Next Article in Journal
Correction: Slišković et al. A Systematic Analysis of the Mediterranean Sea (IHO Sea Area) in the WRiMS Database. Diversity 2024, 16, 358
Previous Article in Journal
Variation in the Biomass of Phragmites australis Across Community Types in the Aquatic Habitats of the Middle Volga Valley
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Dragonfly Functional Diversity in Dinaric Karst Tufa-Depositing Lotic Habitats in a Biodiversity Hotspot

by
Marina Vilenica
1,*,
Vlatka Mičetić Stanković
2 and
Mladen Kučinić
3
1
Faculty of Teacher Education, University of Zagreb, Trg Matice Hrvatske 12, 44250 Petrinja, Croatia
2
Croatian Natural History Museum, Demetrova 1, 10000 Zagreb, Croatia
3
Department of Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Diversity 2024, 16(10), 645; https://doi.org/10.3390/d16100645
Submission received: 30 August 2024 / Revised: 4 October 2024 / Accepted: 13 October 2024 / Published: 17 October 2024
(This article belongs to the Section Freshwater Biodiversity)

Abstract

:
Functional diversity is a key component of biodiversity that reflects various dimensions of ecosystem functioning and the roles organisms play within communities and ecosystems. It is widely used to understand how ecological processes influence biotic assemblages. With an aim to increase our knowledge about dragonfly ecological requirements in tufa-depositing karst habitats, we assessed functional diversity of their assemblages, various life history traits (e.g., stream zonation preference, substrate preference, reproduction type), and relationship between functional diversity and physico-chemical water properties in three types of karst lotic habitats (springs, streams, and tufa barriers) in a biodiversity hotspot in the western Balkan Peninsula. Dragonfly functional diversity was mainly characterized by traits typical for lotic rheophile species with medium dispersal capacity. Among the investigated habitats, tufa barriers, characterized by higher (micro)habitat heterogeneity, higher water velocity, as well as lower conductivity and concentration of nitrates, can be considered as dragonfly functional diversity hotspots. Functional diversity and most of the life history traits were comparable among different substrate types in the studied habitats, indicating higher importance of habitat type in shaping dragonfly functional diversity patterns in karst lotic habitats. Our results should be considered in the management and conservation activities of vulnerable karst freshwater ecosystems and their dragonfly assemblages.

1. Introduction

During the past several decades, numerous ecological studies have improved our knowledge of biodiversity and its temporal and spatial changes as well as our understanding of various ecological phenomena [1,2,3] by investigating interactions between organisms and their environment through analysis of their functional (or life history) traits (i.e., traits highly influencing the performance of organisms [4]) and functional diversity [2,5]. Various morphological, physiological, phenological, or behavioral species characteristics (i.e., functional (and behavioral) or life history traits) [6,7] enable their survival in a certain environment [7,8]. Based on those characteristics, aquatic organisms can be placed into functional groups based on, for instance, their trophic position (e.g., grazers, shredders, collectors, predators), habitat preference (e.g., lotic, lentic, eurytopic), current preference (e.g., limnophile, rheophile), and substrate preference (e.g., phytal, lithal, fine sediments) [9]. Functional diversity (diversity of functional groups (traits) of species within an assemblage) is therefore a biodiversity component that reflects various aspects of ecosystem functioning, such as ecosystem productivity, dynamics, nutrient balance [1,10], as well as the role of organisms within the communities and ecosystems [6]. It can also be used to understand the influence of ecological processes on biotic assemblages [11].
The Dinaric Mountains, located along the western Balkan Peninsula (from northeastern Italy to Albania) are the largest continuous karst landscape in Europe, with their length of over 600 km [12]. Karst habitats are formed through the dissolution of carbonate rocks and are characterized by highly diverse morphological, hydrological, and geological characteristics [13]. One of the unique features of freshwater habitats in karst regions is tufa, a secondary deposition of calcium carbonate resulting from the interaction between the geological bed rock, physico-chemical water properties, and inhabiting biota, especially the bryophytes [14]. Hence, due to high habitat heterogeneity, Dinaric karst freshwater habitats are characterized by high biodiversity, including numerous endemic species, which is why they have long been recognized as biodiversity hotspots, e.g., [15,16,17,18].
Dragonflies (Odonata) are merolimnic insects commonly used as bioindicators of the condition and integrity of freshwater ecosystems, e.g., [19], due to many of their life history traits, e.g., [20,21]. For instance, good taxonomic knowledge allows their rather easy identification at the species level [22]. Different species have different ecological requirements, such as those for habitat type, substrate composition, and riparian and aquatic vegetation structure [23,24]. Also, due to their fast life cycles, behavioral traits, and sensitivity to habitat alteration, many dragonfly species quickly respond to changes in their habitats, including both aquatic and surrounding terrestrial ones [7,25]. As predators, they are highly important in both aquatic and terrestrial food webs, having one of the most important roles in controlling the population densities of other insects, such as mosquitoes [22]. Moreover, they play a crucial role in transferring biomass and energy from aquatic ecosystems to terrestrial food webs [26].
In ecological research, the understanding of the processes shaping biotic assemblages is of fundamental importance [27], which can be achieved through analysis of assemblages’ functional traits. In a previous study [23], only the taxonomic aspect was studied (i.e., dragonfly taxonomic assemblage metrics were analyzed) in the Dinaric karst tufa-depositing lotic habitats in the western Balkan Peninsula. Hence, the main goals of this study were to increase our knowledge about dragonfly ecological requirements in such unique habitats by assessing differences in their functional diversity and life history traits (e.g., body shape, dispersal capacity, stream zonation preference, reproduction) among the three habitat and four main substrate types in the Dinaric karst tufa-depositing lotic habitats in the western Balkan Peninsula. Additionally, we wanted to determine the main physico-chemical water parameters shaping functional diversity of dragonfly assemblages in the selected habitats.

2. Materials and Methods

2.1. Study Area

The study was conducted in a biodiversity hotspot [28,29], specifically in the Plitvice Lakes National Park (NP), located in Croatia’s Dinaric karst region (Supplementary Table S1; for a map of the study area, see Vilenica et al. [30]). The Plitvice hydrosystem comprises 16 lakes connected by tufa barriers, along with several small rivers and streams that act as the primary surface water sources for the lakes [31].
The climate in the area of the Plitvice Lakes NP is humid with warm summers (CfB, Koppen climate classification) [32]. The mean annual temperature is 8 °C, while the mean annual precipitation is 1500 mm [33]. During the study period (2007), the mean annual air temperature was 11.4 °C and the mean annual rainfall was 1664.1 mm (see also in Vilenica [23]).
The study sites encompassed three types of tufa-depositing lotic karst habitats: springs, streams (also including small mountainous rivers) and tufa barriers (for details see, e.g., Vilenica [23], Vilenica et al. [30]) (Figure 1).

