PREDICTING FUTURE SPECIES DISTRIBUTION OF ODONATA IN WESTERNMOST MEDITERRANEAN REGION UNDER CLIMATE CHANGE Master in Ecology, Environmental Management and Restoration Author: Aida Viza Sánchez Tutor: Dr. Cesc Múrria i Farnós Department of Evolutionary Biology, Ecology and Environmental Sciences University of Barcelona 28th of September of 2016
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PREDICTING FUTURE SPECIES
DISTRIBUTION OF ODONATA IN
WESTERNMOST MEDITERRANEAN
REGION UNDER CLIMATE CHANGE
Master in Ecology, Environmental Management and Restoration
Author: Aida Viza Sánchez Tutor: Dr. Cesc Múrria i Farnós
Department of Evolutionary Biology, Ecology and Environmental Sciences
University of Barcelona 28th of September of 2016
PREDICTING FUTURE SPECIES
DISTRIBUTION OF ODONATA IN
WESTERNMOST MEDITERRANEAN
REGION UNDER CLIMATE CHANGE
Master in Ecology, Environmental Management and Restoration
Author: Aida Viza Sánchez
Tutor: Dr. Cesc Múrria i Farnós Department of Evolutionary
Biology, Ecology and Environmental
Sciences University of Barcelona
28th of September of 2016
Internal Advisor: Dr. Núria Bonada, FEM Research Group, University of Barcelona
Main Advisor: Dr. Cesc Múrria, FEM Research Group, University of Barcelona
Author: Aida Viza, MSc student, FEM Research Group, University of Barcelona
ABSTRACT
A critic question in biodiversity conservation is how species will response in front of current rates
of Climate Change. Such environmental alterations have the potential to modify habitat
characteristics and, consequently, it is predicted that many species may shift their ranges to
higher latitudes or altitudes to remain in a constant environmental niche. On another hand,
those species with high evolutionary adaptation, phenotypic acclimation or plasticity are
expected to have the ability to face new conditions. Finally, species with poor strategies are
vulnerable and can become extinct. In this project, I focus on the evolutionary history, functional
traits characteristics and Species Distribution Models (SDM) of Odonata to elucidate how
species distribution of odonates in Iberian Peninsula and Morocco will be affected by Climate
Change and the role that traits would play in future species responses. In general, I found that
odonates potential distribution will be altered by an increase of temperature seasonality and
drought events, as a result of anthropogenic impact. High emissions scenarios were dominated
by a reduction of species potential distribution, while low emissions scenarios showed a trend to
subtile displacement from current species distribution. The ecological distance between species
including also closely related species was decoupled to their phylogenetic divergence.
Therefore, phylogeny cannot predict the ecological requirements of species. Moreover, none
clear pattern was found between traits (ecological and life-history), current habitat occupancy
and future potential distribution under several models of climate change. Hence, I cannot
elucidate species response based on the probability of their lineage to neither extinction,
northward range expansion nor shift in its distribution range. Further studies modelling multi-
species distribution considering intraspecific traits and genetic variability will be needed to infer
future species-specific distribution and extinction risk in order to do a correct management of
freshwater biodiversity under climate change.
RESUM
Una qüestió crítica en la conservació de la biodiversitat és com les espècies respondran davant
del Canvi Climàtic. Les alteracions ambientals poden modificar les característiques de l'hàbitat
i, en conseqüència, s’espera que moltes espècies canviïn la seva distribució a latituds o altituds
més elevades, per tal de romandre en un nínxol ambiental constant. S'espera que les espècies
amb una alta capacitat d’adaptació evolutiva, d’aclimatació o de plasticitat fenotípica puguin fer
front a les noves condicions. En canvi, les espècies amb estratègies limitades són vulnerables i
poden arribar a extingir-se. Aquest projecte pretén entendre com afectarà el Canvi Climàtic a la
distribució dels odonats de la Península Ibèrica i el Marroc, i quin paper juguen els trets
biològics en la resposta futura de les espècies. En general, la distribució potencial dels odonats
serà alterada com a resultat del canvi climàtic antropogènic. Els escenaris futurs amb majors
emissions estan dominats per la reducció de la distribució potencial de les espècies, mentre
que en els escenaris de baixes emissions aquest tendeix a desplaçar-se. No obstant això, la
distància ecològica entre espècies no està acoplada a la seva divergència filogenètica, per tant
la filogènia no pot predir els requeriments ecològics de les espècies. D'altra banda, no s'ha
trobat cap pauta clara entre les característiques funcionals, l’ocupació actual i la predicció de la
distribució potencial futura sota diversos models de canvi climàtic. Per tant, no puc aclarir com
respondrà cada espècie ni atribuir a un llinatge la probabilitat de canvi en la seva àrea de
distribució. Per tant, calen més estudis de modelització de distribució de múltiples espècies
tenint en compte les característiques i la variabilitat genètica intraespecífica, ja que són
necessaris per a inferir la futura distribució de les espècies i el grau d'amenaça, per tal de
realitzar una correcta gestió de la biodiversitat d’ecosistemes fluvials sota el canvi climàtic.
