Interaction between climate change scenarios and biological invasion reveals complex cascading effects in freshwater ecosystems

Climate change often facilitates biological invasions, leading to potential interactive impacts of these global drivers on freshwater ecosystems. Although climatic mitigation efforts may reduce the magnitude of these interactive impacts, we are still missing experimental evidence for such effects under multiple climate change scenarios within a multi-trophic framework. To address this knowledge gap, we experimentally compared the independent and interactive effects of two climate change scenarios (mitigation and business-as-usual) and biological invasion on the biomass of major freshwater trophic groups (phytoplankton, zooplankton, periphyton, macroinvertebrates, and a native macrophyte) and the decomposition rate of allochthonous material. Among the independent effects, we found that the business-as-usual climate treatment resulted in lower native macrophyte biomass and higher periphyton biomass compared to the climatic baseline and mitigation treatments. This indicates the potential of climate change to alter the relative dominance of different freshwater producers and demonstrates that climate mitigation efforts can counteract these effects. Biological invasion alone increased the biomass of chironomids, a dominant macroinvertebrate group in tropical freshwater ecosystems, demonstrating a compensatory effect on climate change. Climate change and biological invasion interactively reduced the decomposition rate of allochthonous detritus, likely mediated by the feeding preference of abundant chironomids for periphytic algae associated with the presence of non-native macrophytes. We concluded that (i) climatic mitigation can maintain climate baseline conditions in freshwater ecosystems, and (ii) the interactive effects between future climate scenarios and biological invasion are related to complex cascading interactions among trophic groups on ecosystem processes.

Methods
We performed an outdoor mesocosm experiment at the Federal University of Rio de Janeiro (Latitude: -22.84, Longitude -43.23) over 35 days between July and August 2021. We used 50 L plastic containers (65.8 cm height and 31.0 cm diameter), each filled with a five cm-deep sediment: a bottom layer of organic substrate (Mega fértil – Box Reef, 1 cm deep) topped with thoroughly washed sand (4 cm deep), all commercially acquired. Each mesocosm was then filled with approximately 30 L of dechlorinated tap water, which was filtered through a 50 μm mesh plankton net. The mesocosms were submerged 20 cm below ground level to simulate shallow ponds or small-scale lagoon compartments.

The native rooted-submerged macrophyte Cabomba caroliniana was established by planting four apical stem fragments (15 cm in length without lateral branches) into the substrate layer of each mesocosm, matching the shoot density range of submerged species in natural conditions (Li et al., 2015). Cabomba caroliniana is native to South America, including Brazilian freshwater environments, and co-occurs with several other native macrophyte species (Schooler et al., 2009). All fragments were cultivated under uniform conditions for ten days before introducing the non-native species H. verticillata as we aimed to simulate the arrival of a non-native species into an ecosystem with established native macrophyte (Petruzzella et al., 2020; Riis & Sand-Jensen, 2006). All macrophyte fragments were commercially acquired from Flora Aquática, Brazil.

The freshwater trophic groups were established through a combination of free colonization and inoculation, depending on their identity. The zooplankton community was established by adding a subsample inoculum (1 L from a total of 500 L) into each mesocosm at the beginning of experiment manipulation. This subsample was collected from several locations within a macrophyte-rich wetland at the Guapiaçu Ecological Reserve (Latitude: -22.45, Longitude: -42.77) using a 50 μm mesh plankton net in the early July 2021. The phytoplankton, periphyton, and macroinvertebrates were established through free colonization, although these organisms were potentially present in the zooplankton inoculum. To evaluate periphyton growth, we attached a 100 cm² Vulcan plastic substrate to a floater in each mesocosm.

Detritus biomass loss was assessed using leaves from four allochthonous tree species commonly found in Tijuca National Park, Rio de Janeiro, Brazil (Latitude: -22.95, Longitude: -43.27): Ficus insipida, Artocarpus heterophyllus, Cecropia melaleuca, and Eugenia brasiliense. Freshly senescent leaves were collected from the forest floor and dried at 60°C until they reached a stable dry weight. We used coarse mesh-size litter bags, which allow colonization of macroinvertebrates, and we filled them with a 2.02 ± 0.06 g mix of dry leaves, equally composed of the four species. Although we used the detritus from the terrestrial matrix and aquatic microfauna typical of wetlands, both encompass the same Atlantic Forest biome.

Experimental design
We established two experimental climate change treatments based on the Representative Concentration Pathways (RCP) that provide future climate expectations according to different predicted greenhouse gas emissions (IPCC, 2023). We selected RCP 4.5 and RCP 8.5 scenarios for a 20-year time-series interval (2080-2099) as representative future climate scenarios. The RCP 4.5 scenario represents future conditions with moderate changes in temperature and rainfall regimes resulting from climate change mitigation policies (Thomson et al., 2011). The RCP 8.5 scenario, known as business-as-usual, represents future climatic conditions resulting from the continuation of current greenhouse gas emissions trends. The BAU scenario predicts comparatively strong changes in the temperature and rainfall regimes, along with an increasing frequency of extreme climatic events (Riahi et al., 2011). We also established a climatic control treatment to represent historical conditions, commonly described as the baseline observed between 1985 and 2004. Hereafter, the three experimental climate treatments are referred to as baseline, mitigation, and BAU.