2.2. Environmental Variables

Every month over a one-year period, at every study site, we measured the following physico-chemical water properties above each microhabitat that was sampled: oxygen concentration, oxygen saturation, water temperature (using the oximeter WTW Oxi 330/SET), pH (using the pH meter WTW pH 330), conductivity (using the conductivity meter WTW LF 330), alkalinity (by titration with 0.1 M HCl), water velocity (using the P-670-M velocimeter), and nutrients (ammonium by HRN ISO 70-3:1998 method and nitrates by HRN ISO 7890-3:2001 method) (see more in Vilenica [23]).

2.3. Dragonfly Sampling

Macrozoobenthos sampling (including dragonfly nymphs) was conducted every month between February 2007 and February 2008 at ten study sites belonging to the three above-mentioned Dinaric karst tufa-depositing lotic habitats (Figure 1, Supplementary Table S1) in the Plitvice Lakes NP, Croatia.
At each site and each sampling event, samples were taken in all dominant substrate types (those with a share of at least 5% coverage (bryophytes (mosses and liverworts), cobbles, sand, and silt with leaf litter), defined according to Wentworth [34]).
Samples were collected following the standard macrozoobenthos sampling methodology as described in Vilenica [23], i.e., using Surber samplers (mesh size: 0.5 mm; surface area: 14 × 14 cm on bryophytes and 25 × 25 cm on all other microhabitats). Microhabitats at the lower reaches of Crna rijeka were due to the greater water depth, sampled using a D-frame hand net (mesh size: 0.5 mm; surface area: 25 × 25 cm). At each study site, 36 macroinvertebrate samples were collected over a one-year period (i.e., 360 samples in total). Dragonfly abundance was calculated as number of individuals per m2. Species were identified using relevant identification keys [35,36,37]. The voucher specimens are at the Department of Biology, Faculty of Science, Zagreb, Croatia.

2.4. Data Analysis

In a previous study [23], a total of eight dragonfly species were recorded (Table 1, Supplementary Table S2). Prior to the analyses, all quantitative data were tested for normality using the Shapiro–Wilk test in Statistica, version 10.0 [38].
The functional diversity of dragonfly assemblages was quantified using a total of 36 functional traits from seven groups of functional (life history) traits (Table 2) (taken from Schmidt-Kloiber and Hering [9]; Dijkstra et al. [39]). The assignment of a species to a particular functional trait category within each functional trait group used is based on a single category assignment system (as in the case of body type and dispersal capacity trait groups) or a 10-point assignment system (as in the case of the rest of the functional traits used) (see in Dijkstra et al. [38]).
The Rao quadratic diversity (RaoQ) coefficient is a measure of functional diversity that considers both the differences between species (in terms of their functional traits) and their relative abundances, and it was used to measure the functional diversity of dragonflies in the studied habitats. This coefficient reflects patterns of trait convergence or divergence relative to what would be expected by chance. To assess shifts in mean trait values within dragonfly assemblages, community weighted mean (CWM) values were calculated (combining species-specific functional traits with the relative abundance of each species within the assemblage) for each functional trait, with an aim to capture the effects of environmental selection on specific functional trait categories [40]. Both RaoQ and CWM values were calculated using the CANOCO software package, version 5.15 [41].
The differences in physico-chemical water parameters among the three habitat types (springs, streams, and tufa barriers) as well as functional metrics among the three habitat types and among the substrate types (cobbles, bryophytes, sand, silt with leaf litter) were tested using the Kruskal–Wallis H test, followed by a multiple comparisons post hoc test to determine which groups differ from each other. Those analyses were performed in Statistica, version 10.0 [38].
To assess the impact of physico-chemical water parameters on the spatial distribution of CWM values for functional traits in dragonfly assemblages, a redundancy analysis (RDA) was conducted. Before performing the RDA, dragonfly abundances were centered and standardized based on average functional traits. The analysis included CWM data for eight dragonfly species and six physico-chemical water parameters that showed significant differences among habitat types. The statistical significance of the relationship between dragonfly functional traits and physico-chemical water parameters was assessed using a Monte Carlo permutation test with 499 permutations. Both the RDA and Monte Carlo tests were conducted using the CANOCO package, version 5.15 [41].

3. Results

3.1. Environmental Variables

Concentration of nitrates (Kruskal–Wallis H test, N = 118, DF = 2; H = 19.66, p < 0.001), pH (H = 34.06, p < 0.001), oxygen saturation (H = 13.19, p < 0.01), water velocity (H = 10.97, p < 0.01), conductivity (H = 40.43, p < 0.001), and alkalinity (H = 32.66, p < 0.001) significantly differed among the three habitat types (Figure 2).
The multiple comparisons post hoc test showed that springs had lower oxygen saturation (p < 0.01) and lower pH (p < 0.001) compared to streams and tufa barriers. Water velocity was higher in tufa barriers compared to springs (p < 0.01), and conductivity, alkalinity, and concentration of nitrates were lower in tufa barriers compared to springs and streams (p < 0.001) (Figure 2).
Water temperature (H = 5.12, p > 0.05), oxygen (H = 4.83, p > 0.05), and ammonia concentrations (H = 1.78, p > 0.05) were comparable among the three habitat types (Figure 3).

