Hydrobiologia DOI 10.1007/s10750-017-3403-0
REVIEW PAPER
Exploring the effects of salinization on trophic diversity in freshwater ecosystems: a quantitative review Anakena M. Castillo Luis F. De Leo´n
. Diana M. T. Sharpe . Cameron K. Ghalambor .
Received: 5 June 2017 / Revised: 24 August 2017 / Accepted: 2 October 2017 Ó Springer International Publishing AG 2017
Abstract Salinization of freshwater ecosystems represents a potential threat to biodiversity, but the distribution of salinity tolerance among freshwater organisms and its functional consequences are understudied. In this study, we reviewed global patterns of salinity tolerance across a broad range of freshwater organisms. Specifically, we compared published data on LC50 (a metric of salinity tolerance) across climatic regions, taxa, and functional feeding groups (FFGs). We found that microinvertebrates were more sensitive to salinity than vertebrates and macroinvertebrates. Within aquatic insects, there was considerable variability in tolerance across FFGs. Specifically, scrapers, gatherers, and filterers were more sensitive on Handling editor: Eric Larson
average than omnivores, shredders, and predators. Thus, we predict that increasing salinization can negatively impact trophic diversity and in turn cause overall changes in the structure and function of freshwater ecosystems. We also identified both historical exposure and taxonomic affinity as potential drivers of contemporary salinity tolerance across freshwater organisms. Finally, we found important gaps in our understanding of the potential impacts of salinization on freshwater biodiversity, particularly in regions expected to be affected by increased salinization due to climate change and secondary salinization. Understanding the differential vulnerability of freshwater taxa is critical to predicting the ecosystem impacts of salinization, and informing conservation and management decisions.
Electronic supplementary material The online version of this article (doi:10.1007/s10750-017-3403-0) contains supplementary material, which is available to authorized users. A. M. Castillo L. F. De Leo´n Centro de Biodiversidad y Descubrimiento de Drogas, Instituto de Investigaciones Cientı´ficas y Servicios de Alta Tecnologı´a (INDICASAT-AIP), PO Box 0843-01103, Panama´ 5, Repu´blica de Panama´ A. M. Castillo Department of Biotechnology, Acharya Nagarjuna University, Guntur, India
C. K. Ghalambor Department of Biology, Colorado State University, Fort Collins, CO 80523, USA L. F. De Leo´n (&) Department of Biology, University of Massachusetts Boston, Boston, MA 02125, USA e-mail:
[email protected]
D. M. T. Sharpe Department of Biology, McGill University, 1205 Ave. Docteur Penfield, Montre´al, QC H3A 1B1, Canada
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Hydrobiologia
Keywords Climate change Biodiversity Functional diversity Human disturbances Macroinvertebrates Salinity tolerance
Introduction Abiotic factors are important drivers of population and community structure in freshwater environments (Piscart et al., 2005). Along with temperature, dissolved oxygen, and turbidity, salinity (the amount of dissolved salt per unit of water; Williams & Sherwood, 1994; Pinder et al., 2005; Waterkeyn et al., 2008) is often a major determinant of variation in the composition of freshwater communities (Hart et al., 1990; James et al., 2003; Nielsen et al., 2003; Piscart et al., 2005; Szo¨cs et al., 2014). Salinity can vary in freshwater environments, both due to natural (e.g., tidal influences, seasonal cycles, wind or rain; Williams, 2001; Rengasamy, 2006; Herbert et al., 2015) and anthropogenic disturbances (e.g., climate change/ sea-level rise, secondary salinization; Williams, 2001; Can˜edo-Argu¨elles et al., 2013; Herbert et al., 2015). The latter are currently thought to be responsible for increasing salinization of historically freshwater environments (Hart et al., 1990, 1991; James et al., 2003; Nielsen et al., 2003; Horrigan et al., 2005), and are the focus of our review. Salinization can reduce survival by affecting basic functions such as osmoregulation and reproduction (Hart et al., 1991; Hassell et al., 2006; Karraker, 2007), but freshwater species vary in their ability to tolerate changes in salinity (Dunlop et al., 2007; Kefford et al., 2012a, b). Therefore, the understanding of how salinity alters species composition and ecosystem function represents a major challenge for predicting changes in freshwater biodiversity. Collectively, there is considerable variation in salinity tolerance in freshwater organisms, ranging from strictly freshwater species (salinity \ 0.5%) to highly tolerant species capable of inhabiting hypersaline environments (salinity [ 50%). For example, tadpoles of Rana syvaltica cannot tolerate even the slightest increase in salinity (Sanzo & Hecnar, 2006), whereas other amphibian species can thrive in brackish water (e.g., cane toad, Rhinella marina; De Leo´n & Castillo, 2015). Similar variability is observed in fish (Kozak et al., 2013), crustaceans (Dunlop et al., 2007;
