How Does Global Climate Change Affect Islands

Abstract

Island systems are amidst the most vulnerable to climate alter, which is predicted to induce shifts in temperature, rainfall and/or bounding main levels. Our aim was: (i) to map the relative vulnerability of islands to each of these threats from climate alter on a worldwide scale; (2) to estimate how island vulnerability would affect phylogenetic diversity. We focused on monocotyledons, a major group of flowering plants that includes taxa of important economic value such every bit palms, grasses, bananas, taro. Islands that were vulnerable to climatic change were found at all latitudes, e.g. in Commonwealth of australia, Indonesia, the Caribbean area, Pacific countries, the Us, although they were more mutual near the equator. The loss of highly vulnerable islands would lead to relatively low absolute loss of plant phylogenetic diversity. However, these losses tended to be higher than expected by chance alone even in some highly vulnerable insular systems. This suggests the possible plummet of deep and long branches in vulnerable islands. Measuring the vulnerability of each island is a starting time step towards a risk analysis to identify where the impacts of climate change are the most likely and what may be their consequences on biodiversity.

Introduction

Information technology is now widely accepted by the scientific community that the Globe is undergoing drastic climate change due to increased greenhouse gas emissions¹. Changes in global climate accept occurred several times throughout the Earth's history but have stretched over very long periods of fourth dimension whereas currently these changes are taking identify over the space of a century or less^one,two,3. This rapid alter, associated with other threats resulting from homo activity related to product and consumption^four, are having a strong impact on biodiversity^v,six. Considered as ane of the 5 principal causes of species and populations losses^7,8,9, climate change may pb to direct alterations of natural habitats, forcing species to move from their historical range, accommodate to new ecology conditions, find refuge in unaltered microhabitats or may lead to species extinction^{3,ten,11,12,13}. Chiefly, climate change acts in synergy with other human being-induced threats, such equally land apply intensification or biological invasion, increasing their effects.

In this context, island biodiversity requires specific attention for several reasons. Insular communities, because they are spatially segregated and have evolved in isolation, are characterized by extremely high rates of endemism^14,15. Although they occur on less than v% of the Earth's terrestrial area, isle plants and vertebrates have an endemic richness that may exceed that of mainland species by a factor of 9.5¹⁵. Island biota are as well very prone to extinction: around 80% of past extinctions and a third of threatened terrestrial species are found on islands¹⁶. Past extinctions were probably triggered past invasive species, the naïveté of insular species, and the high range-restriction of some populations^{17,18,nineteen,twenty,21,22}. Although climate change might impact island biota in many different ways, information technology is likely that sea level rise and climate shifts will exist of major importance due to their direct association with the availability of suitable habitats for terrestrial organisms. Bounding main level rise is expected to pb to the submergence of several islands^2,23. Ocean level rising may also increment coastal erosion and saline water intrusion, impacting natural habitats^24,25. This means that elevation, area, and the complexity of shoreline inlets are of major importance regarding vulnerability to sea level rise^26,27. Equally for climate shift, it includes changes in the frequency and intensity of extreme weather events (e.g. droughts, tempest surges, hurricanes), besides as altered patterns of seasonal and mid-term weather systems. This leads to the displacement of suitable climatic conditions to dissimilar altitudinal or latitudinal ranges, which implies that for some island species, suitable climates may only be plant far beyond their limits²⁸. Island size and topographic heterogeneity will and so play a central role in preserving habitats where species could survive. When suitable habitats disappear, species that are able to adapt or/and have advantageous traits, e.yard. flowering times that can rail temperature shifts²⁹, volition probably be naturally selected nether the new ecology atmospheric condition, whereas others may go extinct. Shifts in climatic conditions may then promote a cascade of local extinctions.

Despite the importance of island biota to global biodiversity, the impact of climate change on insular biodiversity has just begun to exist investigated^{23,28,30,31,32,33,34}. The few existing studies focused just on species richness, and the lack of cognition of other biodiversity currencies certainly limits our understanding of this impact. In fact, species richness lonely does not provide information regarding certain crucial aspects for species conservation such as evolutionary history³⁵. Thus far, nosotros do non know how climatic change will impact the tree of life. Will it lead to the loss of deep and/or unique evolutionary branches, or to random pruning? Tin nosotros await a certain tendency towards resilience, as observed on continents^36,37? If so, for what reasons?