3.2. Dragonfly Life History Traits and Functional Diversity at Different Karst Lotic Habitats

Dragonfly functional diversity (RaoQ index) was significantly higher at tufa barriers (Kruskal–Wallis H test, N = 30, DF = 2; H =16.46, p < 0.001) compared to springs (p < 0.001) and streams (p < 0.05) (Supplementary Table S3, Figure 4).
Significant differences among the habitat types were recorded for the following life history traits: the share of Zygoptera (Kruskal–Wallis H test, N = 30, DF = 2; H = 14.00, p < 0.01), Anisoptera body types (H = 9.86, p < 0.01), species with medium dispersal capacity (H = 12.03, p < 0.01), species preferring metarhithral (H = 17.94, p < 0.001), hyporhithral (H = 14.88, p < 0.001), and epipotamal (H = 10.69, p < 0.01) stream sections, littoral-preferring species (H = 12.83, p < 0.01), eupotamon (H = 11.12, p < 0.01) and parapotamon (H = 13.80, p < 0.01) species, species preferring microhabitats with psammal (H = 10.32, p < 0.01), akal (H = 10.97, p < 0.01), lithal (H = 12.84, p < 0.01), phytal (H = 14.00, p < 0.01), and particulate organic matter (H = 11.42, p < 0.01) substrates, rheophile species (H = 10.72, p < 0.01), species laying the eggs into the substrate (H = 10.82, p < 0.01), not attached to or in the substrate (H = 10.97, p < 0.01), into open water (H = 10.97, p < 0.01), and inside plant tissue (H = 14.00, p < 0.01) (Supplementary Table S3, Figure 5).
The multiple comparisons post hoc test showed that tufa barriers had a higher share of Zygoptera compared to springs (p < 0.05) and streams (p < 0.05), and tufa barriers had a higher share of Anisoptera compared to springs (p < 0.05). A higher share of species preferring metarhithral and hyporhithral stream sections were recorded at tufa barriers compared to the other two habitats (p < 0.01), and a higher share of epipotamal and littoral species were recorded at tufa barriers compared to springs (p < 0.001). Higher shares of eupotamon (p < 0.01) and parapotamon (p < 0.01) species were recorded at tufa barriers compared to springs. Higher shares of species preferring microhabitats with psammal, akal, lithal, and particulate organic matter substrates (p < 0.01) were recorded in tufa barriers compared to springs, while tufa barriers also had a higher share of species preferring phytal compared to springs and streams (p < 0.05). A higher share of rheophile species was recorded at tufa barriers compared to springs (p < 0.01), as well as of species laying their eggs into the substrate (p < 0.01), not attached to or in the substrate (p < 0.05), and into open water (p < 0.01), while tufa barriers also had a higher share of species laying their eggs inside plant tissue compared to springs and streams (p < 0.05) (Figure 5).
Other dragonfly life history traits were comparable among the three habitat types (p > 0.05), or significance was marginal (i.e., a multiple comparisons post hoc test did not determine differences between the habitat pairs) (Supplementary Table S3, Figure 5).

3.3. Dragonfly Functional Traits and Environmental Variables

The RDA analysis (Figure 6) showed significant differences in the dragonfly functional traits among the three habitat types, with explanatory variables accounting for 54.80% of the variance (F ratio = 4.85, DF = 6, p = 0.002). The first two ordination axes (eigenvalues of 0.49 and 0.04) explained 53.26% of the variation. The first axis showed the strongest correlation with conductivity (R = −0.76), while the second axis was primarily correlated with nitrate concentration in water (R = 0.18) and water velocity (R = −0.15).

3.4. Dragonfly Life History Traits and Functional Diversity at Different Substrate Types

Dragonfly functional diversity (RaoQ index) (Figure 7) and most life history traits (Figure 8) were comparable among the four main substrate types in the studied lotic habitats, or differences were marginally significant (Kruskal–Wallis H test, N = 30, DF = 2; Supplementary Table S4). In terms of life history traits, only the share of species preferring microhabitats with particulate organic matter substrates was significantly higher (Kruskal–Wallis H test, N = 30, DF = 3; H = 11.22, p < 0.05) at silt with leaf litter compared to bryophytes substrates (p < 0.05) (Supplementary Table S4, Figure 8).

4. Discussion

The Plitvice barrage-lake hydrosystem represents a rather harsh environment due to rather low water temperature and productivity [42,43], but also high conductivity and alkalinity [12,44]. Although this system is considered to be a biodiversity hotspot (e.g., [16]), for some groups of aquatic organisms, such as dragonflies, it could be challenging to cope with such conditions, in combination with the presence of alien fish species [45], which are generally known to negatively influence dragonfly abundance [46]. Most probably for these reasons, a rather low number of dragonfly species (i.e., eight) occurs in the system’s lotic habitats [23]. Moreover, only a low share of European dragonflies is specialized to inhabit forest streams with cold-water and/or high-water current [39,47], especially within the studied geographical range. However, most of the recorded species were previously reported from karst habitats [48,49]. Our results showed that despite the low dragonfly taxonomic diversity, their functional diversity is rather high in Dinaric karst tufa-depositing habitats in the western Balkan peninsula [38]. Among the three studied habitat types, namely springs, streams, and tufa barriers, the diversity of dragonfly functional traits was the highest at the latter, similar to as found for taxonomic assemblage metrics [23]. In our study area, functional diversity was predominantly characterized by traits characteristic for specialists, lotic rheophile species, in accordance with habitat characteristics. Moreover, most of the recorded species were those with medium dispersal capacity, a trait typical for lotic species [50], as those can more easily disperse along their habitats compared to species that inhabit patchy lentic habitats, which then in turn have higher dispersal abilities [51].
Due to higher taxonomic diversity [23], tufa barriers consequently had a higher share of both the Anisoptera and Zygoptera body shape trait, streams were inhabited only by anisopterans Cordulegaster bidentata and Onychogomphus forcipatus and zygopteran Platycnemis pennipes, while no species were recorded at springs [23]. Tufa barriers had the highest share of rheophile lotic species preferring the upper reaches of lotic habitats (such as Cordulegaster bidentata, Orthetrum coerulescens, and Calopteryx virgo), but also some species that preferably occur in the lower reaches of running waters (Gomphus vulgatissimus, Onychogomphus forcipatus), and those typical for lentic habitats (Crocothemis erythraea, Coenagrion puella) were found there [23,39]. As explained in Vilenica [23], lentic species present at lotic tufa barriersnatural lake outlets, most probably have drifted from the upstream lakes [52]. Due to (micro)habitat heterogeneity, species with various substrate preferences were recorded at tufa barriers. Hence, a higher share of species occurring in akal (Onychogomphus forcipatus), psammal (e.g., Gomphus vulgatissimus, Onychogompus forcipatus, Cordulegaster bidentata), lithal (e.g., Onychogomphus forcipatus, Calopteryx virgo), phytal (e.g., Crocothemis erythraea, Platycnemis pennipes, Calopteryx virgo), and particulate organic matter (e.g., Cordulegaster bidentata, Orthetrum coerulescens) substrates was recorded there [39]. Moreover, a rather high diversity of available microhabitats resulted in tufa barriers being represented by higher ethodiversity [7], i.e., higher variability of behavioral traits related to reproduction type (oviposition), where we documented a higher share of species laying eggs into the substrate (e.g., Cordulegaster bidentata, Platycnemis pennipes), not attached to the substrate (e.g., Gomphus vulgatissimus, Onychogompus forcipatus), into open water (e.g., Orthetrum coerulescens, Crocothemis erythraea), and into plant material (Platycnemis pennipes, Calopteryx virgo, Coenagrion puella) [39]. Although studies focused on dragonfly functional diversity in the European karst lotic habitats are still rare, some showed similar results, where higher dragonfly functional diversity was related to higher habitat heterogeneity [24]. Moreover, studies conducted on other aquatic insects in the same study area, such as caddisflies and mayflies, showed that functional traits (functional feeding groups and stream zonation preference of species) changed along with the habitat types, characterized by differences in microhabitat composition and abiotic water parameters [53,54]. Therefore, our results confirm the importance of habitat and microhabitat heterogeneity not only for taxonomic [23] but also functional diversity of dragonfly assemblages [30,55]. In addition, tufa barriers have already been recognized as special habitats with high vulnerability and high complexity in terms of their hydrogeological, hydrological, and biological characteristics and defined as freshwater reefs where high biodiversity prevails, e.g., [56,57].
Higher dragonfly functional diversity was associated with lower conductivity and concentration of nitrates as well as higher water velocity, parameter values associated with tufa barriers. The slightly elevated nitrate concentrations and corresponding increase in conductivity could be attributed to the substantial rise in tourism pressure within the National Park area [58], which is why the water quality is recommended to be systematically monitored together with populations of freshwater communities. However, even though dragonflies are considered as good indicators of habitat and water quality, many studies have shown that their assemblages respond more strongly to habitat degradation (particularly to changes in hydro-morphology of the waterbody and in the structure of aquatic and riparian vegetation) than to water pollution [59,60,61]. A previous study determined water temperature amongst the most important physico-chemical water parameters influencing the occurrence of dragonfly species and their taxonomic diversity in lotic habitats of the Plitvice barrage-lakes system [23]. In line with these findings, tufa barriers, characterized by higher water temperature, diverse microhabitats, and abundant food resources, were identified as the most suitable habitats for the greatest number of dragonfly species [23,30,62]. In contrast, low water temperature in the studied karst springs was most probably one of the most important determinants of dragonfly absence from such habitats [23], similar to the findings of Cíbik et al. [63]. Therefore, instead of defining the most important physico-chemical water parameters shaping dragonfly functional diversity in the studied habitats, we suggest that the interplay of physico-chemical water parameters, microhabitat diversity, and most likely food availability and predator presence, had a synergistic impact, and resulted in tufa barriers being the most suitable habitats for the highest number of species, and consequently in the highest dragonfly functional diversity.
Functional diversity and most of the life history traits were comparable among different substrate types, even though the previous study of [23] showed that the recorded species mainly avoided microhabitats with bryophyte substrates and the highest water velocity, while higher species richness was associated with microhabitats with lithal and psammal and lower water velocities. Significant differences were only found in species preferring microhabitats with fine substrates (i.e., particulate organic matter) [39], such as Orthetrum coerulescens, being the most abundant at microhabitats with silt and leaf litter (see also Vilenica [23]).