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Horrigan et al., 2007), and aquatic insects (Piscart et al., 2005; Dunlop et al., 2007). Although the biochemical and physiological mechanisms underlying salinity tolerance have been extensively studied in various aquatic species, few studies have considered how interspecific salinity tolerance varies across taxa and regions, and how this variation could affect trophic diversity—a crucial component determining community structure and ecosystem function in freshwater ecosystems. To explore this issue, we review the existing literature on salinity tolerance in freshwater organisms. Our goal is to understand if different taxonomic and functional groups (e.g., predators, scrapers, etc.) are differentially vulnerable to changes in salinity, and then use these trends to infer potential changes in community structure and function with increasing salinization. Examining both taxonomic and trophic diversity will allow us to simultaneously understand potential phylogenetic contributions to susceptibility, as well as its contemporary functional consequences. In addition, we use these trends to explore potential drivers of global patterns of salinity tolerance across aquatic organisms. Specifically, we consider the role of both historical exposure and taxonomic (phylogenetic) affinity as drivers of contemporary salinity tolerance across our entire dataset. Historical exposure could result in high tolerance in organisms occupying regions historically exposed to high levels of salinity (Kay et al., 2001; Ryder & Vink, 2007; Kefford et al., 2012a). By contrast, taxonomic affinity could result in salinity tolerance patterns mediated by phylogenetic relationships across taxonomic groups rather than geography (Cheng, 2005). A more reticulated pattern showing the effects of both historical exposure and taxonomic affinity could also be expected. Understanding interspecific variation in salinity tolerance also has important applied implications, because differential vulnerability in the face of increasing anthropogenic salinization may result in significant changes to freshwater ecosystems humans depend on (Hart et al., 1991; Nielsen et al., 2003; Kaushal et al., 2005; Kefford et al., 2016). Indeed, it has been predicted that increasing salinity will result in changes in biodiversity, community composition, and productivity in freshwater environments (Kaushal et al., 2005; Piscart et al., 2006; Pond, 2010; Kefford et al., 2011; Szo¨cs et al., 2014; Herbert et al., 2015).
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We largely focus on aquatic macroinvertebrates (primarily aquatic insects), both because of the availability of data for this group, and because of their ecological importance in freshwater food webs (Cummins, 1973; Merritt et al., 1996; Wallace & Webster, 1996; Covich et al., 1999; Ramı´rez & Gutie´rrez-Fonseca, 2014). Macroinvertebrates perform clearly defined functions in freshwater environments including reducing and cycling organic matter (e.g., scrapers, shredders, filterers, and gatherers), as well as being predators and prey for many aquatic organisms (Cummins, 1973; Wallace & Merritt, 1980; Cummins et al., 1989; Palmer et al., 1996; Wallace & Webster, 1996; Covich et al., 1999; Merritt et al., 2002). Furthermore, they influence key ecosystem processes such as nutrient recycling, primary production, decomposition, and transformation of material (Wallace & Merritt, 1980; Wallace & Webster, 1996; Dobson et al., 2002). It is therefore expected that changes in the abundance (or complete loss) of particular functional groups of macroinvertebrates could have substantial ecosystem-level effects. To allow broader-scale comparisons, we also included other taxa (fish, amphibians, and microinvertebrates) whenever data were available in the literature.
Methods Literature review We conducted an extensive literature review to explore how salinity tolerance varies across freshwater organisms. This literature review was divided in two phases. First, we searched the peer-reviewed literature to collect experimental data on salinity tolerance using a common metric, the concentration of salinity where 50% of the individuals tested die (LC50). We searched combinations of the following terms: ‘salinity tolerance’, ‘LC50’, ‘aquatic insects’, ‘freshwater organism’, ‘macroinvertebrates’, ‘freshwater vertebrates’, and ‘freshwater ecosystem’. These searches were performed in Web of Science and Google Scholar, and were not restricted by year of publication or taxon. Second, we gathered data from the following databases: the AQUIRE (Aquatic Information Retrieval) component of the U.S. EPA ECOTOX database (http://cfpub.epa.gov/ecotox/), EcoSun Laboratories, and toxicity databases from the Unilever Centre for
Environmental Water Quality and Institute for Water Research (UCEWQ-IWR); (SEWRPC Community Assistance Planning Report, 2001; Kefford et al., 2003; Palmer et al., 2004; Browne, 2005; Slaughter, 2005). Our complete Database is available on the Dryad Digital Repository (https://doi.org/10.5061/ dryad.c6v4p). From each of these sources, we extracted LC50 values derived from experimental laboratory conditions where salinity tolerance was estimated using NaCl in the form of sea salt, sea water, synthetic sea water, and artificial salt. We did not include other salt types in our analysis because different salts could have different levels of toxicities (Kunz et al., 2013), and because NaCl is one of the most common pollutants resulting from the salinization of freshwater environments (Hamilton et al., 1975; Dickman & Gochnauer, 1978). We focused on LC50 values because they are widely reported in the literature and because they provide a standardized, quantitative estimate of salinity tolerance (Kefford et al., 2004c). Although these values are derived from laboratory tests rather than field experiments, previous studies suggest that LC50 estimates are correlated with salinity tolerance in natural environments (Kefford et al., 2004c; Horrigan et al., 2007) and therefore, can be useful to predict community and ecosystem-level effects. Most LC50 values were expressed in terms of EC (Electrical Conductivity) in units such as mS cm-1 or uS cm-1. To compare across studies, LC50 values reported in mS cm-1, uS