Table 1. Percentages of species potential distribution categories for each model (MPI and
HadGEM2 ES) and scenario (RCP 2.6 and RCP 8.5). Values >40% in bold. Categories: 1:
potential area is latitudinally or longitudinally displaced, 2: potential area is being expanded, 3: no
significant differences between current and future potential areas distribution, 4: habitat lost, 5:
significant reduction of potential area.
RAxML phylogenetic tree (fig. 6) included 2 suborders, 9 families and 73 species (80.2%
of the species list was covered), and the final matrix contained 8649 bp. The species
coverage was 67.12%, 58.90%, 72.60%, 72.60%, and 57.53%, for COI, 12S, 16S, 18S
and 28S genes, respectively (table S4). The two suborders Anisoptera and Zygoptera
were monophyletic, in agreement with other previous phylogenetic analyses (Dumont et
al., 2010; Dijkstra & Kalkman, 2012; Suhling et al., 2015). Zygoptera was divided in two
supported clades “Lestomorphs” and “non-Lestomorphs”. In the Iberian Peninsula,
Lestomorphs were composed by three genera: Chalcolestes, Lestes and Sympecma,
whereas the remaining genera Platycnemis, Ceriagrion, Pyrrhosoma, Ischnura,
Enallagma, Coenagrion, Erythromma and Calopteryx were clustered together in “non-
Lestomorphs”. Anisoptera order was separated into two clades: (1) families
Cordulegasteridae, Gomphidae, and Aeshnidae, and (2) families Corduliidae and
Libellulidae as indicated in Dumont et al. (2010). The first clade was well-resolved, and
all genera were placed as previously showed in Ware et al. (2007) and Dumont et al.
(2010). However, the monophyletic family Libellulidae did not have much supported
nodes, but genera position corresponds to Dijkstra & Kalkman (2012), except for the
genera Zygonyx and Crocothemis that were placed in the same clade. Finally,
Corduliidae was placed paraphyletic as Dijkstra et al. (2013) stated, but in contrast of
Dumont et al. (2009) that found this family as monophyletic.
Traits conservatism was rejected because Blomberg’s K and Pagel’s λ values in both
axes were close to 0 (K=0.000192 and λ=0.50 for the first axis, and K=0.000694 and
λ=0.37 for the second axis; p-value>0.05; table 2). In general, individual traits were
neither preserved in the phylogeny, except large body, wings and abdomen sizes that
were phylogenetically conserved in the two indexes (large body: K=3.15, λ=1; large
abdomen: K=1.27, λ=1; large wings: K=1.11, λ=1). All in all, these results indicated no
trait correlation in the phylogenetic tree and no phylogenetic signal of traits evolution. In
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other words, the ecological similarity of closely related species was decoupled to their
phylogenetic relations.
Odonata species commonly showed a high habitat specificity (Hassall & Thompson,
2008; Dijkstra, 2006; Suhling et al., 2015). It means that each species inhabited one of
the categories for each defined habitat preference. For instance, species that preferred
lentic water never were found in lotic habitats, or species located in riparian forest were
exclusive for this habitat. For example, Calopteryx virgo was only found in permanent
forested streams, Sympetrum meridionale preferred permanent vegetated ponds and
Cordulegaster boltonii was found in pristine highland streams. We also found few
generalist species, for instance Anax imperator inhabited in all types of lotic habitats, or
all Trithemis species inhabited permanent but also temporary lotic waters.
Distribution of trait categories across niche space explained a 23.59% of the total
variability on axis 1, whereas axis 2 and 3 explained a 19.73% and a 14.99%,
respectively (fig. 7). The morphological small sizes and also abundant and continuous
distributed species were the main contributors in the trait variance on the positive sides
on axis 1, whereas morphological medium sizes and also rare and fragmented
distributed species contributed negatively. In contrast, on axis 2 medium body size and
abundant and continuous distributed species were the main contributors on the positive
sides, while small body size and fragmented and rare distributed species contributed
negatively. Large morphological sizes contributed positively on axis 3, while medium
morphological sizes were negatively (fig. 7a).