5. Conclusions

Our study confirmed the high value of highly sensitive tufa barriers as local diversity hotspots. The presented results showed that functional diversity of dragonfly assemblages in Dinaric karst lotic habitats is influenced by the interplay of physico-chemical water properties, microhabitat composition, and most probably food availability and predator presence. Habitats with higher (micro)habitat heterogeneity (i.e., tufa barriers) supported higher functional diversity of dragonfly assemblages, thus acting as functional diversity hotspots within the studied karst lotic system and highlighting the valuable use of this approach in ecological research and the planning of conservation activities. Preservation of natural habitat structure, variability of microhabitats, and removal of alien fish species should be imperative to preserve vulnerable karst lotic systems and their dragonfly assemblages.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/d16100645/s1: Table S1: Geographic coordinates and altitude of the study sites belonging to three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia.; Table S2: Dragonfly species and their mean abundances (number of individuals per m2) recorded at ten study sites belonging to three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia. Legend: BRS = Bijela rijeka spring, CRS = Crna rijeka spring; BRMR = Bijela rijeka middle reaches, CRMR = Crna rijeka middle reaches, CRLR = Crna rijeka lower reaches, PL = Plitvica, KR = Korana; LB = Labudovac, KM = Kozjak-Milanovac, NOB = Novakovića Brod.; Table S3: Differences (Kruskal-Wallis H test with multiple comparisons post hoc test) in community weighted mean (CWM) values of drag-onfly functional traits among three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia. SP = springs, ST = streams, TB = tufa barriers. Significant results are in bold.; Table S4: Differences (Kruskal-Wallis H test with multiple comparisons post hoc test) in community weighted mean (CWM) values of dragonfly functional traits among three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia. B = bryophytes, SLL = silt with leaf litter. Significant results are in bold.

Author Contributions

Conceptualization, M.V., V.M.S. and M.K.; methodology, M.V., V.M.S. and M.K.; validation, V.M.S. and M.K.; formal analysis, M.V.; investigation, M.V., V.M.S. and M.K.; resources, M.K.; data curation, M.V., V.M.S. and M.K.; writing—original draft preparation, M.V.; writing—review and editing, M.V., V.M.S. and M.K.; visualization, M.V.; supervision, M.V., V.M.S. and M.K.; project administration, V.M.S. and M.K.; funding acquisition, M.K. All authors have read and agreed to the published version of the manuscript.

Funding

The study is a result of Projects No. 119-1193080-1206 (PL: Mladen Kučinić) and No. 119-1193080-3076 (PL: Mladen Kerovec) supported by the Croatian Ministry of Science, Education, and Sports.

Institutional Review Board Statement

The study was conducted based on permissions from the Ministry of Environmental and Nature Protection of the Republic of Croatia (RN: 532-08-02-1/7-06-3; 532-08-02-1/7-06-3).

Data Availability Statement

Data are available from the corresponding authors upon request.