cm-1, mg/l, and ppm were converted to ppt or % (parts per thousand or g/l), using the formula: TDS (mg/l) = water salinity (uS/cm) 9 0.68 (Hart et al., 1991). We then built a database with detailed taxonomical (Phylum, Order, Family, Genus), ecological (functional feeding group), and geographical (e.g., country, climate, latitude, longitude) information for each organism. Each organism was assigned to one of the following functional feeding groups (FFGs): bacterivore, filterer, gatherer, herbivore, omnivore, parasite, predator, scraper, or shredder. These FFGs were assigned based on the organism’s diet and trophic level, following standard FFGs for invertebrates and vertebrates from the literature (Table 1). Functional feeding groups are often assigned at high taxonomic levels in the literature (i.e., Pratt & Cairns, 1985; Merritt et al., 1996; Ramı´rez & Gutie´rrez-Fonseca, 2014); however, this can introduce
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Hydrobiologia Table 1 Standard Functional Feeding Groups (FFGs) in freshwater organisms used in this study FFGs
Function
Prevalent food source
Representative taxa
Reference
Bacterivore
Filters tiny particles, such as bacteria
Bacteria
Microinvertebrate (protozoan)
Pratt & Cairns (1985)
Filterer/collector
Filters fine organic particles in the water column
Detritus particles
Invertebrate
Gatherer/collector
Collects fine sediments and deposits materials in the stream bottom
Detritus particles
Invertebrate
Merritt et al. (1996, 2008), Thorp & Rogers (2011), Ramı´rez & Gutie´rrez-Fonseca (2014) Merritt et al. (1996, 2008), Thorp & Rogers (2011), Ramı´rez & Gutie´rrez-Fonseca (2014)
Herbivore
Eats large amounts of plants materials
Plant materials
Vertebrate
Noble et al. (2007)
Scraper
Feeds on materials on rocks, wood or hard surfaces
Periphyton, detritus particles
Invertebrate Vertebrate
Merritt et al. (1996, 2008), Altig et al. (2007), Thorp & Rogers (2011), Ramı´rez & Gutie´rrezFonseca (2014)
Shredder
Cuts, chews plant material
Materials from higher plants
Invertebrate
Merritt et al. (1996, 2008), Tomanova et al. (2006), Boyero et al. (2011), Ramı´rez & Gutie´rrez-Fonseca (2014)
Omnivore
Generalist, consumes a variety of food materials (photosynthetic organisms and animal materials)
Variety of food materials (photosynthetic organisms and animal materials)
Invertebrate
Noble et al. (2007), Thorp & Rogers (2011), Ramı´rez & Gutie´rrez-Fonseca (2014)
Parasite
Absorbs food or fluids from living organisms
Predator
Catches living organisms
Animal materials
Vertebrate
Invertebrate
Gooderham & Tsyrlin (2002), Thorp & Rogers (2011)
Invertebrate
Merritt et al. (1996, 2008), Noble et al. (2007), Thorp & Rogers (2011), Ramı´rez & Gutie´rrezFonseca (2014)
Vertebrate
biases whenever there is diet variation among taxa. Therefore, whenever possible, we assigned FFGs both at the level of Family (which allowed for a larger sample size, but poorer taxonomic resolution), and at the level of genus (which restricted our sample size, but provided higher taxonomic resolution). Furthermore, to disentangle the effect of salinity on common species, we repeated the above analyses by focusing on the traditional EPT (Ephemeroptera, Plecoptera, and Trichoptera) insect taxa alone. These EPT taxa have been previously found to be highly sensitive to salinity (Pond, 2010; Kefford et al., 2011, 2016; Cormier et al., 2013), and therefore crucial as bioindicators (e.g., Rosenberg & Resh 1993; Helson & Williams, 2013; Leigh et al., 2013; Conti et al., 2014).
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Finally, we assigned a geographical location to each study using either the precise geographical coordinates reported in the study (when available) or using Google Earth to estimate coordinates for the general locality. We then classified each location into one of the following four climate categories: Temperate, Cold, Tropical or Arid, following the classification used by Peel et al. (2006), Kottek et al. (2006). Data analysis All data on salinity tolerance (LC50) were square root transformed to meet the assumptions of normality and homoscedasticity before performing two sets of analyses. First, using the entire dataset, we fit a linear model to test for variation in salinity tolerance (LC50)
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as a function of climatic region (Arid, Cold, Temperate, and Tropical), group (Vertebrates, Microinvertebrates, and Macroinvertebrates), FFG (Bacterivore, Filterer, Gatherer, Herbivore, Scraper, Shredder, Omnivore, Parasite, and Predator), and their interaction. Second, using data from aquatic insects only, we fit a separate linear model to test for variation in salinity tolerance across climatic regions, taxa (Orders), FFGs at Genus level, and their interaction. We focused on aquatic insects here because they had robust sample sizes (Table 2), and because their functional groups are well established in the literature (Pratt & Cairns, 1985; Merritt et al., 1996; Gooderham & Tsyrlin 2002; Altig et al., 2007; Noble et al., 2007; Ramı´rez & Gutie´rrez-Fonseca, 2014; Table 1). We also examined cumulative frequency distributions of salinity tolerance values to estimate Kaplan–Meier survival functions (Kefford et al., 2012a). We performed this analysis as an alternative way to estimate the sensitivity of organisms to different salinity concentrations (Kefford et al., 2012a). Finally, to quantify variability in salinity tolerance, we estimated the coefficient of variation (CV = s/x), which represents the ratio of the standard deviation (s) to the mean (x). All analyses and plotting were performed using the statistical software R (R Development Core, 2008).