To begin to understand these bug, we designed a study to estimate isle relative vulnerability to climatic change and assess its impacts on the monocot tree of life. Relative vulnerability allows to identify islands which may exist the most threatened by climate change at a world scale. These bug are specially important for this major group of plants, which has a worldwide distribution and high species richness and endemism on islands. Monocots also provide a wide range of products to mankind. We used the phylogenetic diversity (PD) measure out from³⁸ to mensurate the expected PD at risk of being lost^39,twoscore. PD is more than a simple assessment of the evolutionary aspect of biodiversity every bit it may highlight current and future benefits provided by biodiversity to people and ecosystems, i.due east. pick-values^41,42. Moreover, the loss of PD can be much higher than the loss of species richness (SR) if (i) closely related species go extinct (thus threatening non only terminal branches simply too deep branches shared by a set of species), or (ii) if species on long and isolated branches disappear^38,43,40. Patterns of PD loss may then assist identify which parts of the tree of life are the almost at risk from climate change. Nosotros analysed 1,497 genera distributed across five,565 islands from across the world. This is as well the first global scale study of this kind to integrate regional variations of climatic modify as estimated by the Intergovernmental Panel on Climatic change (IPCC).

Results

Frequency and distribution of vulnerability to climatic change (step 1)

Over the 5,565 islands studied, the most represented category was "moderate vulnerability", followed by low, loftier and very high vulnerability, respectively, for all the types of threats. In full general, global vulnerability was correlated to sea level rise, shift in temperature and shift in rainfall, all the same, scores for these three threats had lower correlations with each other (Table 1). Islands that were virtually vulnerable to threats from climate change were more than frequently situated at depression latitudes and/or in the Southern Hemisphere, e.g. in Australia or in the Pacific Ocean, such as Kiribati and French Polynesia islands (Fig. i). Withal, some northern islands also had high vulnerability, especially regarding shifts in rainfall (Fig. one), for example in Norway and Sweden. In full, 54, 109, 165 and 34 islands had a very loftier vulnerability to bounding main level ascension, shift in temperature, shift in rainfall, and global threat from climate change, respectively (Fig. 1; Supplementary Datasets S1 and S2).

Table 1 Correlation coefficients betwixt vulnerability scores for each threat beyond all islands using Pearson's correlation test.

Total size tabular array

Spatial distribution of ExpPDloss (step two)

Accented ExpPDloss

Estimates of expected loss of phylogenetic diversity at a global scale (ExpPDloss) following local species extinctions indicated that the ExpPDloss per island was highest at low latitudes and in the eastern part of the world such every bit in Madagascar, Borneo, New Guinea, Taiwan, Sri Lanka, Sumatra but with Cuba being ane of the most notable exception (Fig. 2; see Supplementary Dataset S1 for the full list of islands and their ExpPDloss). The islands whose disappearance would cause the greatest ExpPDloss when only owned genera were included were Madagascar, Sumatra, Tasmania, New-Caledonia, Honshu, Cuba, New Republic of guinea, and Sri Lanka, among others (Fig. 2). When corrected for sampling effort, the relative ExpPDloss values inverse only slightly when considering either all genera or simply endemic genera (Supplementary datasets S1 and S2).

Where is ExpPDloss significantly high?

By removing the effect of richness on the ExpPDloss using null models (see methods), we establish that the most significant losses were predominantly expected at low latitudes and eastern longitudes (Fig. 3). Islands with highly significant ExpPDloss were, among others: Republic of madagascar, Kalimantan, New-Republic of guinea, Tasmania, Sri Lanka, just also Cuba and Tierra del Fuego. For insular endemic genera, significant ExpPDloss was constitute, amidst others, for Republic of madagascar, Indonesia (Sumatra, Borneo, New Guinea, Sulawesi), the West Indies (Cuba, Jamaica, Hispaniola), Honshu, Sri Lanka, and Tasmania (Fig. 3).

Would the disappearance of highly vulnerable islands take a large effect on PD? (footstep 3)

Loss of phylogenetic diversity per island and category of vulnerability

We establish that, on average, the ExpPDloss for each category of vulnerability was very similar across the iv types of threats (Fig. 4). However, the highest values of ExpPDloss were found for islands with moderate vulnerability (Fig. 4). Notable exceptions include Cuba and New Guinea, which were highly vulnerable to predicted sea level rise and shifts in rainfall, respectively, and whose disappearance would cause large ExpPDloss. Significant ExpPDloss, i.e. higher than expected by chance (p_value_ind), was establish for only a modest proportion of islands among all categories of vulnerabilities (Fig. 5). For shifts in temperature and sea level rise, the median p-value_ind was highest in the "very high vulnerability" category (Fig. v). When considering only endemic genera, the highest ExpPDloss was predicted to occur mainly for islands in the "moderately vulnerable" category (Fig. iv). Moreover, just a small proportion of islands had meaning ExpPDloss (Fig. v) and they generally had a low or moderate vulnerability to climate change (east.k. Madagascar, large Indonesian islands).