Acknowledgments

Our colleagues from the Department of Biology, Faculty of Science, University of Zagreb are thanked for their help with collecting the samples and sorting the collected material. Three anonymous reviewers and an Academic Editor are thanked for their valuable comments and suggestions that markedly improved this paper.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Tilman, D.; Knops, J.; Wedin, D.; Reich, P.; Ritchie, M.; Siemann, E. The influence of functional diversity and composition on ecosystem processes. Science 1997, 277, 1300–1302. [Google Scholar] [CrossRef]
  2. Nock, C.A.; Vogt, R.J.; Beisner, B.E. Functional Traits. In eLS; John Wiley & Sons Ltd.: Chichester, UK, 2016; pp. 1–8. [Google Scholar] [CrossRef]
  3. Mammola, S.; Carmona, C.P.; Guillerme, T.; Cardoso, P. Concepts and applications in functional diversity. Funct. Ecol. 2021, 35, 1869–1885. [Google Scholar] [CrossRef]
  4. McGill, B.J.; Enquist, B.J.; Weiher, E.; Westoby, M. Rebuilding community ecology from functional traits. Trends Ecol. Evol. 2006, 21, 178–185. [Google Scholar] [CrossRef]
  5. Hooper, D.U.; Chapin, F.S.; Ewel, J.J.; Hector, A.; Inchausti, P.; Lavorel, S.; Lawton, J.H.; Lodge, D.M.; Loreau, M.; Naeem, S.; et al. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecol. Monogr. 2005, 75, 3–35. [Google Scholar] [CrossRef]
  6. Petchey, O.L.; Gaston, K.J. Functional diversity: Back to basics and looking forward. Ecol. Lett. 2006, 9, 741–758. [Google Scholar] [CrossRef]
  7. Cordero-Rivera, A. Behavioral diversity (ethodiversity): A neglected level in the study of biodiversity. Front. Ecol. Evol. 2017, 5. [Google Scholar] [CrossRef]
  8. Tapolczai, K.; Bouchez, A.; Stenger-Kovács, P.A.; Padisák, J.; Rimet, F. Trait-based ecological classifications for benthic algae: Review and perspectives. Hydrobiologia 2016, 776, 1–17. [Google Scholar] [CrossRef]
  9. Schmidt-Kloiber, A.; Hering, D. www.freshwaterecology.info—An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecol. Indic. 2015, 53, 271–282. [Google Scholar] [CrossRef]
  10. Tilman, D. Functional diversity. In Encyclopedia of Biodiversity; Levin, S.A., Ed.; Academic Press: San Diego, CA, USA, 2001; pp. 109–120. [Google Scholar]
  11. Villéger, S.; Mason, N.W.H.; Mouillot, D. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 2008, 89, 2290–2301. [Google Scholar] [CrossRef]
  12. Bonacci, O.; Pipan, T.; Culver, D.C. A framework for karst ecohydrology. Environ. Geol. 2009, 56, 891–900. [Google Scholar] [CrossRef]
  13. Bonacci, O.; Željković, I.; Galić, A. Karst rivers’ particularity: An example from Dinaric karst (Croatia/Bosnia and Herzegovina). Environ. Earth Sci. 2013, 70, 963–974. [Google Scholar] [CrossRef]
  14. Srdoč, D. Procesi taloženja kalcita u krškim vodama s posebnim osvrtom na Plitvička jezera. Krš Jugosl. 1985, 11, 4–6. [Google Scholar]
  15. Gottstein Matočec, S.; Bakran-Petricioli, T.; Bedek, J.; Bukovec, D.; Buzjak, S.; Franičević, M.; Jalžić, B.; Kerovec, M.; Kletečki, E.; Kralj, J.; et al. An overview of the cave and interstitial biota of Croatia. Nat. Croat. 2002, 11, 1–112. [Google Scholar]
  16. Ivković, M.; Plant, A. Aquatic insects in the Dinarides: Identifying hotspots of endemism and species richness shaped by geological and hydrological history using Empididae (Diptera). Insect Conserv. Divers. 2015, 8, 302–312. [Google Scholar] [CrossRef]
  17. Gredar, T.; Šarac, A.; Prša, P.; Fišer, Ž.; Kostanjšek, R.; Bizjak Mali, L. Morphology and differential counts of blood cells as important health indicators in the olm. Proteus anguinus. Amphibia-Reptilia, 2024; ahead of print. [Google Scholar] [CrossRef]
  18. Previšić, A.; Walton, C.; Kučinić, M.; Mitrikeski, P.T.; Kerovec, M. Pleistocene divergence of Dinaric Drusus endemics (Trichoptera, Limnephilidae) in multiple microrefugia within the Balkan Peninsula. Mol. Ecol. 2009, 18, 634–647. [Google Scholar] [CrossRef]
  19. Simaika, J.P.; Samways, M.J. An easy-to-use index of ecological integrity for prioritizing freshwater sites and assessing habitat quality. Biodivers. Conserv. 2009, 18, 1171–1185. [Google Scholar] [CrossRef]
  20. Noss, R.F. Indicators for monitoring biodiversity: A hierarchical approach. Conserv. Biol. 1990, 4, 355–364. [Google Scholar] [CrossRef]
  21. Chovanec, A. Dragonflies (Insecta: Odonata) as indicators of the ecological integrity of aquatic systems—A new assessment approach. Verh. Int. Ver. Theor. Angew. Limnol. 2000, 27, 887–890. [Google Scholar] [CrossRef]
  22. May, M.L. Odonata: Who They Are and What They Have Done for Us Lately: Classification and Ecosystem Services of Dragonflies. Insects 2019, 10, 62. [Google Scholar] [CrossRef]
  23. Vilenica, M. Ecological traits of dragonfly (Odonata) assemblages along an oligotrophic Dinaric karst hydrosystem. Ann. Limnol.-Int. J. Limnol. 2017, 53, 377–389. [Google Scholar] [CrossRef]
  24. Vilenica, M.; Rebrina, F.; Matoničkin Kepčija, R.; Šegota, V.; Rumišek, M.; Ružanović, L.; Brigić, A. Aquatic Macrophyte Vegetation Promotes Taxonomic and Functional Diversity of Odonata Assemblages in Intermittent Karst Rivers in the Mediterranean. Diversity 2024, 14, 31. [Google Scholar] [CrossRef]
  25. Datto-Liberato, F.H.; Lopez, V.M.; Quinaia, T.; do Valle Junior, R.F.; Samways, M.J.; Juen, L.; Valera, C.; Guillermo-Ferreira, R. Total environment sentinels: Dragonflies as ambivalent/amphibiotic bioindicators of damage to soil and freshwater. Sci. Total Environ. 2024, 934, 173110. [Google Scholar] [CrossRef]
  26. Rivas-Torres, A.; Cordero-Rivera, A. A Review of the Density, Biomass, and Secondary Production of Odonates. Insects 2024, 15, 510. [Google Scholar] [CrossRef]
  27. Novella-Fernandez, R.; Chalmandrier, L.; Brandl, R.; Pinkert, S.; Zeuss, D.; Hof, C. Trait overdispersion in dragonflies reveals the role and drivers of competition in community assembly across space and season. Ecography 2023, 2024, e06918. [Google Scholar] [CrossRef]
  28. Bãnãrescu, P.M. Distribution pattern of the aquatic fauna of the Balkan Peninsula. In Balkan Biodiversity Pattern and Process in the European Hotspot; Griffith, H., Kryštufek, B., Reed, J.M., Eds.; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2004; pp. 203–219. [Google Scholar]