estimates were from the USA (42%), Australia (25%), or South Africa (19%), with most other countries represented by only one study (14%). Only one study reported LC50 values for the Neotropics (i.e., Mexico; Table 3). Across the entire dataset, salinity tolerance varied significantly across groups, FFGs, and climatic regions (Table 4; Figs. 1, 2). With respect to group, vertebrates and macroinvertebrates were more tolerant, and showed higher variability in tolerance, relative to microinvertebrates (Figs. 1A, 2A). With respect to FFGs, omnivores tended to be the most tolerant, whereas filterers, gatherers, and scrapers were the least tolerant, particularly in cold climates. In addition, predators from cold climates also appeared to present low tolerance (Fig. 1B). Finally, the effects of climatic region, although significant, were difficult to generalize, given that there was also a significant interaction with FFG and Taxa (Table 4), and their rank order varied across FFGs. For instance, among filterers and gatherers, tropical species were the most tolerant, but among omnivores, cold-climate species were the most tolerant (Fig. 1B). Salinity tolerance across aquatic insects Salinity tolerance in aquatic insects also varied significantly across climatic regions, Orders, FFGs, and their interaction (Figs. 2B; 3; Table 5). The most tolerant Orders (i.e., the highest mean LC50) were Odonata, Coleoptera, Diptera and Hemiptera, and the most sensitive Order was Ephemeroptera. This pattern was consistent across climatic regions (Fig. 3A). The
Results We found a total of 915 LC50 values from 42 published studies and nine reports/theses (Table 3; https://doi. org/10.5061/dryad.c6v4p). The majority (86%) of
Table 2 Number of LC50 estimates for different orders of aquatic insects Order
Coleoptera Diptera Ephemeroptera Hemiptera Lepidoptera Megaloptera
LC50 estimates (data points)
Number of families
Number of genera
79
8
38
Filterer, gatherer, predator, scraper, shredder
58 165
10 10
22 27
Filterer, gatherer, predator Filterer, gatherer, predator, scraper
66
10
20
Predator
1
1
1
Shredder Predator
1
1
1
90
13
32
Plecoptera
8
4
5
Trichoptera
76
14
27
Odonata
FFG
Predator Gatherer, predator, scraper, shredder Filterer, gatherer, omnivore, predator, scraper, shredder
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Hydrobiologia Table 3 Number of studies by region and country included in the current study Region
Country
Number of studies
Reference
Oceania
Australia
13
Hargraves (1975), Williams (1984), Walsh (1994), Kefford et al. (2004a), (b), (2006a), (b), (2007), Allan (2006), Zalizniak et al. (2006), Hassell et al. (2006), Dunlop et al. (2007), Horrigan et al. (2007)
Europe
Austria
1
Wichard (1975)
North America
Canada
2
Johnsson & Clarke (1988), Sanzo & Hecnar (2006)
Europe
England
1
Sutcliffe (1961)
Europe
France
2
Piscart et al. (2011), Kefford et al. (2012a)
Asia
India
2
Gosh & Pal. (1969), Padhye & Ghate (1992)
Asia
Israel
1
North America
Mexico
1
Kefford et al. (2012a) Martı´nez-Jero´nimo & Martı´nez-Jero´nimo (2007)
Oceania
New Zealand
1
Piscart et al. (2011)
North America
1
Piscart et al. (2011)
North Europe
1
Piscart et al. (2011)
Europe
Russia
Africa
South Africa
South-Eastern Europe
1 10
1
North America
USA
Europe
Yugoslavia
22
1
Piscart et al. (2011) Forbes & Allanson (1970), Goetsch & Palmer (1997), Palmer & Sherman (2000), O’Brien (2003), Kefford et al. (2004a), (b), (2005), AQUIRE; EcoSun laboratories; IWR-UCEWQ Piscart et al. (2011) Trama (1954), Wallen et al. (1957), Dowden & Bennett (1965), Patrick et al., (1968), Thornton & Sauer (1972), Hamilton et al., (1975), Adelman et al. (1976), Hinton & Eversole (1979), Kostecki (1984), Birge et al. (1985), Kszos et al. (1990), Cowgill & Milazzo (1991), Newman & Aplin (1992), Lasier et al. (1997), Wisconsin State Laboratory of Hygiene (1998), Myers & Kohler (2000), Chadwick & Feminella (2001), Blasius & Merritt (2002), Bringolf et al. (2005), Gardner & Royer (2010), Echols et al. (2010), Kang & King (2012) Arambasic et al. (1995)
Order Trichoptera from arid and cold regions also showed low tolerance. Similar patterns were observed when plotting the cumulative frequency distribution (Fig. S1). Variation across FFGs was also consistent Table 4 Results of a linear model testing for variation in LC50 across Climate, Group, FFG, and their interactions across the entire dataset Variables