Would the extinction of all genera on vulnerable islands crusade higher ExpPDloss than extinctions at random?

We found contrasting results depending on the threat considered. For shifts in temperature, ExpPDloss was college than expected by chance merely when all islands with low vulnerability were lost (p_value_all; Fig. six). Regarding sea level rise and global vulnerability to climate change, p_value_all were relatively high in both islands with moderate and very loftier vulnerability. As for the event of a shift in rainfall, ExpPDloss was the most pregnant when highly vulnerable islands were lost. Moreover, for three out of the 4 threats considered, the loss of genera occurring on the most vulnerable islands would cause college ExpPDloss than expected in 60% to 80% of our randomizations. Yet, we observed that p_values_all were poorly congruent with the phylogenetic bespeak of extinction probabilities (Fig. 6).

Similar results were found when focusing only on endemic genera. ExpPDloss was generally greater than by chance with the loss of (i) islands with low vulnerability to shifts in temperature; (ii) islands that are highly vulnerable to shifts in rainfall; (three) islands with either loftier or low vulnerability to body of water level rise; and (iv) islands with moderate vulnerability to the global threats from climate change (Fig. 6).

Discussion

The present change in climate is raising many questions regarding its issue on biodiversity and the conservation measures to exist taken to mitigate its impacts⁴⁴. In this report, nosotros focused on islands to investigate the vulnerability to climate change of these segregated spatial units that strongly contribute to the world'southward diversity³³. The master aims were to categorise islands worldwide according to their vulnerability to climate change and to investigate how the estimated vulnerability would touch the tree of life of monocots.

Every bit to exist expected, for the set of features considered, the highest vulnerability values were assigned to islands that were small, depression, jagged, and located in areas where bounding main level ascent, shifts in temperature and/or rainfall were predicted to be the highest. Yet, the circuitous interaction between island features and threat levels meant that vulnerable islands were identified across the world. In detail, low lying islands situated in the Caribbean and the Pacific were highly vulnerable to the effects of ocean level rise (eastward.g. The Melt Islands, French Polynesia, the Republic of the marshall islands)^34,45. Large predicted shifts in rainfall in Due north America and Scandinavian countries combined with low elevations and pocket-sized areas, may explicate why many islands that are vulnerable to shifts in rainfall are located in the Northern Hemisphere (although many others are found near the equator and at Southern latitudes).

By estimating the relative threat of climate change on insular biodiversity based on predictions from the IPCC, we identified islands where species may be most at take chances in a context of dubiousness⁴⁵. This could and then help to conceptualize the effects of climate modify and establish strategies to preserve biodiversity. Like analyses could be carried out for other groups of organisms, such equally eudicots, mammals^31,34, or to assess the risks faced by man settlements⁴⁶.

As this is the offset study at this scale, some critical features could not be taken into account due to the paucity of standardized information for a large number of islands. We lacked data on the lithology of many islands which is some other important cistron of vulnerability to bounding main level rising. For instance, islands with rocky shores are likely to be more stable, whereas islands with sedimentary shores may adjust in shape, size and position over very short periods of time depending on the supply and transportation of sediments⁴⁷. Equally for reef islands, they might grow following shifts in sea levels (just meet⁴⁸). The study of Kench et al.⁴⁹ illustrates this complex situation, in that eighteen out of 29 coral islands afflicted by ocean level rise had actually grown in size due to new gravel deposits during cyclonic events.

Regarding estimates of vulnerability to shifts in temperature and rainfall, at that place are at least three chief sources of uncertainties and limitations that should be considered. The first is that the scale of global predictions may fail to account for more localised furnishings and, in some cases, does not let to distinguish spatially close islands with dissimilar ecology weather condition^33,l,51,52. The second is the doubt concerning these estimates for islands located in regions that are largely influenced past major climate drivers with very high variability, and for which even the direction of their impact nether climate change is hard to predict (east.yard. El Niño Southern Oscillation)^33,53. The 3rd is the climatic heterogeneity within islands, which is expected to be greater in larger and more than elevated islands, with important climatic differences between windward and leeward regions⁵⁴, or along altitudinal belts. This makes that a single vulnerability score may non be sufficient to capture the spatial heterogeneity of threats in large and/or mountainous islands. It must be considered, however, that part of this complication is comprised in the vulnerability index, as area, altitude and topographic heterogeneity are integrated in the cess of vulnerability. Our chief conclusion regarding this point is that, although the vulnerability scores used hither do allow comparing a wide range of islands at a global scale, more research is necessary to understand the effects of climate and topographic heterogeneity on the vulnerability to climate alter. Every bit a direction, we suggest focusing on large islands where a significant proportion of the Tree of Life could exist lost if some species went extinct (e.g. Madagascar, Borneo, New-Guinea, Cuba, Taiwan, Sri Lanka, Sumatra). In add-on, as vulnerability assessments can be conducted at different scales, one prospect would be to define dissimilar levels of vulnerability depending on conservation objectives. In this framework, our approach could for case correspond to "level one" based on isle typology, level "0" could refer to the vulnerability of archipelagos, "level 2" to the vulnerability of habitats etc.