To establish the experimental climate treatments, we chose a representative year from the 20-year time series interval for both temperature and rainfall datasets. This selection process involved several steps. Firstly, we calculated the standard deviation (SD) of each year within the 20-year time interval concerning the mean value of the 20-year interval for both temperature and rainfall values individually (eq. 1). Next, we summed the standard deviations of temperature and rainfall for each year within the 20-year interval, which represented the total standard deviation (eq. 2).

SDy1 = ∑ (|y|t1 - x̅) + … + (|y|t960- x̅), in which:                   (eq.1)

SDtotal = ∑ SDy1 + … + SDy20.                                                                                (eq. 2)

y = a year within the 20-year time series interval,

|y| = temperature or rainfall absolute value for a year y,

x̅ = 20-year time series interval mean temperature or rainfall,

t = time series interval - every 3 hours for temperature and daily for rainfall.

We selected the year with the lowest total standard deviation compared to the average of the 20-year interval for each scenario: (i) the year 1998 best represented the baseline climate conditions compared to the 1961-2005 time series, whereas (ii) the year 2097 best represented both the mitigation and BAU scenarios compared to the 2080-2100 time series (Figure 1). Selecting a year for each climate scenario ensured (1) the representation of the average climate conditions over the 20-year interval for each treatment, (2) the continuity and variability of temperature and precipitation, and (3) a robust comparison between the experimental climate treatments in this study.

We used predicted data for each representative year of the three climate treatments for Central and South America based on the global circulation models described by the IPCC (Chou, 2014a, 2014b; Lyra, 2018). The modeled temperature and rainfall data were generated by the Brazilian Center of Weather Forecasting and Climate, affiliated with the National Institute for Space Research (CPTEC/INPE), and obtained from the PROJETA platform (https://projeta.cptec.inpe.br/; Chou, 2014a, 2014b; Lyra, 2018). We employed a high-resolution climate change model (0.5 km, continental, HADGEM2-ES) specifically for the municipality of Rio de Janeiro, Brazil (Latitude: -22.90, Longitude: -43.20), where our experiment was conducted. The PROJETA platform provided data on air temperature at 2 m height above the land surface in 3-hour intervals, along with daily precipitation data for each climate change scenario. Using these datasets, we established the temperature and rainfall manipulations for each treatment combination, as outlined in Figure 1. Overall, rainfall volume decreased from mitigation to BAU scenario compared to the baseline. Regarding warming, the mitigation and BAU scenario showed temperatures from 1.0 ± 2.0°C (mitigation, mean ± SD) to 2.6 ± 1.8°C (BAU, mean ± SD) higher than the baseline scenario mean temperature. The mean difference in temperature between mitigation and BAU scenarios was 1.7 ± 2.4°C (mean ± SD).

We implemented a custom-made automated heating system (NAYAD Limno) to manipulate the temperature regime in the mesocosms. This system comprised a temperature sensor and an aquarium heater (80 W, Master, Rio de Janeiro, Brazil) positioned at the top of each mesocosm. These components were connected to a control system where the heater responded to the sensor, which monitored the difference between the current and predicted temperature for each climatic treatment in three-hour intervals. Remarkably, more than 90% of the predicted temperatures were accurately attained within a 3-hour timeframe for all experimental climatic treatments (Figure 1). We observed no significant differences between the monitored and modeled temperatures across any climate change treatment (Supplementary material: Table S1). Rainfall manipulation was carried out daily by adding dechlorinated tap water filtered through a 50 μm mesh size plankton net to the mesocosms to ensure no addition of new individuals. We tracked water volume variation throughout the experiment, noting that BAU treatment exhibited reduced water volume compared to baseline and mitigation treatments (Supplementary material: Figure S1). We also measured ortho-phosphate concentrations and related them to the water volume variation within the climatic treatments using generalized linear mixed-effects models (Supplementary material: Figure S2). We performed the ortho-phosphate analysis as described by Golterman (1978), and no additional nutrients were carried out during the experiment.