df
Mean Sq
F
P
Climate
3,876
9.02
7.336
0.001
Group
2,876
42.47
34.376
0.001
FFG
8,876
28.60
23.255
0.001
18,876 3,876
7.12 14.37
5.787 11.685
0.001 0.001
Climate:FFG Climate:Taxa
Values in bold show statistical significance
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regardless of whether FFGs were assigned at the Family (Figs. 2C, 3B; Table 5) or Genus level (F4,425 = 45.85; P \ 0.001; Fig. S2). Scrapers, gatherers and filterers consistently showed lower tolerance (i.e., lowest mean LC50) but higher variability in tolerance than omnivores, shredders, and predators (Fig. 3B; Fig. S2). This pattern was largely consistent across climatic regions, although predators showed high variability across regions, with cold-climate species being one of the most vulnerable. Similar results were found in the cumulative frequency distribution of all FFGs (Figs. S3, S4). Finally, the same pattern of variation in salinity tolerance was observed among EPT taxa (F2, 246 = 64.58; P \ 0.001, Fig. S5). Specifically, the most tolerant (i.e., highest mean LC50) Order was
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LC50 (ppt)
A
40 SW
30
Climate Arid
20
Cold
BW
Temperate Tropical
10 FW
0 Macroinvertebrate
Microinvertebrate
Vertebrate
B
40
LC50 (ppt)
Group 30
SW
Climate Arid
20
Cold
BW
Temperate Tropical
10 FW
er re Sh
Pr
Sc
ed
ra
dd
pe
r
or at
te si Pa ra
H
er
bi
he at G
O m ni vo re
vo re
r re Fi
lte
ivo ct Ba
re
r
re
0
FFG
Fig. 1 Variation in salinity tolerance across groups (A), and FFGs (B) in the entire dataset across climate regions (Means ? SE). LC50 values represent estimates of salinity tolerance across the entire dataset obtained from experimental studies reported in the literature. The dotted lines show three levels of
A
80
CV
60 40 20 0 Macroinvertebrate
Microinvertebrate
Vertebrate
Taxa
B
80
CV
60 40 20 0 Coleoptera
Diptera Ephemeroptera Hemiptera
Odonata
Plecoptera
Trichoptera
Order
C
80 60
CV
Fig. 2 Coefficients of variation (CV) in salinity tolerance in groups (A), Orders (B), and FFGs (C) of aquatic insects, pooled across climatic regions. Variation in FFGs is shown at the level of Family only
salinity: freshwater (FW; \ 0.5 ppt), brackish water (BW; 0.5–30 ppt), and saline water (SW; 30–50 ppt). Note that taxa with a single mean estimate (e.g., Bacterivore) have been included in the graph for illustration purpose only, but they have been excluded from the statistical analyses
40 20 0 Filterer
Gatherer
Omnivore
Predator
Scraper
Shredder
FFG
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Hydrobiologia
LC50 (ppt)
A
40 SW
30
Climate Arid
20
Cold BW
Temperate Tropical
10 FW
pt er a Tr ic ho
te ra Pl e
do O
H em
em
co p
na
ta
te ra ip
er op
te ra Ep h
C ol
D ip
eo
pt er a
te ra
0
Order
B
40 SW
30
LC50 (ppt)
Fig. 3 Variation in salinity tolerance across groups, Orders (A), and FFGs (B) of aquatic insects across climate regions (Means ? SE). LC50 values represent estimates of salinity tolerance across aquatic insects obtained from experimental studies reported in the literature. The dotted lines show three levels of salinity: freshwater (FW; \ 0.5 ppt), brackish water (BW; 0.5–30 ppt), and saline water (SW; 30–50ppt). Variation in FFGs is shown at the level of Family only. Taxa with single mean estimates (e.g., Plecoptera) have been included in the graph for illustration purpose only, but they have been excluded from the statistical analyses
Climate Arid
20
Cold BW
Temperate Tropical
10 FW
er Sh
re
dd
pe ra Sc
Pr
r
or ed
at
ni vo r m O
G
Fi
at
lte
he
re
r
re
r
e
0
FFG
Table 5 Results of linear model testing for variation in LC50 values across Climate, Order, FFG, and their interactions across aquatic insects Variables
df
Mean Sq
F
P
Climate
3,493
12.37
13.945
0.001
Order
8,493
41.75
47.065
0.001
FFG
5,493
6.44
7.258
0.001
Climate:FFG Climate:Order
11,493 10,493
0.31 0.58
0.345 0.649
0.974 0.771
Order:FFG
11,493
2.35
2.653
0.001
2,493
1.16
1.303
0.272
Climate:Order:FFG
Values in bold show statistical significance
Trichoptera, whereas the most sensitive (i.e., lowest mean LC50) Order was Ephemeroptera. Variation across FFGs at both Family (F5,243 = 23.78; P \ 0.001; Fig S6) and Genus level (F4,201 = 19.44; P \ 0.001) for EPT taxa were also consistent with those observed across all groups of aquatic insects, i.e., with gatherers and scrapers being the most sensitive.