The FPCA of traits disparity within species revealed how ecological characters are
distributed among families, indicating that each family was characterised by a certain
biological and ecological preferences and identity. In fact, permutation test of variance
between groups indicated significant differences between families in relation to traits
disparity (p-value = 0.01). Given the high specificity for preferred habitat, the families of
Odonata showed high variability of how individual species were distributed in relation to
traits disparity. Some families had high trait disparity (i.e., large circle area in fig. 7b) such
as Lestidae and Libellulidae, whereas other families showed low trait disparity such as
Platycnemididae.
In fig. 7c species were grouped as currently vulnerable because they inhabit high
elevations (blue labels) or their habitat distribution was in regression (red labels) against
species that will expand geographical range (yellow label) or have the capacity to do it
(green labels). None of these groups were plotted nearby on the FPCA axes. Similarly,
we also labelled species according to their category in the hypotheses (fig. 7d for 2050
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and fig. 7e for 2080): blue labels showed species grouped as “favoured” because
potential distribution will expand, in contrast to vulnerable or critical species that their
potential distribution will be reduced (orange labels), and in some cases their potential
habitats will disappear (red labels). Some species were classified as “stable” distribution,
since potential distribution maybe shift, but the total area is equal (green label if shifts
and yellow label if is the same region). It did not show any pattern, i.e., species distributed
across the trait space did not reveal if a species is going to expand or reduce their
potential distribution.
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Fig. 5. Examples of each hypothesized category. Square colours correspond to the code
indicated in fig. 1. The colour of the areas showed in current, 2050th and 2080th maps have
their legend below (colours key).
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Fig. 6. Maximum-likelihood phylogenetic tree of 5 genes of Order Odonata including 31 genera
belonging to 9 families. Comprises 77 taxa including 4 outgroup genera of Ephemeroptera. Branch
support percentage is indicated: maximum likelihood bootstrap (>80) / Bayesian inference (>0.95),
*refers to branches with discordances between the two phylogenetic inferences. Suborder
classification is given by coloured branches: Zygoptera and Anisoptera.
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Fig. 7. Fuzzy Principal Component Analysis (FPCA) on trait data. (a) Distribution of functional traits on FPCA axes. See Table S1 for traits labels code. (b)
Distribution of the families on FPCA axes. Family names code is: Ca, Calopterygidae; Ce, Coenagrionidae; Le, Lestidae; P, Platycnemidae; A, Aeshnidae;
Cg, Cordulegasteridae; Cl, Corduliidae; G, Gomphidae; Li, Libellulidae. See Table S4 for species code. The two suborder groups are represented in the
same colours as phylogenetic tree in figure 5. (c) Current species status. Red labels: vulnerable, blue: high altitude habitats, green: potentially expansive,
yellow: expanding. (d-e) Species labelled as the category which they belong in 2050 (d) or 2080 (e). Colours correspond to the code indicated in fig. 1.
Axes 1 and 2 explained 23.59 and 19.73% of the total variability, respectively.
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Category Traits Code K PIC.variance.P λ M
orp
ho
log
y
Body Size
<40 BS 0.00 0.23 0.87
>40 - <60 BM 0.00 0.30 0.89
>60 BL 3.15 0.00 1
Abdomen Size
<30 AS 0.44 0.00 0.86
>30 - <45 AM 0.30 0.00 0.88
>45 AL 1.27 0.00 1
Wing (posterior) Size
<30 WS 0.00 0.31 0.81
>25 - <38 WM 0.00 0.25 0.88
>38 WL 1.11 0.00 1
Dis
trib
uti
on
Density Abundant AB 0.00 0.60 0
Rare RA 0.00 0.63 0
Distribution
Continuum CO 0.09 0.13 0
Fragmented FR 0.09 0.14 0
Vulnerable VU 0.13 0.51 0
Range
North-Africa NA 0.00 0.81 0
Iberian Peninsula PI 0.00 0.68 0.54
Europe EU 0.00 0.12 0
Africa AF 0.44 0.00 1
Hab
ita
t p
refe
ren
ces
Habitat
River RV 0.15 0.08 0.64
Streams ST 0.25 0.00 0.81
Ponds PD 0.00 0.41 0.55
Lakes LK 0.00 0.40 0
Seasonality Temporal TP 0.00 0.83 0
Permanent PR 0.00 0.84 0
Vegetation
Submergent SB 0.16 0.09 0
Floating-leaf FL 0.09 0.23 0.14
Ruderal RO 0.12 0.03 0.55
Forest, riparian FO 0.26 0.02 0.84
Water Chemistry
Acid AC 0.08 0.57 0
Saline SA 0.00 0.97 0
Ad
ult
s
Flight
Winter: I-II WI 0.00 0.99 0
Spring: III-V SP 0.00 0.77 0
Summer: VI-IX SU 0.00 0.79 0.21
Autumn: X-XII AU 0.00 0.77 0.43
Axis 1 of the FPCA 0.000192 0.60 0.50
Axis 2 of the FPCA 0.000694 0.22 0.37
Table 2. Niche conservatism results expressed as Blomberg’s K and Pagel’s λ indices. The higher
the K statistic, the more phylogenetic signal in a trait: K = 0 means a random pattern of evolution,
trait variation has not followed the phylogeny; K = 1 indicates some degree of conservatism; when
K > 1 there is a strong phylogenetic signal and conservatism of traits (bold numbers). Traits with
PIC.variance.P < 0.05 have non-random phylogenetic signal. In the same way, when λ is close
to 1, internal branches retain their original length indicating a strong trait correlation with the tree;
whereas when λ go towards 0, trait evolution has not followed the tree topology.