In the Global Assessment Report on Biodiversity and Ecosystem Services released by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), PD is now recognised as a fundamental indicator of one of "Nature's Contributions to People" (NCP 18 - maintenance of options)⁵⁵. Indeed, PD provides options for future generations and for organisms to adapt in a irresolute environment^38,41,42. The IPBES therefore highlighted that the loss of phylogenetic diverseness implies irreversible losses of options to humanity⁵⁵. In this context, assessing the impacts of island vulnerability to climate change represents a first step to provide cognition for conservation actions aiming at the reduction of irreversible losses.

The outset analyses of our research show that extinctions on the most vulnerable islands would remove relatively little insular PD. Indeed, vulnerable islands generally have small size and low top which are factors of low species richness⁵⁶, conducting to reduced loss of PD⁴⁰. By contrast, islands that contribute the most to loss of PD were just moderately threatened by climate change. This was the case for Madagascar, Borneo, Honshu, Sri Lanka, Sumatra, New Caledonia, which all harboured loftier rates of endemic and evolutionary unique genera (Supplementary Method S2)¹⁵. These islands are big and environmentally various which fosters high richness and endemicity but also offers greater opportunities for plants to track their climatic preferences^15,57,58.

Nonetheless, the link betwixt ExpPDloss and taxon richness may hide the fact that some long and/or deep branches of the tree of life may occur on vulnerable islands. By explicitly removing this association using comparisons with null models, we constitute that some highly vulnerable islands – although non all of them – may lose more PD than expected past take a chance. This is particularly true for islands that are highly vulnerable to sea level rise and temperature shifts, which is probably due to their greater frequency at depression latitudes, where some range-restricted taxa representing relatively large amounts of PD occur (Supplementary method S2). This reinforces the claim that highly vulnerable islands could be home to evolutionary distinct, rare and endangered genera and that climatic change would increase their likelihood of extinction^31,34.

These outcomes correspond to a worst-example and island-centred scenario in which all genera on an island would become extinct, and in which the probability of extinction of a genus is proportional to the number of islands it disappears from. Nosotros acknowledge that sensitivity to climatic change is highly complex and depend on many factors such as species ecological preferences and tolerances, traits (east.g. phenology), dispersal potential (e.chiliad. among islands of an archipelago) or biotic interactions. Species-centred and trait-based approaches remain therefore essential to understand the responses of species to threats from climate change merely may be more relevant at regional or local scales. Finally, we besides encourage the mobilization of data hosted in natural history collections and complementary field sampling in islands where impacts of climate change are expected to exist high. This would contribute to include several islands that were discarded from the nowadays analysis due to lack of advisable data, as for example, many islands along the entire coasts of Southern asia, North Africa, in the Red Bounding main, or in the Maldives (but a unmarried island of the archipelago could exist included hither).

The simulation of the extinction of all genera occurring on vulnerable islands showed one more facet of the consequences of climate change. If genera occurring on vulnerable islands went extinct, the monocot tree of life would be pruned to non-negligible proportions (i.e. causing higher ExpPDloss than random). Several hypothesis can exist evoked to explicate this outcome. The first is that it is driven by the loss of the well-nigh evolutionarily distinct and/or range-restricted genera. Nonetheless, the different tests performed hither showed that the expected loss of the almost evolutionarily distinct genera and the expected loss of genus richness were rarely significant when all vulnerable islands were lost (Supplementary method S2). A second potential caption for significant ExpPDloss on vulnerable islands would be that genera are closely related^43,40. Yet, the phylogenetic signal of extinction risks was relatively depression on vulnerable islands, indicating that genera threatened by the loss of the most vulnerable islands tended to exist randomly distributed amid the tips of the phylogeny. The rejection of these hypotheses leads then to consider 2 other possibilities. The offset is that certain range-restricted genera are amassed in species-poor clades, thus threatening the respective deep branches, whereas many others are over-dispersed, i.e. some deep branches besides back up rubber taxa. The second explanation is that some relatively long branches are threatened, although many other evolutionarily distinct genera are secured. These hypotheses that there is a relatively low number of deep and long branches at hazard is supported past the moderate frequency of cases where ExpPDloss is higher than random. Overall, these findings prove that, as also observed by^36,59, taxa that are vulnerable to climate alter may be constitute either on long or brusque branches, and whereas some are over-dispersed in the phylogeny, others are clustered in item clades.