The three climatic treatments (baseline, mitigation, and BAU) were factorially combined with the presence of biological invasion. We used the non-native submerged macrophyte Hydrilla verticillata, known for its successful colonization in shallow lakes either as a single dominant species or coexisting with others (Sousa, 2011). Originally native to Asia and Australia, H. verticillata has become cosmopolitan, establishing itself as an invasive species in numerous freshwater ecosystems, including those in Brazil (Langeland, 1996; Sousa, 2011). Hydrilla verticillata is associated with strong negative impacts on aquatic ecosystems, such as the replacement of native aquatic species and the reduction of multiple ecosystem services, which makes this species an ideal model organism for testing the impacts of invasive macrophytes (Calvo et al., 2019; Gentilin-Avanci et al., 2021; Silveira et al., 2018; Umetsu et al., 2012). We highlight that these impacts are especially strong when Hydrilla spreads its populations to new ecosystems and increases biomass over time (Sousa, 2011). In our experiment, H. verticillata was established by adding two apical stem fragments, each 15 cm in length without lateral branches, to the surface water of each mesocosm (i.e., macrophytes were not planted). Such density represents a medium propagule pressure (Li et al., 2015) in their colonization stage under natural conditions, as they can regenerate from fragments that float in the water columns for days or weeks before effectively colonizing the sediment layer (Umetsu et al., 2012). We thoroughly washed all fragments to prevent the accidental transfer of macroinvertebrates, zooplankton, phytoplankton, or periphyton into the mesocosms. Each treatment combination was replicated six times in a spatial block design, resulting in a total of 36 mesocosms (Supplementary material: Figure S6 represents the variation in the field air temperature within each block). Within each spatial block, there was one replicate of all treatment combinations.

Sample processing
We determined the biomass of all freshwater trophic groups at the end of the experiment. Phytoplankton biomass (μg L-1) was estimated using chlorophyll-a concentration assessed in the pelagic zone. Chlorophyll-a concentration was determined by filtering 200 ml of water through Whatman GF/F 0.7 pm filters and subsequently spectrophotometrically using hot (60–70 °C) ethanol (Jespersen & Christoffersen, 1987). Periphyton biomass (DW, g) was determined by vacuum filtering the material detached from the 100 cm² Vulcan plastic substrate. We used pre-burned and pre-weighed Whatman GF 6 filters to determine periphyton ash-free dry mass. The filters were dried at 60 °C for 24 hours to determine the dry weight and then incinerated in a muffle at 500°C for 1 hour to determine the ash-free content.

Zooplankton community biomass (DW m-3, μg) was assessed at the end of the experiment by filtering the total mesocosm volume (Mean volume, Baseline: 22.6 L; Mitigation: 21.1 L; BAU: 11.5 L) using a 50 μm plankton net. The filtered material was concentrated in 100 mL aliquots and fixed with formaldehyde. Enumeration of the zooplankton community was conducted in a Sedgewick-Rafter chamber under an Olympus BX50 microscope for rotifers and cladocerans. Young nauplii and copepodites were quantified separately in open chambers under an Olympus SZ-40 stereomicroscope. Adult copepods were quantified under a microscope and identified using a stereoscopic microscope for detailed observation of identifying traits. Samples were thoroughly evaluated under a stereoscopic microscope in an open chamber to identify rare species. All organisms were identified to the lowest taxonomic level possible. The individual dry weight of rotifers was calculated from the biovolume, where 30 individuals of each species were measured (Ruttner-Kolisco, 1977). To calculate the individual dry weight of cladocerans and copepods, including juvenile forms, a total of 30 individuals of each species and taxonomic category were measured. In cases where samples contained less than 30 individuals, all individuals found were measured. The dry weight of cladocerans and copepods was calculated using the biovolume measurements and published weight-length regressions (Azevedo & Verdade, 2012; Bottrell & Newsome, 1976; Dumont et al., 1975). The total dry biomass of each group was calculated by multiplying the density (ind m-3) by the mean individual dry weight (DW, μg).

Macroinvertebrate biomass (DW, g) was determined by filtering the total mesocosm volume, including the material from washed macrophyte fragments and detritus leaf litter, sorting the sediment through a set of sieves (diameter of 1 mm and 0.5 mm). For the sediment, we sampled an area of 98 cm². All macroinvertebrates were sorted in transilluminated trays and fixed with 70% ethanol for identification to the lowest possible taxonomic level, usually to the genus level. We used the biomass of genus Chironomus (DW, g) as a representative of the macroinvertebrate trophic group due to its very high abundance (encompassing 91.53% of the total macroinvertebrate biomass) and its presence across all treatment combinations. We dried Chironomus individuals at 60 °C for 72 hours and then weighed all individuals in a Mettler UMT2 high precise balance (readability: 0.1 µg).

Native and non-native macrophyte biomass (DW, g) was determined by drying their fragments to a constant mass at 60 °C for 48 hours and individually weighing them using a Shimadzu AUW220D precise balance. Detritus biomass loss (DW, g) was accessed by drying all leaves and leaf fragments from the litterbags individually to a constant mass at 60 °C for 48 hours and weighing them in a laboratory balance. We calculated the leaf biomass loss as the difference in the dry leaf mass between the beginning and end of the experiment. We also performed ammonium and orthophosphate analysis for all mesocosms, following the methods described by Holm-Hansen (1980) for ammonium and Golterman (1978) for orthophosphate.