22
DISCUSSION
Future climate predictions under the four scenarios evidenced an increase in seasonality
of temperature and a decrease in rainfall variability. In general, the predicted
environmental characteristics of Mediterranean basin and inland of Iberian Peninsula will
be harsher than the Atlantic coast due to the increase of drought events, which will be
buffered by change in the atmospheric circulation (Giorgi & Lionello, 2008). As expected,
the predicted future climate conditions will directly impact on future species distribution
of odonates, but these responses will be highly variable across species and predictions.
For instance, several species will lose their potential distribution area in Iberian Peninsula
(e.g., Sympetrum flaveolum), in opposition, other species will shift or increase their
potential distribution areas (e.g., Anax ephippiger). Across predictions, differences were
evident between the most pessimist model HadGEM2 versus MPI global climate models
and between the highest RCP 8.5 versus the lowest RCP 2.6 emissions scenarios. In
general, if only the environmental conditions are considered, the predictions for 2080 for
the most severe conditions showed that the majority of species (54.69%) will reduce their
potential distribution (category 4) and around 7.81% will go extinct (category 5). In
contrast, the most favourable conditions revealed a subtle dominance of species that
expand their potential distribution (category 2) or species that will displace their
geographical distribution (category 1) to habitats where the ecological conditions will be
more suitable Hence, the climatic models used to predict the future distribution of
odonates indicate that human measures for reducing anthropogenic emissions are
critical for ensuring habitat conservation and preserving the present-day diversity of
species.
Despite I revealed how important is to model species-specific effects of global warming
on abiotic conditions for multiple species, the high variability across species disallow me
to establish generalizations. Since the majority of species will reduce their distribution
range in similar or higher emissions than currently, the species-specific biotic responses
of odonates facing climate change will be critical for occupying or not the new potential
distribution. In general, species could respond to climate change (1) moving in space or
time to remain in a constant environmental niche, or by (2) evolutionary adaptation or (3)
2007) and it is also well documented in odonates from North-Africa to South-Europe
(Cano-Villegas & Conesa-García, 2009) and from South-Europe to North-Europe
(Hickling et al., 2006; Ott, 2010). However, my results did not support a massive
northward expansion of any specific linage or trait characteristics of odonates following
habitat change, in contrast, obtained patterns of future potential species distribution
indicated idiosyncratic responses when the entire diversity of odonates form the
westernmost Mediterranean regions is considered.
The Iberian Peninsula harbours a high diversity of odonates that differ in distribution
ranges and habitat specificity, but I did not find a clear pattern between analysed
biological traits, current habitat preferences and future suitable habitats. For many
species, Iberian Peninsula is either the southernmost region of their European
distribution (e.g., Brachytron pratense), the northernmost region of their African
distribution (e.g., Diplacodes lefebvrii) or the centre (e.g., Oxygastra curtisii) of their
Mediterranean distribution (Dijkstra, 2006). It is expected varying ecological and
functional traits across species with disparate distribution range, which suggests the high
diversity of differences in ecological requirements among these species. Biological and
ecological traits determine niche occupancy. For instance, freshwater species and also
odonates could be classified by their preferred water temperature conditions in warm-,
cool- and cold-water types. Climate warming will favour warm-water species opposite to
cold-water species because temperature will tend to increase (Heino et al., 2009). In fact,
theoretically species can be classified as vulnerable (e.g., bad flyers, low tolerance to
eutrophication) or favourable (e.g., mechanism of resistance to drought events or high
temperatures) depending on their response facing climate change (Ott, 2010), but I found
here that analysed biological traits and future SDMs are decoupled. It means that I
cannot predict future direction of the species responses facing climate change and
therefore there are not favourable traits to face global warming expanding to new
habitats. For instance, species with favourable traits in front of drought events (e.g.,
preference for temporary habitats such as Sympetrum flaveolum) will not expand if their
future potential distribution area is not expected to increase in parallel. This study reveals
that ecological and life-history traits are not good predictors of species shifts for
odonates, which was also previously suggested for American songbird species (Auer
and King, 2014).
