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Article

Global Warming and Fish Diversity Changes in the Po River (Northern Italy)

by
Anna Gavioli
1,*,
Giuseppe Castaldelli
1,*,
Stefania Trasforini
2,
Cesare Puzzi
2,
Maria Pia Gervasio
1,
Tommaso Granata
3,
Daniela Colombo
3 and
Elisa Soana
1
1
Department of Environmental and Prevention Sciences, University of Ferrara, Via Luigi Borsari 46, 44121 Ferrara, Italy
2
G.R.A.I.A. srl Gestione e Ricerca Ambientale Ittica Acque, Via Repubblica 1, 21020 Varano Borghi, Italy
3
CESI—Italian Electrical and Technical Experimental Center, Via Rubattino 54, 20134 Milano, Italy
*
Authors to whom correspondence should be addressed.
Environments 2024, 11(10), 226; https://doi.org/10.3390/environments11100226
Submission received: 2 September 2024 / Revised: 9 October 2024 / Accepted: 12 October 2024 / Published: 17 October 2024
(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Ecosystem)
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Abstract

:
In the context of climate change, the current rise in temperature, changes in precipitation, and extreme weather events are exceptional and impact biodiversity. Using the Mann–Kendall trend test, change-point analysis, and linear mixed models, we investigated the long-term trends (1978–2022) of water temperature and flow in the Po River, Italy’s largest river, and examined changes in the fish community over the same period. Our findings indicate that the daily water temperature of the Po River increased by ~4 °C from 1978 to 2022, with a significant rise starting in 2005. The river’s daily discharge showed higher variability and decreased from 2003 onwards. The number of days per year with water temperatures above the summer average increased steadily by 1 day per year, resulting in over 40 additional days with above-average temperatures in the last four decades. The number of summer days above the seasonal average water temperature was the most influential factor affecting fish diversity. Total fish species richness and native species richness significantly decreased between 1978 and 2022 with the increasing number of days above the summer average water temperature, while non-native species increased. Our results demonstrate that the Po River is experiencing significant impacts from global warming, affecting freshwater communities.

Graphical Abstract

1. Introduction

One of the biggest concerns facing humanity is climate change since it impacts ecosystem health and biodiversity [1], food security, nutrition, and poverty by altering agrifood systems [2] and aquaculture production [3]. Although climates have changed throughout Earth’s history, the current rate and magnitudes of temperature rise, shifts in precipitation, and the occurrence of extreme weather events are alarming [4]. For example, the global mean surface temperature In the first two decades of the 21st century (2001–2020) was 0.99 higher than in 1850–1900 [5].
Freshwater ecosystems are among the most threatened ecosystems by climate change, with rising temperatures, changes in precipitation and flow, and increased frequency of extreme events [6]. On the other hand, water temperature is one of the most important niche parameters for aquatic organisms, particularly ectotherms, which can be more sensitive to global warming [7].
Climate change can affect aquatic organisms in different ways, for example, driving species range shift, changing the predator-prey relationship [8], promoting generalist species against specialist ones [9], and altering oxygen availability and environmental conditions [10,11]. Climate change can also act at different levels of aquatic biological organisation, from the individual to the community level. For instance, warmer water temperatures can promote smaller body sizes in fish specimens [12] and a general homogenisation of fish communities due to the decline of cold-water species and the expansion of warm-water ones [13].
Climate change rarely acts alone, particularly in freshwater ecosystems, where it interacts with threats like invasive species, land-use changes, reduced connectivity, and alterations in water quantity and quality [6,14]. Climate warming may also enhance the success of species invasions [15] and alter community composition and food web structure [16].
The interactions between various threats complicate our understanding of species loss in communities under climate change. For example, species loss in fish communities can be masked by species turnover, driven by invasive species, or shifts in species distributions due to climate change [17]. Counterintuitively, this can result also in increasing the species richness [18].
Climate change is likely to severely impact the Mediterranean, known for its warm summers and wet winters [19], especially in north-east Italy [20]. Here, climate change impacts are already evident, as evidenced by alterations in precipitation intensity and patterns, air temperature warming, and increased frequency of droughts [21,22,23,24]. In this area, there are some preliminary studies on climate change impacts on agriculture [20], transport and transformation of nutrient loads [25,26], freshwater biota [27], and occurrence of extreme events [28,29]. However, to the best of our knowledge, there are no high-resolution studies on the evolution of the hydrological regime and the water temperature trends in the Po River and on their effects on riverine fish communities. In fact, high-resolution studies on climate change require long-time series data, which are not always available, or models and climate scenarios [30,31]. Therefore, in the present study, we focused on the Po River, the longest river in Italy and the main contributor of freshwater discharges and nutrient loads to the Adriatic Sea, whose basin hosts more than 17 million inhabitants and ~40% of the Italian GDP [32]. For the first time in the Po River, we examined long-term trends, from 1978 to 2022, of water temperature measures in relation to climate warming [1] and water flow measures in relation to drought frequency [28]. Using fish as a taxon model, we identified changes in community composition and species diversity during the same period. As climate warming favours the success of non-native species and harms native communities [15,33], we examined the response of fish species to changes in water temperature and flow, under the hypothesis that in the Po River native species decreased with increasing water temperature and decreasing flow, while non-native species followed an opposite trend.