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Discussion Salinization, either as a result of natural or anthropogenic processes, is a growing concern in freshwater ecosystems around the world. To date, most studies have focused on species-level responses, and less attention has been paid to potential effects on trophic diversity, community structure, and ecosystem processes. We set out to explore this possibility by analyzing how LC50 (an estimate of salinity tolerance) varies across climate zones, taxa, and aquatic insect functional feeding groups. Below, we discuss some of the main implications of our findings. Salinity tolerance across climate zones Overall, we observed large variation in salinity tolerance across climate regions, but the direction and magnitude of this variation differed across groups, taxa, and FFGs. For example, tropical groups (i.e., macroinvertebrates; Fig. 1A), taxa (Coleoptera, Diptera and Hemiptera; Fig. 3A), and FFGs (i.e., filterers,
Hydrobiologia
gatherers; Fig. 1B) showed higher tolerance than similar organisms in their cold or temperate climate. Another interesting geographic pattern was the relative paucity of data from the Neotropics, and tropical Africa and Asia, which limits our ability to predict the possible effects of salinization in these regions. This is worrisome given that global sea levels are expected to rise by 1 m by the end of 21st century as a consequence of climate change (IPCC, 2007; Rahmstorf, 2007). This could lead to a potential increase of salinity in coastal areas of the Neotropics such as Northern and Southern Gulfs of Mexico, the Central American Isthmus, and the Caribbean islands (IPCC, 2000; Courchamp et al., 2014). Increased salinity in these regions could also result from secondary salinization by anthropogenic disturbances, such as expansion of the Panama Canal and the proposed construction of a sea-level canal through Nicaragua (Meyer & Huete-Pe´rez, 2013). It is therefore urgent to expand our understanding about whether and how neotropical freshwater biodiversity will be able to cope with these changes, and the possible ecosystem-level consequences. Salinity tolerance across fish and microinvertebrates We found large variability in salinity tolerance across taxa. Specifically, freshwater vertebrates, which in our database were represented mostly by freshwater fish, showed higher tolerance than micro- and macroinvertebrates. The same pattern has been reported previously (James et al., 2003), and is likely related to fishes’ ability to perform active ion exchange (Bacher & Garnham, 1992; James et al., 2003). Furthermore, high salinity tolerance in freshwater fish, particularly in secondary and euryhaline species that can occur in both fresh and brackish/marine water, is likely a conserved character from marine ancestors (Hart et al., 1991). These species often inhabit saline environments, either permanently (e.g., Atherinids, Gobiids; Hart et al., 1991) or transiently (e.g., Milkfish; Lin et al., 2003), and therefore are expected to tolerate increased salinity. Although vertebrates showed higher median tolerances, it is important to note that a considerable number of species within these groups (mainly amphibians) also showed low tolerances (Sanzo & Hecnar, 2006). In contrast, freshwater microinvertebrates, which showed lower tolerance,
are less associated with marine environments, and lack a more recent marine ancestor (Sutcliffe, 1974). In addition, microinvertebrates use a passive mechanism (osmosis) to regulate their internal ion concentration (Sutcliffe, 1974; Hart et al., 1991), and therefore are highly sensitive to relatively small quantities of salt, as in the case of Hydra spp. (Sutcliffe, 1974). However, some members of this group (e.g., Rotifera and Copepoda) do show higher salinity tolerance (Halse et al., 1998; Timms, 1998; Williams et al., 1998). Salinity tolerance across aquatic insect orders Our database was dominated by macroinvertebrates; and in particular by aquatic insects. Within this group, we found considerable variation in LC50. Interestingly, tolerance varied across different taxonomic units, with different species within a given taxon (e.g., Order, Family, Genera) often showing substantially different tolerances. For example, we found that the Order Ephemeroptera had the lowest tolerance overall, but that particular species within this Order could tolerate brackish water (e.g., Hexagenia limbata and Tasmanocoenis sp.; supplementary material). Indeed, Tasmanocoenis spp. has previously been reported as the most salt tolerant mayfly species (Zinchenko & Golovatyuk, 2013). The Order Trichoptera, which exhibited higher tolerance than Ephemeroptera, included a number of case-building species (e.g., Triplectides sp., Notalina sp.). While cases are typically used for protection against predators, to avoid physical damage, and to assist in prey capture (Danks, 2002; Gooderham & Tsyrlin, 2002), they have also been suggested to increase tolerance to salinity and other pollutants (Winterbourn & Anderson, 1980; Zamora-Mun˜oz & Svensson, 1996). Hemiptera also showed high salinity tolerance. This pattern is not surprising, given that some Families of Hemiptera (Corixidae, Notonectidae, Veliidae, Gerridae) are often found in saline waters (Hart et al., 1991; Cheng, 2005). The Orders Diptera, Coleoptera and Odonata showed the highest tolerance values overall. This is not surprising, given that these groups are commonly found in saline environments (Hart et al., 1991; Cheng, 2005). In particular, some Families of Diptera such as Simuliidae, Ceratopogonidae, and Chironomidae have been reported in high salinity environments (Rutherford & Kefford, 2005; Zinchenko & Golovatyuk,