Previous studies because the impacts of climate modify on PD^36,37,59 were conducted on a continental scale. They showed that climate change could lead to spatial homogenization of PD and that the tree of life would exist, to a certain extent, resilient to this threat. In comparing, our study highlights the need to consider the specificity of island systems when devising conservation strategies. H2o expanses may institute a stiff barrier against species dispersal. This implies that local extinctions, rather than shifts in the distribution range, are more than likely, specially when considering some features of insular biota such as the loss of dispersal ability, depression population sizes, and narrow distribution ranges. Consequently, PD loss instead of PD homogenization is expected and insular PD is certainly more than threatened than continental PD.

Determination and prospects

To conclude, assessing the vulnerability of islands to climate change represents a first pace towards identifying where its impact on biodiversity is most probable to be seen^{27,34,45,threescore,61}. Importantly, by tackling the crucial challenges to predict and mitigate the effect of climatic change on biodiversity, this report contributes to issues of global relevance as defined in the policies of the IPCC^one,2 and the IPBES⁶². We found that (i) sea level rise, shifts in temperature and shifts in rainfall may not cause high absolute ExpPDloss at a global calibration (ii) notwithstanding, ExpPDloss on some vulnerable islands tends to be higher than if extinctions were random (iii) taxa found on vulnerable islands likely capture some deep and/or long phylogenetic branches. The expected pregnant loss of monocot PD on vulnerable islands is and then another warning that climate change will affect human well-being^63,64. The results of this report tin be used in two ways. First, they can serve as a guide to identify where to act in order to protect the tree of life. While we focused on monocots, other highly diverse insular groups with many endemic species, such as eudicots, would be worth investigated in order to elucidate to which extent these findings can be generalized. Our assay of islands worldwide provides a nautical chart indicating where to focus to avoid imminent losses. This shows the need of moving from global to local in order to monitor the status of the local populations subtending these evolutionary branches that are under threat, and study ways to avoid their extinctions. The second perspective concerns the synergistic effects of climate change with other threats impacting biodiversity⁶⁵. Even on islands not considered to exist vulnerable to climate change, other factors, especially human being-induced habitat losses and species invasions, may correspond an firsthand threat to their biodiversity^66,67. Future studies should consider the diversity of threats on island biodiversity, including biotic multipliers, and their interactions.

Methods

To assess the consequences of climate alter on isle phylogenetic diversity, we proceeded as follows:

ane.
We calculated the vulnerability of each isle to iii threats related to climate change depending on some island features
2.
Nosotros estimated how much phylogenetic diversity (PD) would be lost on a global scale when an island disappears. As the extent of the loss of PD depends on an island's genus richness, we also estimated whether these losses were significant or not, i.e. whether they were higher than by hazard solitary.
3.
Nosotros linked island vulnerability to loss of PD. In particular, we assessed how much PD would be lost when all islands in the same vulnerability category were removed and whether these losses were pregnant.

The three steps were repeated for all monocot genera occurring on islands and then simply for those genera that are restricted to islands, i.e., non observed on the mainland.

Data

Islands

Following previous studies^fifteen,56, nosotros divers an island as an area surrounded past h2o whose size is smaller than Australia and excluding islands within continents. Our island database was extracted from the Global Isle Database released by the United Nations Environment Program which has data on 180,495 islands from all over the earth⁶². We worked at the island but not archipelago calibration.

Phylogeny and establish occurrences

Nosotros used a monocot phylogeny that is well resolved at the genus level for the vast bulk of genera⁶⁸. Working at the genus level allowed us to accept into account taxa united by solid shared evolutionary history, materialized by shared traits which fabricated them successful on islands and which are therefore the object of frequent evolutionary and ecological research^69,lxx. Genera names from this phylogeny were matched with the accepted names found in the eMonocot database and used as a reference to cheque for the synonymy of plant occurrence names. eMonocot is built by an international consortium of botanists and aims to provide the most reliable information on monocot taxonomy and occurrence.

Constitute occurrence points were downloaded from the Global Biodiversity Information Facility portal (GBIF, GBIF.org (09 Feb 2017) GBIF Occurrence Download https://doi.org/10.15468/dl.kyylbs). Nosotros selected all "basisOfRecord" occurences comprised within the island polygon boundaries, defined in the Global Island Database (GID)⁶². We used the taxon name structure from eMonocot to account for possible synonymies in the GBIF dataset and attributed an accepted proper noun following the synonymy list in eMonocot for each record. Nosotros excluded all marine taxa.