2. Materials and Methods

2.1. Study Area

The Po River is the longest (652 km) and largest (average discharge 1540 m3 s−1 at the basin closing section) river in Italy, flowing from the north-western Alps to the Adriatic Sea through all of northern Italy. The Po River basin covers 71,000 km2 and includes the most densely urbanised area of Italy with the highest GDP due to intense industrial, agricultural, and livestock activities [32]. This study focused on the middle reach of the Po River, from river km 357 to river km 438 from the source (Figure S1). This reach is characterised by medium to high water velocities and significant water warming in recent decades [26], which cannot be attributed to local heat sources, e.g., discharges from power plants commissioned or implemented after the start of the analysed temperature time series.

2.2. Water Temperature and Flow Data

Continuous water temperature datasets, representative of the middle course of the Po River, have been obtained from two monitoring stations operated by energy companies at two cooling thermoelectric power plants near the city of Piacenza (Emilia–Romagna region, river km 418). Daily average water temperature data, from 1978 to 2005, were recorded at the La Casella power plant operated by the ENEL group (https://www.enel.com/it/media/esplora/ricerca-foto/photo/2020/03/italia-centrale-la-casella, accessed on 1 January 2023; 45°05′30.0″ N, 9°26′44.2″ E) and, from 2006 to 2022, at the power plant of Piacenza operated by the A2A Life Company group (https://www.a2a.eu/en/group, accessed on 1 January 2023; 45°03′37.9″ N, 9°42′19.9″ E).
Water temperature was measured in both locations by resistance temperature detector (RTD) probes with platinum Pt100 resistance thermometers with a nominal resistance of 100 Ω at 0 °C, defined according to IEC 751 (EN 60751). Other sensor characteristics: measuring range 0–40 °C, accuracy ±0.1 °C at 0 °C, 4-wire connection, signal conversion electronics with 4–20 mA output in the range 0–40 °C. The combination of the daily water temperature data from the two nearest stations, described above, did not affect the continuous 45-year time series as verified in the validation procedure Supplementary Information S1, [26]. Indeed, water temperature data from two sampling stations belonging to the official monitoring network of the Environmental Agency of the Emilia–Romagna Region (ARPAE), which are the closest to the monitoring station included in this study but cover a shorter period (2000–2022) and with lower resolution (monthly), showed a very good correlation (r2 = 0.99, p-value < 0.001), confirming the possibility of merging the data from the closest stations. To the best of our knowledge, no data were available before 1978.
Data on river flow (daily average values) were obtained from the permanent records of a gauging station near the city of Piacenza operated by ARPAE and retrieved from the “Hydrological Annals—Second Part” published by ARPAE (Table 1), whose electronic versions are available on the Regional Open Data Portal (https://simc.arpae.it/dext3r/, accessed on 1 January 2023).

2.3. Fish Species Data

Qualitative fish community data were collected to describe the fish community and its changes in the middle course of the Po River, where water temperature and flow data were also recorded (Figure S1).
The temperature and flow series started in 1978, and no earlier data are available. Consequently, the data on the presence-absence of fish species in the middle course of the Po River were obtained from the only reference available for that period [34]. Gandolfi and Le Moli (1977) [34] provided the most complete information on the fish fauna along the entire course of the Po, including a map of the distribution of fish species along three different sections, the upper, middle, and lower. Fish species data in [34] was sampled with the help of professional fishermen, who were common on the Po at the time and who used nets for collecting fish, and by direct interviews with fishermen. Based on the temporal stability of fish assemblages [35], we assumed that fish species in the middle reach of a large river in the plain, such as the Po, cannot disappear from one year to the next without catastrophic events [36], and therefore we referred to the assemblage described in Gandolfi and Le Moli in 1977 to 1978. Fish presence-absence data in the middle course of the Po River for 1988, 1998, 2007, 2017, 2018, 2019, 2020, 2021, and 2022 were obtained from field sampling as part of institutional monitoring programs such as the Po River Fish Inventory commissioned by the Po River Basin Authority [37,38,39,40,41]. Fish samplings in institutional monitoring programs were carried out according to standard procedures published in [42], mainly during the warm season, using electrofishing from boats combined with nets to ensure that all species present were caught. Sampling was replicated spatially to ensure that all macrohabitats within the sampled river reach were covered and temporally to detect the presence of species that make short, and medium-range migrations. A presence-absence matrix of fish species for the middle course of the Po River was created for 1978, 1988, 1998, 2007, 2017, 2018, 2019, 2020, 2021, and 2022 by defining a species as present if it was reported from cited literature sources and absent if not. Fish species were categorised as native or non-native according to their biogeographical origin as established by current scientific literature (e.g., [43]). A species was defined as non-native to the Po River if it was introduced by humans, regardless of the time since its introduction. The brown trout Salmo trutta and the European perch Perca fluviatilis were considered native species in the Po, although their status is still a matter of debate. This conservative choice was based on the impossibility of determining whether the species S. trutta, reported only by Gandolfi and Le Moli 1977 [34], had been introduced at that time and on the presence of P. fluviatilis in Italy because of the last glaciation [44]. Recent taxonomic determinations and corresponding common names are checked in Eschmeyer’s Catalogue of Fishes [45]. For each sampling year, the number of native species (NAT), the number of non-native species (NNS), and the total species richness (TS) were calculated (Table S1).