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2013). Their high tolerance is thought to be due to their life history strategies (i.e., short life cycle, high larval mobility) and a suite of physiological adaptations (Krivosheina, 2004). For example, the mosquito Aedes argenteus is capable of enlarging its gills and altering the epithelium of the mid-gut to avoid swelling in salt solutions (Wigglesworth, 1933). In the Order Coleoptera, the Genus Ochthebius contains the highest number of halophilous species with salinity tolerance of up to100 g/l (156 mS/cm); Zinchenko & Golovatyuk (2013), which is likely related to adaptation and evolution on dry land for millions of years (Gooderham & Tsyrlin, 2002). Finally, the Order Odonata also contains several species (e.g., Lestes dryas, Ischnura heterosticta) capable of living and reproducing in brackish water (Kefford et al., 2006c; Hassall & Thompson, 2008). A similar pattern was observed when we focused our analysis on common EPT taxa. Broadly, the global patterns of salinity tolerance across Orders reported here are not fully consistent with previous studies conducted at regional scale in Eastern Australia, South Africa, France, and Israel (Kefford et al., 2012a). Specifically, while Kefford et al., (2012a) reported Coleoptera as the most tolerant group, we found that both Coleoptera and Odonata tended to be the most tolerant at global scale. Similarly, we found that Diptera was more sensitive than previously reported by Kefford et al. (2012a); (Fig.S1). This suggests that global patterns of salinity tolerance in freshwater organisms are rather complex and that additional studies across a broader range of species are necessary. This is particularly relevant for some taxonomic groups such as Lepidoptera and Megaloptera, for which data were limited. Salinity tolerance across functional feeding groups There was substantial variability in salinity tolerance across aquatic insect functional feedings groups. Scrapers, gatherers, and filterers were generally the least tolerant, whereas omnivores, predators, and shredders were the most tolerant. Interestingly, shredders from cold climates also showed some of the lowest levels of tolerance. This differential vulnerability to salinity is important because the diversity of FFGs is crucial to maintain ecosystem functions such as removal of organic matter (Scrapers; Simpson et al., 1998), detritus (Gatherers; Simpson et al., 1998) and fine particles (Filterers; Jeppesen et al., 2007), and
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suggests that in the absence of replacement by functionally equivalent taxa, an increase in salinity could alter productivity, nutrient recycling and energy flow in freshwater ecosystems (Simpson et al., 1998; Jeppesen et al., 2007). Although omnivores, shredders, and predators showed higher median tolerances, it is important to note that a considerable number of species within these groups also showed low tolerances. This indicates that a portion of these FFGs could also be affected by salinization, which in turn could affect additional ecosystems processes. Declines or extirpations of any FFG could indirectly affect higher/lower trophic levels through cascading effects, leading to compensatory increases in the abundance of more tolerant species. For example, it has been shown that an increase in salinity of 1250 mg/l led to a 77% reduction in the abundance of more sensitive cladocerans, but a 90–400% increase in the abundance of more tolerant chironomids (Bailey & James, 2000). Thus, similar to other environmental stressors, salinization could alter community structure and have functional consequences for freshwater ecosystems (Fig. 4). Changes in community structure include alterations to food-web parameters such as the configuration, number, and strength of links, species interactions, and even trophic positions of organisms (Fig. 4C; Wurtsbaugh, 1992; Simpson et al., 1998), which can affect the overall productivity of freshwater ecosystems (Fig. 4D). It is important to mention several caveats that could limit the generalizations we discuss here, including variability in methodologies such as experimental setting, samples size or the taxonomic resolution of different studies. For example, the choice of species tested and the experimental methods used could bias the patterns of tolerance we observed within taxa or FFGs. Specifically, the use of LC50 as surrogate for salinity tolerance could underestimate true salinity tolerance in cases where organisms exhibit avoidance tactics in the wild (e.g., microhabitat selection, dispersal to refugia, and/or the production of dormant phases) not apparent from experimental studies in the laboratory. Conversely, salinity tolerance could be overestimated when LC50 values are estimated for adult stages only, given that early stages (eggs, juveniles) might be more sensitive to salinity (James et al., 2003; Kefford et al., 2004a, 2006b). Despite these limitations, LC50 is the most standardized and widely available metric to infer salinity tolerance in
Hydrobiologia
C
A
B
D
Fig. 4 A graphical model of the effects of salinization on the structure and functioning of freshwater ecosystems. A The structure of a hypothetical food web at equilibrium in the absence of disturbance. B The expected association between functional diversity and ecosystems function at equilibrium (e.g., Hillebrand & Matthiessen, 2009). C Possible changes in the structure of a hypothetical food web following disturbance (here salinization). These changes include the extirpation of
species or functional groups (empty pentagon), weakening of trophic links between species (dashed lines), strengthening or establishment of new of trophic links (thicker lines), and the decrease (smaller circles) or increase (enlarged circles) of population abundance and/or biomass. D shows expected functional consequences at ecosystem level, depicted as a weakening of the association between functional diversity and ecosystem function (e.g., Biswas & Mallik, 2010)
freshwater organisms. With regard to the ecosystem consequences of salinity, the assignment of a single FFG across taxa may not always hold, particularly at higher taxonomic levels such as Order and Family. Trophic niches can vary with size classes within a species, as well as between closely related species (Ramı´rez & Gutie´rrez-Fonseca, 2014). However, we obtained consistent results between our lowest and highest taxonomic levels, suggesting that our analysis was relatively robust to the assignment of FFGs.