We and so filtered out occurrences of species that are non native to island polygons using the eMonocot database which provides data on a species' "native" or "not-native" condition. To do so, we attributed a Taxonomic Databases Working Grouping polygon (TDWG; scale used in the eMonocot database⁷¹) to each island polygon used in our analysis⁶². All GBIF occurrences associated with a TDWG polygon and respective to a non-native species in the eMonocot database were excluded, which could sometimes atomic number 82 to the exclusion of a genus.

Notwithstanding, with this method we could not identify the condition of taxa with occurrences where information regarding the "native" or "not-native" status was missing in the eMonocot database. A second test was carried out for those species. For each, we delimited a polygon defined by the maximal and minimal latitudes and longitudes of their known native range. We and so excluded the occurrences of species constitute outside their corresponding polygon.

Crossing information from large databases - the GBIF, eMonocot, and GID⁶² databases – we compiled 2,550,396 occurrences representing 15,901 species from 1,497 genera on v,565 islands. Although this seems to exist a modest proportion of the initial sample (180,495 islands), suggesting that more sampling efforts are needed, this represents one of the largest dataset used for large scale conservation studies in islands. The use of eMonocot allowed reducing taxonomic and geo-localization errors and uncertainties, and therefore gave united states more confidence in the validity of our data compared to using GBIF alone⁷². Information technology also allowed to exclude not-native species, complete and correct a species' surface area of distribution, and check for synonymies.

Stride i - Assessing Island Vulnerability

Starting time, nosotros assessed the vulnerability to climatic change of the 5,565 islands harbouring native monocot species, past evaluating how they will be impacted past sea level rise, shifts in temperature, and shifts in rainfall. Vulnerability is a concept used to evaluate the potential impacts of climatic change on a system^61,60. The factors of vulnerability considered and the calculation of vulnerability scores are described below.

Factors of vulnerability

To estimate island vulnerability, we used a prepare of features that are expected to have a strong influence on the effects of climatic change on insular biodiversity (Fig. 7)^60,26,34. Vulnerability to the 3 threats mentioned above was estimated by because the post-obit factors:

Body of water Level Rising. Nosotros estimated the vulnerability to this threat using the values of ocean level rise predicted by the IPCC^ane and considering four island features: expanse, maximal elevation, mean elevation and circularity. The selection of these variables was based on the reasoning that a large area, loftier peak, and roundness (i.due east. smallest possible perimeter) increase the proportion of the island surface not affected by floods, erosion, and saltwater intrusion. This consequently reduces the possibility of sea level rise affecting the island's entire biota^26,27.
Shift in temperature. Nosotros assessed the vulnerability to shifts in temperature by calculating the difference between predicted and current hateful almanac temperature and between predicted and current temperature seasonality (defined equally the standard divergence of hateful monthly temperatures). We also considered that the vulnerability of an island to a shift in temperature will depend on expanse and topographic heterogeneity. Indeed, a big and topographically heterogeneous isle may comprise a wider range of climates and thus is more probable to maintain suitable climates in at least part of its territory.
Shift in rainfall. Nosotros assessed the vulnerability to shifts in rainfall by calculating the difference between predicted and electric current values of mean annual rainfall and the difference betwixt predicted and current rainfall seasonality. Nosotros as well considered factors related to area and topography, which are related to the likelihood of maintaining suitable climates (as with the vulnerability to shifts in temperature).

Current climatic variables were extracted from WorldClim version two.0⁵⁰. Predicted temperature, rainfall and body of water level rise values came from the IPCC^ane (provided by WorldClim version 1.4) and stand for climate projections from global climate models based on four concentration pathways of representative greenhouse gases. In order to determine which scenario(s) to use, we performed a series of preliminary tests to assess the impact of each scenario on estimates of isle vulnerability. Results indicated that islands were ranked similarly in their vulnerability to climate change under dissimilar scenarios. Although scenarios differed greatly in their estimates of sea level rise, temperature, and rainfall changes, they did non differ much regarding the spatial distribution of these changes (i.due east. regions expected to experience the nearly change were roughly the same). Nosotros therefore selected the scenario that considers two.half-dozen Watts per foursquare meter of cumulative emissions of human being greenhouse gases. This corresponds to the near optimistic scenario, where temperature rise remains beneath two °C in a higher place pre-industrial values¹, and is the proposed target of the Paris Agreement on Climatic change.

Elevation and area data were extracted from Weigelt et al.⁷³ and GID⁶² databases, respectively. Island circularity was estimated every bit the ratio between the squared perimeter and the surface area divided by 4π, with values ranging from 0 to i (a perfect circle having a value of ane).