2.4. Data Analysis

The non-parametric Mann–Kendal trend test was applied to investigate daily water temperature and flow trends from 1978 to 2022, as water temperature and flow did not meet assumptions of the parametric test (e.g., normality assumption examined with the Kolmogorov–Smirnov test). The Mann–Kendall trend test is a commonly used statistical method for determining whether a trend exists in a dataset [46]. The Sen’s slope was used to determine the slope of the identified trend. Finally, Lanzante’s procedure for single change-point detection with the Wilcoxon–Mann–Whitney test was applied to identify the change point in the water temperature and flow series. If a change point was identified, a Mann–Kendal trend test was then performed before and after the change point to highlight different trends in the period.
For the 45-year period, the annual mean, minimum, and maximum water temperature (meanTemp, minTemp, maxTemp; respectively) were calculated from the daily values to investigate annual trends. The summer and winter mean water temperatures (Summer_meanTemp, Winter_meanTemp, respectively) were calculated to investigate seasonal trends. To investigate the increase in days with temperatures above the seasonal average, the days over summer season means (Summer_days) and the days over winter (Winter_days) were calculated. Finally, the annual mean water flow (meanflow), annual minimum water flow (minflow), annual maximum water flow (maxflow), and summer mean flow temperature (Summer_meanflow) were calculated. Seasons with extreme values of temperature (i.e., summer and winter) were included in the analysis to highlight extreme environmental trends, while seasons with intermediate values as spring and autumn were not included in the analysis. Records falling within the period 1 January to 31 March were assigned to the winter season, while records falling within the period 1 July to 30 September were assigned to the summer season. Since annual trends met the assumptions of the parametric test, linear regression was applied to examine variable trends.
Linear mixed effects (LME) models were used to investigate whether the temporal dynamics of the fish community reflected the increase in temperature and the decrease in flow [47]. The total fish species richness (TS), the native (NAT), and the non-native species (NNS) richness were used in the models as response variables. The annual mean water temperature, the number of days per season above the seasonal average temperature in summer and winter, and the mean and minimum annual flow were used as predictors. The predictors were standardised to z scores (mean = 0, variance = 1) prior to model fitting to allow comparison of the coefficients between predictors that were measured on different scales [48]. To account for temporal dependencies, the year of fish data collection was added as a random effect. The restricted maximum likelihood estimation (REML) was used to fit the model [47].
To select the best model, a stepwise process was applied to the Akaike Information Criterion (AIC; [49]) corrected for small sample sizes (AICc; [50]). The selection of the best model was based on Akaike weights (models with large Akaike weights have strong support) and low AICc values [51]. Finally, the direction and magnitude of the effect of the different drivers and associated 95% confidence intervals of the best models were estimated.
All the analyses were performed in R Studio v2023.03 software [52] using R language [53] and trend, scales, lme4 and AICcmodavg R packages [54,55,56,57].

3. Results

3.1. Water Temperature and Flow Trends

From 1978 to 2022, the daily water temperature in the Po River increased by ~4 °C on average, with a maximum value of 31 °C recorded in July 2006 (Figure 1a,b, Table 1). During the same period, the daily river discharge showed a higher variability with a maximum of 11,067 m3 s−1 registered in November 1994 and a minimum of 124 m3 s−1 in July 2022 (Figure 1c,d, Table 1). The daily water temperature and the daily river discharge were significantly correlated, with decreasing discharge associated with increasing temperature (rs = −0.202, p-value < 0.001).
The change point analysis identified the change point of the daily temperature series in 2005 (W = 25,298,004, p-value < 0.001). The Mann–Kendall trend test showed a significant positive trend from 1978 to 2005 (z = 4.241, n = 9980, p-value < 0.001) with a change size identified by Sen’s slope of 0.035 °C·year−1 (Figure 1b). The Mann–Kendall trend test also showed a significant positive trend from 2005 to 2022 (z = 5.0281, n = 6457, p-value < 0.01) with change size identified by Sen’s slope of 0.084 °C·year−1 (Figure 1b and Figure S2a).
In the daily flow series, the changepoint analysis identified the change point of the flow series in 2003 (W = 38,570,875, p-value < 0.001). The Mann–Kendall trend test showed a significant positive flow trend from 1978 to 2003 (z = 4.2918, n = 9172, p-value < 0.001) with a change size identified by Sen’s slope of 2.30 m3 s−1 year−1 (Figure 1d and Figure S2b). Then, the Mann–Kendall trend test showed a significant negative trend from 2003 to 2022 (z = −2.11, n = 7265, p-value = 0.034), with a decrease of −1.31 m3 s−1 year−1.
Significant positive trends in the annual mean, minimum, and maximum water temperature series of the Po River were identified from 1978 to 2022 (R2 = 0.707; p-value < 0.001, R2 = 0.624; p-value < 0.001, R2 = 0.398; p-value < 0.001, respectively) (Figure 2a–c), with an overall warming rate of 0.09 °C year−1, 0.12 °C year−1, and 0.08 °C year−1, respectively.
The number of winter and summer days above the seasonal average temperature increased significantly over the period (R2 = 0.430; p-value < 0.001, R2 = 0.636; p-value < 0.001, Figure 2d,e, respectively), with almost 1 more day year−1 with water temperature exceeding the seasonal mean, which, in turn, resulted in almost 40 days with water temperature above the seasonal mean at the end of the studied period.
Annual hydraulic variables did not follow a significant trend with the exception of summer annual mean flow, which showed a significant negative trend (R2 = 0.170; p-value < 0.01, Figure 2g).