  29. Miliša, M.; Ivković, M. Plitvice Lakes. In Springer Water; Springer International Publishing: Cham, Switzerland, 2023; ISBN 978-3-031-20377-0. [Google Scholar]
  30. Vilenica, M.; Mičetić Stanković, V.; Sartori, M.; Kučinić, M.; Mihaljević, Z. Environmental factors affecting mayfly assemblages in tufa-depositing habitats of the Dinaric Karst. Knowl. Manag. Aquat. Ecosyst. 2017, 418, 14. [Google Scholar] [CrossRef]
  31. Stilinović, B.; Božičević, S. The Plitvice Lakes—A natural phenomenon in the middle of the Dinaric karst in Croatia. Eur. Water Manag. 1998, 1, 15–24. [Google Scholar]
  32. Šegota, T.; Filipčić, A. Köppenova podjela klima i hrvatsko nazivlje. Geoadria 2003, 8, 17–37. [Google Scholar] [CrossRef]
  33. Zaninović, K.; Gajić-Čapka, M.; Perčec Tadić, M.; Vučetić, M.; Milković, J.; Bajić, A.; Cindrić, K.; Cvitan, L.; Katušin, Z.; Kaučić, D.; et al. Klimatski atlas Hrvatske/Climate atlas of Croatia 1961–1990, 1971–2000; State Hydrometeorological Institute: Zagreb, Croatia, 2008; Available online: https://klima.hr/razno/publikacije/klimatski_atlas_hrvatske.pdf (accessed on 5 August 2024).
  34. Wentworth, C.K. A scale of grade and class terms for clastic sediments. J. Geol. 1922, 30, 377–392. [Google Scholar] [CrossRef]
  35. Gerken, B.; Sternberg, K. Die Exuvien Europaïscher Libellen—The Exuviae of European Dragonflies (Insecta, Odonata); Arnika & Eisvogel/Huxaria Druckerei GmbH: Höxter/Jena, Germany, 1999; p. 354. [Google Scholar]
  36. Askew, R.R. The Dragonflies of Europe, 2nd ed.; Harley Books: Essex, UK, 2004; p. 308. [Google Scholar]
  37. Brochard, C.; Groendijk, D.; van der Ploeg, E.; Termaat, T. Fotogids Larvenhuidjes van Libellen; KNNV Uitgeverij: Zeist, The Netherlands, 2012; p. 320. [Google Scholar]
  38. StatSoft. STATISTICA 10.0 for Windows; StatSoft Inc.: Tulsa, OK, USA, 2010. [Google Scholar]
  39. Dijkstra, K.-D.B.; Wildermuth, H.; Martens, A. Freshwaterecology, Dataset “Odonata”. 2024. Available online: https://www.freshwaterecology.info/fwe_search.php?og=mzb (accessed on 20 July 2024).
  40. Ricotta, C.; Moretti, M. CWM and Rao’s quadratic diversity: A unified framework for functional ecology. Oecologia 2011, 167, 181–188. [Google Scholar] [CrossRef]
  41. ter Braak, C.J.F.; Šmilauer, P. Canoco Reference Manual and User’s Guide: Software for Ordination; Version 5.0; Micro-Computer Power: Ithaca, NY, USA, 2012. [Google Scholar]
  42. Miliša, M.; Habdija, I.; Primc-Habdija, B.; Radanović, I.; Matoničkin Kepčija, R. The role of flow velocity in the vertical distribution of particulate organic matter on moss-covered travertine barriers of the Plitvice Lakes (Croatia). Hydrobiologia 2006, 553, 231–243. [Google Scholar] [CrossRef]
  43. Gligora Udovič, M.; Cvetkoska, A.; Žutinić, P.; Bosak, S.; Stanković, I.; Špoljarić, I.; Mršić, G.; Kralj Borojević, K.; Ćukurin, A.; Plenković Moraj, A. Defining centric diatoms of most relevant phytoplankton functional groups in deep karst lakes. Hydrobiologia 2017, 788, 169–191. [Google Scholar] [CrossRef]
  44. Calijuri, M.L.; do Couto, E.A.; Santiago, A.F.; Camargo, R.A.; Silva, M.D.F.M. Evaluation of the influence of natural and anthropogenic processes on water quality in karstic region. Water Air Soil Pollut. 2012, 223, 2157–2168. [Google Scholar] [CrossRef]
  45. Antonović, I.; Treer, T. A review of freshwater ichthyofauna research published in the Croatian Journal of Fisheries since 1938. Croat. J. Fish. 2015, 73, 176–182. [Google Scholar] [CrossRef]
  46. Johansson, F.; Brodin, T. Effects of fish predators and abiotic factors on dragonfly community structure. J. Freshw. Ecol. 2003, 18, 415–423. [Google Scholar] [CrossRef]
  47. Dijkstra, K.D.B.; Lewington, R. Field Guide to the Dragonflies of Britain and Europe, 1st ed.; British Wildlife Publishing: Gillingham, UK, 2006; p. 230. [Google Scholar]
  48. Fekete, J.; De Knijf, G.; Dinis, M.; Padisák, J.; Boda, P.; Mizsei, E.; Várbíró, G. Winners and Losers: Cordulegaster species under the pressure of climate change. Insects 2023, 14, 348. [Google Scholar] [CrossRef]
  49. Pešić, V.; Gligorović, B.; Savić, A.; Buczyński, P. Ecological patterns of Odonata assemblages in karst springs in central Montenegro. Knowl. Manag. Aquat. Ecosyst. 2017, 418, 3. [Google Scholar] [CrossRef]
  50. Harabiš, F.; Dolný, A. The effects of ecological determinants on the dispersal abilities of central European dragonflies (Odonata). Odonatologica 2011, 40, 17–26. [Google Scholar]
  51. Hof, C.; Brändle, M.; Brandl, R. Lentic odonates have larger and more northern ranges than lotic species. J. Biogeogr. 2006, 33, 63–70. [Google Scholar] [CrossRef]
  52. Sertić Perić, M.; Jakopović, S.; Primc, B. Seasonal drift-benthos trends on a moss-covered tufa barrier within a karst barrage hydrosystem (Plitvice Lakes, Croatia). Nat. Croat. 2015, 24, 223–246. [Google Scholar] [CrossRef]
  53. Šemnički, P.; Previšić, A.; Ivković, M.; Čmrlec, K.; Mihaljević, Z. Tufa Barriers from a Caddisfly’s Point of View: Streams or Lake Outlets? Int. Rev. Hydrobiol. 2012, 97, 465–484. [Google Scholar] [CrossRef]
  54. Vilenica, M.; Ivković, M. A decade-long study on mayfly emergence patterns. Mar. Freshw. Res. 2020, 72, 507–519. [Google Scholar] [CrossRef]
  55. Pinilla-Rosa, M.; García-Saúco, G.; Santiago, A.; Ferrandis, P.; Méndez, M. Can botanic gardens serve as refuges for taxonomic and functional diversity of Odonata? The case of the botanic garden of Castilla–La Mancha (Spain). Limnology 2022, 24, 37–50. [Google Scholar] [CrossRef]
  56. Kučinić, M.; Previšić, A.; Vajdić, M.; Tunjić, M.; Mihoci, I.; Žalac, S.; Sviben, S.; Vučković, I.; Trupković, M.; Habdija, I. First systematic investigation of adults and second checklist of caddisflies of the Plitvice Lakes National Park with notes on research history, biodiversity, distribution and ecology. Nat. Croat. 2017, 26, 225–260. [Google Scholar] [CrossRef]