Calculation of island vulnerability

We estimated the vulnerability of each isle to each threat, i.due east. sea level rise, shift in temperature and shift in rainfall. For each factor associated with a item threat related to climate change, islands were ranked according to the expected influence of that factor on island vulnerability (Fig. vii). We and so attributed a score between 1 (low rank) to 5 (high rank) to each isle depending on its position in the ranking. For each threat, each island was given iv or 5 scores (for shifts in temperature/rainfall and sea level rising respectively) (see above; Fig. vii). The vulnerability of an island to a threat is quantified every bit the hateful of these scores.

Stride 2 - Loss of Phylogenetic Diversity When Islands are Lost Independently

As a 2d stride, nosotros measured the amount and significance of global PD loss following the independent loss of islands, i.e. local extinction of all taxa on a given isle. The aim was to identify which islands would have the greatest impact on the tree of life if they were lost.

Measuring expected PD loss per island

Get-go, we estimated how much PD would be lost across the entire phylogeny of monocots if all genera occurring on a given island went extinct. To do so, we simulated the "loss" of an island, i.e. local extinction of all its taxa. We then estimated the probability of extinction for each genus on an isle as the expected proportion of the genus' global range lost if the island would disappear. Geographic range has been found to exist ane of the principal predictors of species extinction gamble, but presence-but data and the huge number of islands and species studied here did not allow assessing individual species range size. Yet, changes in the number of localities where a species occurs is also an essential factor of extinction chance and is used in the criteria B of the IUCN Red List threat status. In our analysis, species range was therefore measured as the number of islands a genus occurs on. This posits that each island equally contributes to a genus' survival and, therefore probabilities of extinction are given by the proportion of native islands from which a genus disappears. Following Religion³⁹, each branch of the phylogenetic tree was weighted by the product of the extinction probabilities of all its descendants, i.e. equal to the proportion of the range lost for each genera establish on the "lost" island and equal to 0 for all other genera. The branches supporting genera which had not lost any proportion of their range were considered rubber (probability of extinction equal to 0). Nosotros calculated the expected loss of insular PD following the loss of a given island as the sum of weighted branch lengths (³⁹; Eq. 1). This measure estimates how much PD is expected to be lost on a global calibration following local extinctions on a given island. It also allows us to consider the phylogenetic complementarity of extinction risks, i.e. the shared responsibility of taxa to safeguard deep branches³⁹.

$$ExpPDloss(tree,\,proba)=\sum _{b}{50}_{b}\,\prod _{{k}_{b}}{p}_{{grand}_{b}}$$

(1)

where k _b designates the k ^th descendant of branch b on the tree, p _kb is the extinction probability of the 1000 ^th descendant of branch b, and L_b is the length of co-operative b ³⁹.

Nosotros ran this analysis for every native insular found genera. Using this measure out, the probability of extinction of a taxon was related to the number of islands it was found on independently of its potential occurrence on continents. Here, ExpPDloss has to be interpreted equally the impact of isle disappearance on monocot PD across islands but not on monocot PD worldwide (representatives of these genera may survive on continents). To complement this measure, we estimated ExpPDloss from a pruned tree comprising merely genera that are endemic to islands, i.e. those establish on a single or in several islands merely not on the mainland (96 genera from 72 islands). This represents the PD at risk of irreversible loss, because these genera will not survive anywhere else if the islands where they live are lost. Finally, to correct for low sampling on some islands, we corrected ExpPDloss using the predicted genus richness for each island as described in Supplementary method S1.

Measuring the significance of ExpPDloss per island

Every bit absolute ExpPDloss may be correlated with genus richness on an island, nosotros tested whether loss of establish PD on each island was higher than expected by chance. To do then, we randomized genera between islands but kept the genus richness of each island and the range of each genus (i.east. the number of islands a genus is present on). For each island and randomization, we calculated the new ExpPDloss when that island is lost. Simulations were run one thousand times. For each isle, we then calculated the frequency at which the observed ExpPDloss was higher than the 1000 ExpPDloss values calculated from simulations (p-values_ind; unilateral examination). This procedure immune removing the dependency of ExpPDloss on genus richness while retaining the structure of the data. Expected PD losses from the original information were considered highly, moderately or slightly pregnant when they fell into the highest 0.ane%, i% and v% of the distribution values obtained from simulations, respectively.

To identify areas where range-restricted and/or evolutionarily distinct genera co-occur, nosotros likewise estimated for each island the expected loss of species richness (ExpSRloss) and the expected loss of species richness in the near evolutionarily distinct species (ExpSRloss _ED ⁷⁴). We calculated absolute values and their significance. Results were often similar to those of ExpPDloss and are described in Supplementary method S2.