3.2. Fish Community Trends

A total of 51 fish species (29 native and 22 non-native) were recorded in the middle course of the Po River, upstream and downstream of the city of Piacenza, from 1978 to 2022 (Figure 3).
Total species richness and the native species richness showed a significant decrease from 1978 to 2022 (R2 = 0.73, t = −4.65, p < 0.01; R2 = 0.93, t = −10.27, p < 0.01; respectively, Table S1). The richness of non-native species increased significantly during the same period (R2 = 0.47, t = 2.65, p < 0.05, Table S1, Figure 3). Six native species disappeared from the middle reaches of the Po in the first decade between 1978 and 1988: the brown trout (Salmo trutta), the twaite shad (Alosa fallax), the sea lamprey (Petromyzon marinus), the European sturgeon (Acipenser sturio), the brook barbel (Barbus caninus), and the river lamprey (Lampetra zanandreai). During this decade, also the wels catfish, Silurus glanis, appeared in Po River. (Table S1, Figure 3).
In the following decade, from 1988 to 1998, eight native fish species disappeared: the three-spined stickleback (Gasterosteus aculeatus), the Adriatic sturgeon (Acipenser naccarii), the spined loach (Cobitis bilineata), the burbot (Lota lota), the Italian minnow (Phoxinus lumaireul), the South-European nase (Protochondrostoma genei), the roach (Rutilus pigus), the Italian golden loach (Sabanejewia larvata), and the Italian riffle dace (Telestes muticellus) (Table S1, Figure 3). Since 2007, other native species have not been found in the middle reach of the Po River: the tench (Tinca tinca), the Italian nase (Chondrostoma soetta), and the European perch (Perca fluviatilis). In the same period, many non-native species start being recorded, for example, the freshwater bream (Abramis brama), the white bream (Blicca bjoerkna), the asp (Leuciscus aspius), or the roach (Rutilus rutilus). In recent years, also the thinlip grey mullet (Chelon ramada), a marine species, was sampled (Figure 3).
Based on the results of the Akaike Information Criterion for LME models, the number of summer days above the summer temperature mean resulted in the best descriptor for the total species richness (M4 model, Table 2a), which showed a negative pattern along the increasing number of summer days above the seasonal mean temperature (Figure 4a).
The native species richness showed a negative effect with the increasing number of summer days above the summer average temperature, whereas it showed a positive effect with the increasing number of non-native species (Model N4, Table 2, Figure 4b).
The number of summer days above the summer average temperature and the native species richness resulted in the best descriptor for the non-native species richness (Model E4, Table 2), with positive effects (Figure 4c).
Except for the number of summer days above the summer average temperature, other thermal and hydraulic characteristics (i.e., meanTemp, summer_days, winter_days, summer_days_year, meanFlow, summer_meanflow) were not included in the best models.