  57. Sertić Perić, M.; Matoničkin Kepčija, R.; Radanović, I.; Primc, B.; Habdija, I. Freshwater reefs as mesohabitats for the assessment of diel invertebrate drift patterns. Nat. Croat. 2020, 29, 185–203. [Google Scholar] [CrossRef]
  58. Vurnek, M.; Brozinčević, A.; Čulinović, K.; Novosel, A. Challenges in the Management of Plitvice Lakes National Park, Republic of Croatia. National Parks-Management and Conservation. In National Parks—Management and Conservation; Suratman, M.N., Ed.; IntechOpen: London, UK, 2018; pp. 55–72. [Google Scholar] [CrossRef]
  59. Takamura, K.; Hatakeyama, S.; Shiraishi, H. Odonata larvae as an indicator of pesticide contamination. Appl. Entomol. Zool. 1991, 26, 321–326. [Google Scholar] [CrossRef]
  60. Harabiš, F.; Dolný, A. Human altered ecosystems: Suitable habitats as well as ecological traps for dragonflies (Odonata): The matter of scale. J. Insect Conserv. 2012, 16, 121–130. [Google Scholar] [CrossRef]
  61. Vilenica, M.; Kerovec, M.; Pozojević, I.; Mihaljević, Z. Odonata assemblages in anthropogenically impacted lotic habitats. J. Limnol. 2020, 80, 1–9. [Google Scholar] [CrossRef]
  62. Corbet, P.; Brooks, S. Dragonflies. In Collins New Naturalist Library Series, Book 106; Harper Collins: London, UK, 2008; p. 480. [Google Scholar]
  63. Cíbik, J.; Beracko, P.; Bulánková, E.; Čiamporová Zaťovičová, Z.; Gregušová, K.; Kodada, J.; Derka, T. Are springs hotspots of benthic invertebrate diversity? Biodiversity and conservation priority of rheocrene springs in the karst landscape. Aquat. Conserv. Mar. Freshw. Ecosyst. 2022, 32, 843–858. [Google Scholar] [CrossRef]
Figure 1. Photo examples of study sites included in the study: springs: (a) Bijela rijeka spring, (b) Crna rijeka spring; streams (and small mountainous rivers): (c) Bijela rijeka middle reaches, (d) Crna rijeka middle reaches, (e) Crna rijeka lower reaches, (f) Plitvica, (g) Korana; tufa barriers: (h) Labudovac, (i) Kozjak–Milanovac, (j) Novakovića Brod.
Figure 1. Photo examples of study sites included in the study: springs: (a) Bijela rijeka spring, (b) Crna rijeka spring; streams (and small mountainous rivers): (c) Bijela rijeka middle reaches, (d) Crna rijeka middle reaches, (e) Crna rijeka lower reaches, (f) Plitvica, (g) Korana; tufa barriers: (h) Labudovac, (i) Kozjak–Milanovac, (j) Novakovića Brod.
Diversity 16 00645 g001
Figure 2. Environmental variables at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean annual values with standard deviation, SD): (a) nitrate concentration, (b) pH, (c) oxygen saturation, (d) water velocity, (e) conductivity, and (f) alkalinity. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05).
Figure 2. Environmental variables at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean annual values with standard deviation, SD): (a) nitrate concentration, (b) pH, (c) oxygen saturation, (d) water velocity, (e) conductivity, and (f) alkalinity. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05).
Diversity 16 00645 g002
Figure 3. Environmental variables at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean annual values with standard deviation, SD): (a) water temperature, (b) oxygen concentration, and (c) ammonia concentration. Non-significant differences among the habitat types are indicated by the letter a (Kruskal–Wallis H test with multiple comparisons post hoc test, p > 0.05).
Figure 3. Environmental variables at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean annual values with standard deviation, SD): (a) water temperature, (b) oxygen concentration, and (c) ammonia concentration. Non-significant differences among the habitat types are indicated by the letter a (Kruskal–Wallis H test with multiple comparisons post hoc test, p > 0.05).
Diversity 16 00645 g003
Figure 4. Dragonfly functional diversity (RaoQ index) at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD). Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05).
Figure 4. Dragonfly functional diversity (RaoQ index) at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD). Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05).
Diversity 16 00645 g004
Figure 5. Dragonfly functional traits at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD): (a) body shape, (b) dispersal capacity, (c) stream zonation preference, (d) lateral connectivity preference, (e) current preference, (f) substrate type preference, and (g) reproduction type. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05). Legend: DC = dispersal capacity; EUC = eucrenal, HYC = hypocrenal, ERH = epirhithral, MRH = metarhithral, HRH = hyporhithral, EPO = epipotamal, MPO = metapotamal, HPO = hypopotamal, LITT = littoral; EUP = eupotamon, PRP = parapotamon, PLP = plesiopotamon, PAP = palaeopotamon, TMP = temporary water bodies; LIP = limnophil, LRP = limno- to rheophil, RLP = rheo- to limnophil, RPH = rheophil; ARG = argyllal, PEL = pelal, PSA = psammal, AKA = akal, LITH = lithal, PHY = phytal, POM = particulate organic matter; ETS = eggs laid attached to substrate, EIS = eggs laid in substrate, SUB = eggs laid not attached to or in substrate, OWA = eggs laid in open water, IPL = eggs laid inside plant tissue, OPL = eggs laid onto plant material, IRS = eggs laid into submerged soil or onto submerged rock.
Figure 5. Dragonfly functional traits at three Dinaric karst lotic habitat types in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD): (a) body shape, (b) dispersal capacity, (c) stream zonation preference, (d) lateral connectivity preference, (e) current preference, (f) substrate type preference, and (g) reproduction type. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05). Legend: DC = dispersal capacity; EUC = eucrenal, HYC = hypocrenal, ERH = epirhithral, MRH = metarhithral, HRH = hyporhithral, EPO = epipotamal, MPO = metapotamal, HPO = hypopotamal, LITT = littoral; EUP = eupotamon, PRP = parapotamon, PLP = plesiopotamon, PAP = palaeopotamon, TMP = temporary water bodies; LIP = limnophil, LRP = limno- to rheophil, RLP = rheo- to limnophil, RPH = rheophil; ARG = argyllal, PEL = pelal, PSA = psammal, AKA = akal, LITH = lithal, PHY = phytal, POM = particulate organic matter; ETS = eggs laid attached to substrate, EIS = eggs laid in substrate, SUB = eggs laid not attached to or in substrate, OWA = eggs laid in open water, IPL = eggs laid inside plant tissue, OPL = eggs laid onto plant material, IRS = eggs laid into submerged soil or onto submerged rock.