Pace 3 - Linking Expected PD Loss to the Vulnerability of Islands

Absolute value and significance of ExpPDloss per isle in relation to island vulnerability

The third step of the analysis was to link island vulnerability (step i) to the expected loss of PD (step 2). We commencement estimated the absolute ExpPDloss per island per category of vulnerability. Due to the high number of vulnerability scores we defined 4 categories of vulnerability: low (1 ≤ vulnerability score < two), moderate (two ≤ vulnerability score < iii), high (3 ≤ vulnerability score < iv) and very high vulnerability (4 ≤ vulnerability score ≤ 5). From this nosotros identified the islands and the categories of vulnerability where ExpPDloss would be the highest.

Second, we linked the significance of ExpPDloss when islands were lost independently to the category of vulnerability they belonged to. We calculated the distribution of p-values_ind (i.eastward. the departure from the null model described above) and the median p-value_ind per vulnerability category. We identified in this way the categories where significant ExpPDloss was near frequent.

Expected loss of PD when all islands with a similar vulnerability to climate change are lost

As a 2d approach to link isle vulnerability to loss of PD, we tested whether loss of all islands assigned to a given vulnerability category would atomic number 82 to college ExpPDloss than at random (p_values_all). This differs from the previous analyses which considered the independent loss of islands (p_values_ind).

Here we calculated extinction probabilities for each genus as the proportion of their range that would be lost if all islands with a similar vulnerability to climate change disappeared (in step 1 the extinction probability was measured as the proportion of a genus range lost when a unmarried island disappeared). To explore this question, we defined the "range" of a genus as the number of vulnerability categories of the islands on which information technology occurs. For example, if a genus occurs but on highly vulnerable islands, its extinction probability would be 1 if all these islands were lost. The extinction probability of a genus occurring on islands from three categories (e.g. very loftier, high, and moderate vulnerability) would be i/iii under a similar scenario. We and then calculated the phylogenetic bespeak of extinction probabilities for each category of vulnerability and each type of threat using Pagel's λ⁷⁵ and Abouheif'southward⁷⁶ statistical tests. These tests assume to reflect phylogenetic point in a Brownian movement model of evolution and are robust when polytomies are present, which is the case hither^77,78.

We and so compared ExpPDloss when all genera found on islands belonging to a given category of vulnerability were lost to ExpPDloss when genera were distributed randomly amidst categories of vulnerability. In this randomization process, the number of genera per category of vulnerability and the number of categories of vulnerability a genus belonged to were retained. This process was run 1000 times and we calculated whether the frequency of the observed ExpPDloss per vulnerability category was college than by chance (p_values_all). This approach was like to the one used in footstep 2 but here genera were randomized betwixt categories of vulnerability instead of between islands as distinct units. To business relationship for evolutionary distinctiveness and range-restriction, nosotros as well performed a similar analysis for ExpSRloss and ExpSRloss _ED (Supplementary method S2). Moreover, all analyses described above were conducted on all genera occurring on islands and then just on genera restricted to islands.

Data Availability

Data will be made available following acceptance

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Acknowledgements

This piece of work was supported by French state funds managed by the French National Enquiry Bureau within the Investissements d'Avenir plan under reference ANR-11-IDEX-0004-02. Nosotros are grateful to Dan Religion for his helpful advice on an earlier version of the manuscript.

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Writer notes

Thomas Haevermans and Roseli Pellens jointly supervised this work.

Affiliations

Institut de Systématique, Development, Biodiversité (ISYEB UMR7205), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, CP 51, 57 rue Cuvier, 75005, Paris, France

Simon Veron, Thomas Haevermans & Roseli Pellens
Middle d'Ecologie et des Sciences de la Conservation (CESCO UMR7204) MNHN, CNRS, Sorbonne Université - CP135, 43 rue Buffon, 75005, Paris, France

Simon Veron & Maud Mouchet
Purple Botanic Gardens, Kew, Richmond, Surrey, TW9 3AE, UK

Rafaël Govaerts

Contributions

R.P., T.H., 1000.M. and S.V. conceived the project. S.Five., R.P., T.H., Thou.M. designed this study and wrote the article. SV, RG and Thursday nerveless data. R.P., T.H. and One thousand.M. obtained the fiscal support. All authors reviewed the manuscript. R.P. and T.H. are co-senior authors.

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Correspondence to Simon Veron.

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Veron, S., Mouchet, M., Govaerts, R. et al. Vulnerability to climate change of islands worldwide and its touch on the tree of life. Sci Rep 9, 14471 (2019). https://doi.org/10.1038/s41598-019-51107-x

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Received: 27 November 2018
Accepted: 25 September 2019
Published: 09 October 2019
DOI : https://doi.org/10.1038/s41598-019-51107-x

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