4. Discussion

4.1. Water Temperature and Flow Trends

Our study has highlighted the effects of climate warming on the riverine ecosystem of the Po River, which has shown a constant increase in water temperature, more pronounced from 2005 to 2022. The number of summer days with water temperature above the summer average temperature resulted in the best factor influencing fish diversity, while the effects of changes in water flow were retained less crucial.
River water temperatures are increasing globally, although the rate of increase varies between regions. Liu et al., 2020 [58] found that the water temperature of rivers near the equator (between 30° S and 30° N) increased by 0.05 °C per year, while the increases in mid and high latitudes were smaller, ranging from 0.002 to 0.01 °C per year. In the United States, river water temperature increased from 0.009 °C year−1 to 0.077 °C year−1, with the most rapid increase found in the Delaware River from 1965 to 2007 [59]. European rivers are no exception to this trend (e.g., [60]). For example, water temperatures in Polish rivers increased from 0.016 °C year−1 to 0.054 °C year−1 between 1984 and 2020 [61]. Despite inter-annual variability due to other climatic factors not considered in our study, such as North American climatic factors [62], the water temperature in the Po River increased faster, considering both the annual rate in the two separated periods (0.035 °C year−1 from 1978 to 2004 and 0.084 °C year−1 from 2005 to 2022) and the annual mean water temperature (0.09 °C year−1 from 1978 to 2022).
Comparable trends are observed in the European Alps’ rivers. For example, the water temperature of two central European mountain rivers increased by 0.024 °C year−1 from 1977 to 2020 and by 0.044 °C year−1 from 1998 to 2020 [63]. In Switzerland, a comprehensive study of streams and rivers showed a clear warming over the last 40 years with positive trends for all four seasons and more pronounced in lowland watercourses than in alpine regions [64], highlighting the critical trends due to climate warming in this region. Moreover, it is not expected that these trends will come to a halt, but rather that they will continue with greater intensity in the coming decades [65]. According to climate projections, the water temperature in the Po basin is also expected to increase in all seasons between 2041 and 2070, with consequences for precipitation and discharge [66].
The warming rate of water temperature in Po River was highlighted also by the marked rise of minimum water temperatures, which suggests that a critical temperature threshold for organisms cannot be respected in the river with consequent changes in biota, for example, phytoplankton communities, sediment bacterial communities, and related processes and water quality [67]. The Po River is not only experiencing an increase in water temperatures but also an increase in the number of exceptional days with water temperatures above the summer seasonal average, peaking at almost 40 days above the summer seasonal average in 2022. These results highlighted that the water of the Po River maintains warm temperatures for a longer period, which in turn can alter the structure and functioning of aquatic ecosystems [68]. Furthermore, the effect of the temperature rise could be intensified by low flow conditions [29,69].
From 1978 to 2022, the river flow exhibited no strong trend, though a notable decrease occurred from 2003 onwards. The lack of a clear trend in the river flow may be due to the greater variability in how climate change may affect water flow conditions in rivers and to the large variability in the basin, as well as to seasonal shifts rather than absolute changes [24,70,71]. The seasonal contribution was most evident in the periods 2003–2007, 2015–2017 and 2020–2022, when the Po River experienced temporary phases of low regime driven by prolonged summer droughts during 2003–2007, 2015–2017, and 2020–2022 [24,29,72,73,74].
The identification of 2003 and 2005 as breakpoints in daily water temperature and daily flows could be influenced by heat waves that hit Europe and Italy during that year [75,76]. Given the severe impact of heat waves on ecosystem health and their expected increase in frequency in the coming years [1], measures to mitigate climate change are essential.
Furthermore, changes in water temperature and flow can greatly amplify their effects, as they are interconnected. For example, the reduction in water flow can be attributed to several factors, including reduced precipitation, reduced snowpack, earlier snowmelt, and increased evaporation [24]. The increase in air temperature could worsen the impacts of these factors on water flow, along with water abstraction for agricultural and domestic use. Consequently, lower flow conditions can promote higher water temperatures with detrimental effects on the environment and human health [61,69].