than historically less-saline regions such as France (Kefford et al., 2012a). In addition, high salinity tolerance in Odonata species is likely related to their tropical evolutionary history, and adaptation to warm and dry environments (Gooderham & Tsyrlin, 2002; Hassall & Thompson, 2008). These large-scale geographical patterns are consistent with the hypothesis that adaptation to high salinity environments in the past could play an important role in determining contemporary tolerance (Williams et al., 1991; Nielsen & Hillman, 2000; Kay et al., 2001). Interestingly, other organisms from historically less-saline environments also showed high tolerance. This includes organisms from a broad range of taxonomic and functional scales (e.g., vertebrates, omnivores, predators, and shredders) that showed the highest tolerance in cold and temperate climates. This pattern is likely influenced by phylogenetic effects on physiology, a possibility suggested by the significant interaction between climates, FFGs, and Taxa (Table 4). Furthermore, organisms with recent marine ancestors also showed high salinity tolerance. For instance, some Families of Hemiptera (Corixidae, Notonectidae, Veliidae, Gerridae) have successfully colonized islands and brackish waters (Hart et al.,
The roles of historical exposure and taxonomic affinity A variety of factors could influence global patterns of salinity tolerance across spatial and taxonomic scales. Regional variation in salinity tolerance may stem partially from different degrees of historical exposure to saline environments in different regions. For example, aquatic organisms from Australia and South Africa, which were the largest semi-arid and tropical areas included in our review, are more commonly exposed to saline environments (Williams et al., 1991; Kefford et al., 2005, 2012a), and therefore are expected to have evolved higher salinity tolerance
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1991; Cheng, 2005), probably facilitated by having a euryhaline ancestor such as in the case of Gerridae (Andersen, 1999; Damgaard, 2000). Although more data are needed to disentangle the local vs. global effects of salinization on freshwater biodiversity, our analysis suggests that both historical exposure and phylogenetic history are important drivers of contemporary variation in salinity tolerance. Future directions Our review revealed some important knowledge gaps that need to be addressed in order to improve our understanding of the impacts of salinization on freshwater biodiversity. First, there is a paucity of studies on salinity tolerance from tropical environments (Africa, Asia, and America). In the Americas, we only found one study from Mexico, and none from the Central American Isthmus. This is important because the Central American Isthmus is expected to be affected by both global sea level rise due to climate change (IPCC, 2007) and secondary salinization due to megaprojects such as the expansion of the Panama Canal and the future construction of the Nicaraguan Canal (Meyer & Huete-Pe´rez, 2013; De Leo´n & Lopez, 2016). For other regions of the world, studies were highly concentrated in countries such as USA and Australia, with two studies from tropical Australia. Second, most published studies were focused on the effects of salinity at the level of individual organisms, and there was an overall lack of field studies/experiments looking at community-level responses to salinization. Furthermore, we know little about intraspecific variation in traits (morphological, behavioral, or physiological) associated with salinity tolerance. Understanding this variation will help disentangle the plastic vs. genetic component of salinity tolerance, and the potential evolutionary response of freshwater organisms to increased salinization. Third, current experimental studies rarely reported salinity levels experienced by freshwater organisms in natural environments, such as the duration, periodicity, and seasonality of salinization, which could affect tolerance values, given that acute exposure could be more disruptive than gradual exposure to salinity (James et al., 2003). Fourth, the lack of data on sublethal effects is also an important limitation, given that salinity concentrations lower than LC50 could impair organismal functions (e.g.,
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behavior, foraging, reproduction) that might be disruptive to individual performance and ecosystem processes (Paradise, 2009). Finally, in the face of global change, the effects of salinization on freshwater biodiversity are likely to be amplified by interactions with other stressors such as changes in temperature, dissolved oxygen, acidification, precipitation, and hydroperiod (Stoks et al., 2013). For instance, the effects of contaminants (e.g., zinc) are more pervasive at higher temperatures for some organisms such as damselfly larvae (Stoks et al., 2013). Future studies are therefore needed to quantify the synergistic effects of salinity with other environmental factors. Together, these data will be useful to disentangle the role of in situ (e.g., acclimatization or osmoregulation) and ex situ (e.g., dispersal, recolonization) tolerances in promoting resilience in freshwater organisms.
Conclusion Overall, our review suggests that salinity tolerance in freshwater organisms is highly variable across taxa, geographical regions, and functional feeding groups. This suggests that increasing salinization—either due to climate change or secondary salinization—will affect the structure and functioning of freshwater ecosystems, as well as the services that they provide to human society. However, our current understanding of these effects is limited, which constrains our ability to predict the response and the potential for adaptation of freshwater biodiversity in the face of human disturbances. Acknowledgements Financial support was provided by the Secretarı´a Nacional de Ciencia, Tecnologı´a e Innovacio´n (SENACYT, Panama´) in the form of a doctoral fellowship to AMC and a research grant (No. ITE12-002) to LFD. CKG was supported by a National Science Foundation grant (IOS1457383). Additional support was provided by Instituto para la Formacio´n y Aprovechamiento de los Recursos Humanos in the form of a doctoral fellowship to AMC, and by Sistema Nacional de Investigacio´n (SNI, Panama´) to DMTS and LFD. DMTS was also supported by a postdoctoral fellowships from the Fonds Recherche Nature et Technologies Quebec (FQRNT). Finally, the authors thank two anonymous reviewers and editor Eric R. Larson for their comments and suggestions that helped improve an earlier version of the manuscript.
Hydrobiologia
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