The evolutionary signature of trait conservatism is not preserved, except size-related
traits such as abdomen, body and wings length. The only conserved traits are associated
also to wing patterns that can easily distinguish the two monophyletic suborders of
24
Odonata (Anisoptera and Zygoptera) (Dumont et al., 2010; Dijkstra & Kalkman, 2012).
The non-preserved ecological traits can be explained by several mechanisms. Odonata
have tropical origins and are one of the oldest winged insects that still inhabit the earth.
These taxa belong to Odonatoptera, first appearing back minimum to the Upper
Carboniferous period (~300Ma) (Suhling et al., 2015). Such old lineages must have
faced multiple climate changes and adverse environmental conditions over millions of
years that could promote repeated and independent extinction and speciation across
clades, which likely explain some of the lack of phylogenetic signal. In contrast, young
insect orders such as Trichoptera have been appeared more recently and the
phylogenetic signal is still preserved in current species (Garcia-Raventós et al., in
preparation). Moreover, Odonata diversification is more related to sexual morphology,
reproductive behaviour and interactions between species than adaptive ecological
divergence (Wellenreuther et al., 2012), which in turn can affect the loss of a
phylogenetic signal of niche conservatism. As a result, the ecological space delimited by
species traits and the high habitat-specificity of odonates did not show significant
patterns across lineages. In other words, habitat preference such as temporary pond
non-vegetated can be occupied by different species across lineages indistinctively. Thus,
the phylogeny of Odonata is not useful to elucidate which traits are characteristic in each
lineage and if this given trait can predict species vulnerability facing climate warming.
Consequently, I cannot attribute to a lineage the probability of neither extinction,
northward range expansion nor shift in its distribution range. However I did not test
species plasticity and local adaptation, therefore, there are multiple unexplored biotic
factors like species interaction, trophic networks, hot-tolerance, resistance to drought
events, etc. (Hassall & Thompson, 2008) that must influence species colonization and
establishment to new habitats. Further studies modelling multi-species distribution
considering intraspecific traits and genetic variability are needed to infer future species-
specific distribution and extinction risk in order to do a correct management of freshwater
biodiversity under climate change.
25
CONCLUSIONS
As a main result of this project, I found odonates future potential distribution will be
affected by Climate Change. Many species will shift their potential distribution to new
suitable habitat, but the rates and directions at which species will achieve the new
localities are species-specific. Other species will reduce their potential distribution and
their locally adaptability or phenotypically acclimatise will allow them avoid extinction risk.
Despite each Odonata family showed their own ecological space, which was
differentiated between families, the niche conservatism was rejected because traits were
not preserved in phylogenetic tree of Iberian and Moroccan odonates. These results
indicated that the ecological distance between species including also closely related
species was decoupled to their phylogenetic divergence. Therefore, phylogeny cannot
predict the ecological requirements of species.
Although species have high habitat-specificity, none clear pattern was found between
traits (ecological and life-history), current habitat occupancy and future potential
distribution under several models of Climate Change.
Understanding how Odonata will response in front of a Climate Change is critical to carry
out a correct management in order to protect vulnerable species and maintain freshwater
biodiversity.
ACNOWLEDGEMENTS
I would like to acknowledge the help of Oxygastra and AEA El Bosque Animado groups
who gently provided the occurrences data. I am especially gratefull to Xavier Maynou
and Ricard Martín from Oxygastra for field training and their sound advices, and also to
Florent Prunier from AEA El Bosque Animado for his recommendations. I am very
grateful to María Ángeles Pérez for her great help with SDM and also to Dr. Dani Sol and
his group for share their server-resources. Dr. Núria Bonada and Tony Herrera are
thanked for their valuable comments and contacts, and also the research group FEM
(Freshwater Ecology Management) for providing the space, equipment and
unconditional encouragement for the investigation. Finally, I really appreciate the harsh
job, collaboration and nearby support of my lab team (Macro&EvoLAB), my advisor Dr.
Cesc Múrria and Aina Garcia-Raventós.
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Body size Ab. Distrib. Range Habitat Seas. Vegetation Chem. Adult