4.2. Fish Community Turnover

Increasing water temperatures and changes in river flows have significant effects on its ecological processes and on its freshwater communities [77]. However, in the Po River, the number of summer days above the summer average temperature was retained by the LME models as the best predictor among the climatic factors considered in influencing fish communities, while hydraulic features were not significant.
The exclusion of hydraulic characteristics as the best descriptors in explaining fish diversity in Po River may appear surprising. In fact, it is widely acknowledged that fish abundance, diversity, and demographic rates generally respond negatively to changes in flow conditions, which can affect, for example, biological cycles and habitat suitability [78,79,80]. However, the presence-absence data used in our study may not be sensitive enough to detect changes in the overall health and resilience of fish populations in the Po. Rather, it can only provide information on the disappearance of species, which is not a common event due to loss of water availability [81]. Additionally, the middle and lower courses of the Po River have never encountered extreme droughts leading to the interruption of flow. Even during extreme droughts, the river flowed at hundreds of cubic meters per second, reducing negative and irreversible impacts on fish species resulting from intermittent rivers [82].
Furthermore, the exceptionally low flows recorded during this study may have only partially affected the lateral connectivity, since long before the start of the water temperature and flow series of this study, the Po River had already been canalised for a large part of its course by deepening and embanking the central part of the section and by protecting the inner banks with stones. Therefore, the reduction of nursery grounds and habitat availability for fish species could have started before the study period [83,84].
Effects of flow changes on the fish community could be also overridden by other threats such as competition and predation by non-native species [6]. For example, in one of the largest tributaries of the Po River, native fish species were found declining due to the presence of non-native species, despite flow availability [85]. In the Po River, there are no studies available on competition between fish species, but predation by a large predator such as the Wels catfish Silurus glanis could have led to the disappearance of common native species, such as the tench Tinca tinca and the Italian nase Chondrostoma soetta, at least in the lower Po basin [86,87].
According to LME models, the decline in native fish species and the increase in non-native species resulted from the prolongation of warm periods. Species with lower tolerance to higher temperatures, such as the brown trout (S. trutta), the brook barbel (B. caninus), the river lamprey (L. zanandreai), the Italian minnow (P. lumaireul), the South European nase (P. genei), and the Italian riffle dace (T. muticellus) [88], probably suffered more from the rise in temperature and were never found in the middle course of the Po in the recent decades.
As data prior to 1978 are not available, we cannot exclude the possibility that the decline of some native species due to rising water temperatures began earlier, as species extinction is the irreversible conclusion of a population decline. Additionally, changes in fish population structure, with more small-size species and young age classes, could also occur [12]. Furthermore, our analysis is based on presence-absence data and therefore cannot selectively assess the decline for key species in terms of abundance, which could better inform population decline [89].
An example of a species that has likely suffered from water warming before the period considered in this study is the South European nase (P. genei). Historical monitoring documents and interviews with recreational and commercial fishermen indicate that the South European nase was dominant in the middle reaches of the Po until the mid-1970s and still abundant in the lower reaches in the 1980s [90,91]. Based on our data, this species has not been reported since 2007, when the water temperature increased rapidly, but it is also likely that there has been a gradual decline in density over the last two decades, due to a number of cofactors that are challenging to detect at present.
Rising temperatures may not be the only factor in shaping fish diversity, but other disturbances, such as pollution, eutrophication, and overfishing, may also have played an important role [6]. Overexploitation due to excessive fishing pressure has been identified as the main cause of the extinction of European sturgeon (Acipenser sturio) in the Po River and in the north-western Adriatic Sea [92,93]. No studies have been carried out in the same area on the twait shad (A. fallax) and the sea lamprey (P. marinus), but both species have been affected by the increase in fishing effort, which was not subject to any restrictions in the early 1980s.
Official data on commercial fish catches could provide more information on species abundance trends. However, commercial fishing significantly declined with the decrease in abundance of native target species (e.g., eel and sturgeon) during the early period of the study and became almost negligible by the end of the 1990s. Obtaining such commercial data is challenging and often requires retrieving historical records from municipal archives if they are still available. However, this could be an opportunity to investigate in future research.
During the decade from 1988 to 1998, the Po River experienced an increase in pollution and eutrophication conditions [32], which could be the cause of the loss of native species such as the three-spined stickleback (G. aculeatus), the spiny loach (C. bilineata), the Italian golden loach (S. larvata), and the roach (R. pigus), despite their tolerance to high water temperatures. Disentangling the contributions of warming waters and non-native species to native ones has become increasingly difficult in recent years due to the interrelated factors and complex ecological dynamics that have been occurring [94]. In recent years, reflecting the trend that has also been identified on a broader scale [95], the fish community in the middle section of the Po River is still composed of a few species, most of them non-native. Many of the non-native species reported in the Po River were not warm or tropical species, as predicted to increase with warming conditions [96,97], but species originated from Eastern Europe, from rivers at higher latitudes and lower water temperatures than the Po (e.g., bream A. brama, white bream B. bjoerkna, asp L. aspius, or roach R. rutilus). As a result, the warmer conditions in the Po may have favoured the spread of such highly adaptable species, in spite of their preference for water temperature [98]. It is also possible that the establishment in the Po of prey and predators from Eastern Europe was facilitated by the co-evolution of the species [86,99].
During the study period, the sporadic sampling of fish species, such as Leucos aula and Microptereus salmoinedes, is likely attributable to occasional dispersal events from the major alpine lakes to the emissaries and eventually to the Po River, where they were occasionally sampled. However, the intermittent capture rates and the lack of evidence for a reproducing population in the Po River during this period suggest that these occurrences were exceptional and are far from representing an established population.
The temporal extension of our data series is 45 years, during which numerous significant alterations in the fish community composition have occurred. As a result, it is challenging to project future trends in fish diversity in the Po River. Notwithstanding, studies conducted in other regions (e.g., [100]) and global scale studies (e.g., [101]) have yielded general insights into prospective diversity trends under climate change. These studies predict a notable decline in freshwater fish communities, with the loss of nearly half of the species in the coming decades and a rising species invasion success [15].

5. Conclusions

Climate change affects freshwater ecosystems in a variety of ways, from warming temperatures to changes in hydrological conditions. In line with this global trend, our data showed that the Po River is suffering from an increase in water temperature, leading to an increase of ~4 °C from 1978 to 2022. Although climate change assessments have largely ignored freshwater fish, we found that native fish species showed a negative trend along warming water in the Po River.
To better understand how rising temperatures have affected and will affect fish communities, future studies should consider data on functional trait diversity and abundance.
This analysis could consider this response, which is typically species-specific, with cold-water species negatively affected and warm-water or eurythermal species favoured by rising water temperature. In addition, future studies should examine how climate change interacts with other threats, such as the spread of invasive fish species and relative changes in food web structure, changes in land use and river connectivity, and changes in water quantity and quality, as well as changes in human activities, such as commercial and sport fishing.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/environments11100226/s1, Figure S1: Map of the study area; Figure S2: Boxplots of daily water temperatures and flows of the Po River from 1978 to 2022; Table S1: Total fish species richness, native fish species richness, and non-native fish species richness sampled in the Po River; Supplementary Information S1: Validation procedure to reconstruct the continuous 45-year time series from the daily water temperature values.