Diversity 16 00645 g005
Figure 6. Redundancy analysis (RDA) ordination biplot showing the relationship between dragonfly functional traits and six significant environmental variables in Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia. Abbreviations of the functional (life history) traits are in Figure 4.
Figure 6. Redundancy analysis (RDA) ordination biplot showing the relationship between dragonfly functional traits and six significant environmental variables in Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia. Abbreviations of the functional (life history) traits are in Figure 4.
Diversity 16 00645 g006
Figure 7. Dragonfly functional diversity (RaoQ index) at four main substrate types in three Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD) Non-significant differences among the habitat types are indicated by the letter a (Kruskal–Wallis H test with multiple comparisons post hoc test, p > 0.05).
Figure 7. Dragonfly functional diversity (RaoQ index) at four main substrate types in three Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD) Non-significant differences among the habitat types are indicated by the letter a (Kruskal–Wallis H test with multiple comparisons post hoc test, p > 0.05).
Diversity 16 00645 g007
Figure 8. Dragonfly functional traits at four main substrate types in three Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD): (a) body shape, (b) dispersal capacity, (c) stream zonation preference, (d) lateral connectivity preference, (e) current preference, (f) substrate type preference, and (g) reproduction type. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05). Abbreviations of the functional (life history) traits are in Figure 5.
Figure 8. Dragonfly functional traits at four main substrate types in three Dinaric karst lotic habitats in the Plitvice Lakes NP, Croatia (shown as mean with standard deviation, SD): (a) body shape, (b) dispersal capacity, (c) stream zonation preference, (d) lateral connectivity preference, (e) current preference, (f) substrate type preference, and (g) reproduction type. Significant differences among the habitat types are indicated by different letters (Kruskal–Wallis H test with multiple comparisons post hoc test, p < 0.05). Abbreviations of the functional (life history) traits are in Figure 5.
Diversity 16 00645 g008
Table 1. Dragonfly species recorded at three lotic habitat types in the Plitvice Lakes NP, Croatia (for details see Vilenica [23]).
Table 1. Dragonfly species recorded at three lotic habitat types in the Plitvice Lakes NP, Croatia (for details see Vilenica [23]).
Dragonfly Species/Habitat TypeSpringsStreamsTufa Barriers
Gomphus vulgatissimus (Linnaeus, 1758) X
Onychogompus forcipatus (Linnaeus, 1758) XX
Cordulegaster bidentata (Selys, 1843) XX
Orthetrum coerulescens (Fabricius, 1798) X
Crocothemis erythraea (Brullé, 1832) X
Platycnemis pennipes (Pallas, 1771) XX
Calopteryx virgo (Linnaeus, 1758) X
Coenagrion puella (Linnaeus, 1758) X
Number of species (S)038
Table 2. Dragonfly functional traits used for quantifying dragonfly functional diversity at three lotic habitat types in the Plitvice Lakes NP, Croatia.
Table 2. Dragonfly functional traits used for quantifying dragonfly functional diversity at three lotic habitat types in the Plitvice Lakes NP, Croatia.
Functional Trait GroupFunctional TraitExplanation
Body typeAnisoptera
Zygoptera
Dispersal
capacity
High
Medium
Stream
zonation
preference
Metarhithrallower trout region
Hyporhithralgrayling region
Epipotamal barbel region
Metapotamal bream region
Hypopotamal brackish water region
Littoral lentic habitats
Lateral
connectivity
preference
Eupotamonlotic habitats
Parapotamon
Plesiopotamon (including lakes)lentic habitats
Palaeopotamon (including pools, ponds)
Temporary waterbodies
Current
preference
Limnophile preferring lentic habitats, rarely also occur in slow-flowing lotic habitats
Limno- to rheophilepreferring lentic habitats, but often also in slowly flowing lotic habitats
Rheo- to limnophilepreferring slow-flowing lotic habitats and their lentic zones, can also be found in lentic habitats
Rheophileoccurring in lotic habitats, preferably with
moderate and fast water velocity
Substrate type
preference
Argyllal silt, loam, clay
Pelalmud
Psammal sand
Akalfine- to medium-sized gravel
Lithal coarse gravel, stones, cobbles, boulders, bedrock
Phytal algae, bryophytes, macrophytes
POM particulate organic matter
Reproduction Reproduction mode and the form and location of oviposit clutches eggs laid attached to substrate
eggs laid into the substrate
eggs laid not attached to/in substrate
eggs laid into open water
eggs laid inside plant tissue
eggs laid onto plant material
eggs laid on exposed soil or rock
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Vilenica, M.; Mičetić Stanković, V.; Kučinić, M. Dragonfly Functional Diversity in Dinaric Karst Tufa-Depositing Lotic Habitats in a Biodiversity Hotspot. Diversity 2024, 16, 645. https://doi.org/10.3390/d16100645

AMA Style

Vilenica M, Mičetić Stanković V, Kučinić M. Dragonfly Functional Diversity in Dinaric Karst Tufa-Depositing Lotic Habitats in a Biodiversity Hotspot. Diversity. 2024; 16(10):645. https://doi.org/10.3390/d16100645

Chicago/Turabian Style

Vilenica, Marina, Vlatka Mičetić Stanković, and Mladen Kučinić. 2024. "Dragonfly Functional Diversity in Dinaric Karst Tufa-Depositing Lotic Habitats in a Biodiversity Hotspot" Diversity 16, no. 10: 645. https://doi.org/10.3390/d16100645

APA Style

Vilenica, M., Mičetić Stanković, V., & Kučinić, M. (2024). Dragonfly Functional Diversity in Dinaric Karst Tufa-Depositing Lotic Habitats in a Biodiversity Hotspot. Diversity, 16(10), 645. https://doi.org/10.3390/d16100645

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop