampasic plain in Southeastern South America are ecosystems affected by both water pollution and habitat alteration mainly due to agricultural activity. Water quality is influenced by the quality of habitats and both depend on land use and watershed morphology. The objective of this study was to determine the relationship between the variables of four factors: (1) the morphology of the watershed, (2) land use in the watershed, (3) river habitat, and (4) water quality of wadeable streams in Uruguay, as well as to determine the most representative variables to quantify such factors. We studied 28 watersheds grouped into three ecoregions and four principal activities, which generated seven zones with three to five streams each. Correlations between the variables of each factor allowed reducing the total number of variables from 57 to 32 to perform principal component analyses (PCA) by factor, reducing the number of variables to 18 for a general PCA. The first component was associated with water quality and elevation. The second was associated with the stream and watershed size, the third with habitat quality, and the fourth to the use of neighboring soils and objects in the channel. Our results indicate that agricultural intensity and elevation are the main factors associated with the habitat and water quality of these lowland streams. These factors must be especially considered in the development of water quality monitoring programs.

La comunidad bentnica como indicadora de zonas de degradacion y recuperacion en el arroyo Toledo (Uruguay) / Benthos community as indicator of degradation and recuperation zones in the Toledo (Uruguay)

Macrozoobenthos composition and abundance of an organic polluted stream (A. Toledo, Uruguay) are compared among sites of control (C), degradation (D) and recuperation (R), which were seasonally sampled. Water ionic composition, conductivity, pH, temperature and COD were not different among sites, while oxygen, and BOD did show significant differences. Benthos was more abundant in R mainly due to Heleobia spp. Oligochaetes were dominant in C and D, with Branchiura sowerbyi only in C and imnodrilus hoffmeisteri in D. Hirudinea, mainly Gloiobdella michaelseni, occurred almost only in R. the richness of taxa was higher in R, but its high abundance of Heleobia spp. and Sphaeridae leads to the lowest diversity, which was higher in C than D, and in warm than in cold seasons for these two sites. The logarithmic distribution model shows communities of low evenness in all sites