Author Contributions

Conceptualization, G.C., A.G. and E.S.; methodology, A.G. and E.S., validation, G.C. and E.S.; formal analysis, A.G.; investigation, A.G., M.P.G., C.P., S.T., D.C., T.G. and E.S.; data curation, M.P.G., E.S., C.P., S.T., D.C. and T.G.; writing—original draft preparation, A.G.; writing—review and editing, E.S. and G.C.; visualization, A.G.; supervision, G.C. and E.S.; funding acquisition, G.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the EcosistER Project under the National Recovery and Resilience Plan (NRRP) Mission 4 Component 2 Investment 1.5—Call for tender No. 3277 of 30/12/2021 of Italian Ministry of University and Research funded by the European Union—NextGenerationEU (Project code ECS00000033) within WP3—Biotic and abiotic marine resources of the Spoke 5—Circular economy and blue economy CUP 78H22000410006.

Data Availability Statement

Data will be made available upon request.

Acknowledgments

The authors express their gratitude to the Fisheries Bureau of the Emilia-Romagna Region for the long-lasting constructive cooperation and to three anonymous reviewers who help to improve the manuscript.

Conflicts of Interest

Stefania Trasforini, Cesare Puzzi were employed by G.R.A.I.A. srl Gestione e Ricerca Ambientale Ittica Acque, the remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Environments 11 00226 g001
Figure 1. Daily water temperature (a,b) and flows (c,d) data of the Po River from 1978 to 2022, collected in its middle section. In (b,d), statistically significant trends are also shown by blue dashed lines, with the point of change marked by a red vertical bar.
Figure 1. Daily water temperature (a,b) and flows (c,d) data of the Po River from 1978 to 2022, collected in its middle section. In (b,d), statistically significant trends are also shown by blue dashed lines, with the point of change marked by a red vertical bar.
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Figure 2. Trends in annual water temperature and water flow from 1978 to 2022 in the Po River are registered in its middle section. Blue-dashed lines show statistically significant trends: (a) annual mean water temperature, (b) annual maximum and (c) annual minimum water temperature, (d) number of winter days and (e) number of summer days above the seasonal temperature mean, (f) annual mean and minimum discharge, and (g) summer mean discharge. Statistical significance (p-value) and R2 of the models are also shown.
Figure 2. Trends in annual water temperature and water flow from 1978 to 2022 in the Po River are registered in its middle section. Blue-dashed lines show statistically significant trends: (a) annual mean water temperature, (b) annual maximum and (c) annual minimum water temperature, (d) number of winter days and (e) number of summer days above the seasonal temperature mean, (f) annual mean and minimum discharge, and (g) summer mean discharge. Statistical significance (p-value) and R2 of the models are also shown.
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Figure 3. Traffic-light plot representing the fish species sampled in the middle reaches of Po River: green represents the species presence and orange represents the species absence in the sampling year. The scientific name, and native, and non-native statuses are also given.
Figure 3. Traffic-light plot representing the fish species sampled in the middle reaches of Po River: green represents the species presence and orange represents the species absence in the sampling year. The scientific name, and native, and non-native statuses are also given.
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Figure 4. Summary of estimates for the best correlating models: (a) the total fish richness (model M4), (b) the native fish richness (model N4), and (c) the non-native fish richness (model E4). Gray indicates a negative effect, and black indicates a positive effect. The year of sampling was included as a random effect. (Summer_days = Days above the summer season mean). Significance is also shown: *** p-values < 0.001, * p-values < 0.05.
Figure 4. Summary of estimates for the best correlating models: (a) the total fish richness (model M4), (b) the native fish richness (model N4), and (c) the non-native fish richness (model E4). Gray indicates a negative effect, and black indicates a positive effect. The year of sampling was included as a random effect. (Summer_days = Days above the summer season mean). Significance is also shown: *** p-values < 0.001, * p-values < 0.05.
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Table 1. Abbreviations, variable descriptions, units, and statistics of water temperature and flow variables from 1978 to 2022 in the middle course of the Po River.
Table 1. Abbreviations, variable descriptions, units, and statistics of water temperature and flow variables from 1978 to 2022 in the middle course of the Po River.
AbbreviationVariable UnitMinMaxMeand.s.
meanTempAnnual mean water temperature °C12.7317.6114.891.41
minTempAnnual minimum water temperature °C1.007.493.681.68
maxTempAnnual maximum water temperature °C23.5031.0026.491.92
Summer_meanTempSummer mean water temperature °C20.6025.9322.571.45
Winter_meanTempWinter mean water temperature from °C4.1811.517.981.68
Summer_daysNumber of days during the summer season with water temperatures exceeding the seasonal meanNumber of days6.0082.0048.8220.02
Winter_daysNumber of days during the summer season with water temperatures exceeding the seasonal meanNumber of days07939.4219.97
MeanflowAnnual mean water flow m3 s−13151435913255
MinflowAnnual minimum water flow m3 s−112456433090
MaxflowAnnual maximum water flow m3 s−159511,06847862016
Summer_meanflowSummer mean water flow m3 s−12031119675218
maxTempAnnual maximum water temperature from 1978 to 2022°C23.5031.0026.491.92
Summer_meanTempSummer mean water temperature from 1978 to 2022°C20.6025.9322.571.45
Winter_meanTempWinter mean water temperature from 1978 to 2022°C4.1811.517.981.68
Table 2. Summary of AIC results for the selection of linear mixed effects (LME) models correlating (a) total fish richness, (b) native fish richness, and (c) non-native fish richness with hydraulic and thermal predictors (abbreviations are given in Table 1). The year of sampling was included as a random effect. The number of estimated parameters for each model (K), the Akaike’s information criterion (AIC), the corrected AIC (AICc), the delta corrected AIC (Delta_AICc), the Akaike weights (AICcWt), and the cumulative Akaike weights (CumWt) are shown.
Table 2. Summary of AIC results for the selection of linear mixed effects (LME) models correlating (a) total fish richness, (b) native fish richness, and (c) non-native fish richness with hydraulic and thermal predictors (abbreviations are given in Table 1). The year of sampling was included as a random effect. The number of estimated parameters for each model (K), the Akaike’s information criterion (AIC), the corrected AIC (AICc), the delta corrected AIC (Delta_AICc), the Akaike weights (AICcWt), and the cumulative Akaike weights (CumWt) are shown.
(a) Mod.Explanatory
Variable		Component ModelKAICAICcΔAICcAICcWtCumWtLL
M4Total richnesssummer_days414.0622.0600.940.94−3.03
M3Total richnesssummer_days + summer_meanflow514.4829.487.420.020.96−2.24
M5Total richnesssummer_days + meanTemp514.7629.767.70.020.98−2.38
M6Total richnesssummer_days + winter_days514.7929.797.730.021−2.4
M2Total richnesssummer_days + winter_days+ summer_days_year + summer_meanflow714.3670.3648.301−0.18
M1Total richnessmeanTemp + summer_days+ winter_days + summer_days_year+ meanFlow812.17156.17134.11011.91
(b)Explanatory
Variable		Component ModelKAICAICcΔAICcAICcWtCumWtLL
N4Native richnesssummer_days + NNS59.8524.8500.990.990.07
N3Native richnesssummer_days + summer_meanflow + NNS67.4235.4210.560.0112.29
N5Native richnesssummer_days + meanTemp + NNS68.1336.1311.28011.93
N6Native richnesssummer_days + winter_days + NNS611.0439.0414.18010.48
N1Native richnesssummer_days + winter_days+ summer_days_year + summer_meanflow + NNS82.73146.73121.88016.63
N2Native richnessmeanTemp + summer_days+ winter_days + summer_days_year+ meanFlow + NNS85.09149.09124.24015.45
(c)Explanatory
Variable		Component ModelKAICAICcΔAICcAICcWtCumWtLL
E4Non-native
richness		summer_days + Nat52.7117.7100.740.743.65
E5Non-native
richness		summer_days + meanTemp + Nat6−8.1319.872.160.250.9910.07
E3Non-native
richness		summer_days + summer_meanflow + Nat60.3528.3510.65015.82
E6Non-native
richness		summer_days + winter_days + Nat61.9529.9512.24015.03
E2Non-native
richness		meanTemp + summer_days+ winter_days + summer_days_year+ meanFlow + Nat8−6.09137.91120.20111.04
E1Non-native
richness		summer_days + winter_days+ summer_days_year + summer_meanflow + Nat8−2.82141.18123.48019.41
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MDPI and ACS Style

Gavioli, A.; Castaldelli, G.; Trasforini, S.; Puzzi, C.; Gervasio, M.P.; Granata, T.; Colombo, D.; Soana, E. Global Warming and Fish Diversity Changes in the Po River (Northern Italy). Environments 2024, 11, 226. https://doi.org/10.3390/environments11100226

AMA Style

Gavioli A, Castaldelli G, Trasforini S, Puzzi C, Gervasio MP, Granata T, Colombo D, Soana E. Global Warming and Fish Diversity Changes in the Po River (Northern Italy). Environments. 2024; 11(10):226. https://doi.org/10.3390/environments11100226

Chicago/Turabian Style

Gavioli, Anna, Giuseppe Castaldelli, Stefania Trasforini, Cesare Puzzi, Maria Pia Gervasio, Tommaso Granata, Daniela Colombo, and Elisa Soana. 2024. "Global Warming and Fish Diversity Changes in the Po River (Northern Italy)" Environments 11, no. 10: 226. https://doi.org/10.3390/environments11100226

APA Style

Gavioli, A., Castaldelli, G., Trasforini, S., Puzzi, C., Gervasio, M. P., Granata, T., Colombo, D., & Soana, E. (2024). Global Warming and Fish Diversity Changes in the Po River (Northern Italy). Environments, 11(10), 226. https://doi.org/10.3390/environments11100226

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