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All experimental procedures were approved by the University of Toronto animal care committee (Animal Use Protocol number 20012112) and conformed to guidelines prescribed by the Canadian Council on Animal Care.
Animal capture and husbandry
Wild male ruby-throated hummingbirds (Archilochus colubris; (n = 23); mass range during experimental period: 2.59 g to 4.52 g), were caught on the University of Toronto Scarborough Campus (({43.7838}^{circ }hbox {N}), ({79.1875}^{circ }hbox {W})) or the University of Western Ontario campus (({43.0096}^{circ }hbox {N}), ({81.2737}^{circ }hbox {W})) using box traps modified with hook-and-loop fastener tape on a drop door containing hummingbird feeders. Birds were trapped between 06:00 h and 12:00 h during the months of May through September of 2017, 2018, and 2019. Pilot trials were conducted in 03/2018. Birds in the pilot study were on wintering/migratory seasonality with a 12 h daylight schedule. Subsequent trials were conducted between 04/2019 and 01/2020. In 04/2019, birds were under breeding seasonality (14 h daylight) and in 01/2020, birds were under wintering/migratory seasonality (12 h daylight) during experimental trials. The daylight schedule approximated the photoperiod encountered as part of annual migrations to Central America and back. Upon capture, hummingbirds were quickly transported to metal EuroCages (({50.8 times 91.5 times 53.7},hbox {cm}) ((hbox {L}times hbox {W}times hbox {H}))) at the animal care facility where they were housed individually and acclimated to feed from syringe feeders. Birds were provided an 18 % (w/v) Nektar Plus (Guenter Enderle, Tarpon Springs, FL, USA) solution (henceforth referred to as maintenance diet), which was consumed ad libitum, and syringes were replaced daily (range of average consumption of daily maintenance diet during study period was 5.4 mL13.2 mL).
Experimental design
Birds drank solutions of imidacloprid (IMI; Sigma-Aldrich Cat. No. 37894) dissolved in a 20% w/v sucrose solution and were randomly assigned to either control (({0.0},upmu hbox {g g}^{-1}cdot)BW), low (({1.0}upmu hbox {g g}^{-1})), middle (({2.0}upmu hbox {g g}^{-1})), or high dose (({2.5}upmu hbox {g g}^{-1})) groups (n = 7, 4, 8, 4, respectively). Stock solution concentrations were analytically confirmed (low: ({0.32},hbox {gL}^{-1}), middle: ({0.59},hbox {gL}^{-1}), high: ({0.78},hbox {gL}^{-1})) such that a 3 g bird dosed with ({10},upmu hbox {L}) of solution would receive the dosage rate corresponding to either the low, middle or high dose. The volume of imidacloprid stock solution used for dosage was adjusted on a body weight (BW) basis, pipetting from the stock solution into a new nectar syringe and drawing up to a final volume of ({50},upmu hbox {L}) with 20% w/v sucrose solution, ensuring that birds received the same dosage rate throughout the trial. Birds were deprived of their regular nectar solution for 10 min to 15 min consumed the entire small-volume dosing solution within 10 min of being offered the solution. The dose was considered to be delivered when there was no visible solution remaining in the transparent syringe.
Doses were established within a range spanning expected exposure in a bird drinking ({10},hbox {mLd}^{-1}) from contaminated flowers10 up to 10 % of the LD50 in canaries61 (Serinus canaria, LD50: ({25},upmu hbox {g g}^{-1}) to 50 (upmu hbox {g g}^{-1})), similarly small birds with fast metabolic rates to target a sub-lethal concentration expected to produce toxic effects32. When energy demands are high, hummingbirds may consume over three times their body weight in nectar63, therefore ({10},hbox {mLd}^{-1}) is a probable figure for contaminated nectar consumption. Pooled blueberry flower samples collected about 1 year after treatment with imidacloprid contained the neonicotinoids at a concentration of ({5.16},hbox {ng g}^{-1})10. We extrapolated our very low and low dose concentrations based on these data. We stipulate that given the flower sample is a pooled sample, it was collected from flowers long after treatment, and there are different regulations on pesticide use within the ruby-throated hummingbird’s range, these doses were environmentally relevant.
We tested multiple intermediate doses which allowed us to explore dose-response relationships in observed effects64. Pilot experiment data with control, very low (({0.2},upmu hbox {g g}^{-1})), or high dose (({2.5},upmu hbox {g g}^{-1})) (n = 3 per group) are included for cholinesterase activity and toxicokinetic elimination analyses. Other metrics including behaviour and energy expenditure were not included from the pilot study due to differences in data collection protocols and are not strictly comparable. Behavioural data collection, cloacal fluid (CF) collection, and respirometry occurred over 6 days, where pre-dose data were collected for each animal on days 1 through 3, and dosing occurred once per day at 11:00 on days 4 through 6. Body weight measurements were taken daily at 10:00. The body weights of birds on the first day of experimentation ranged from 2.70 g to 4.52 g. For simplicity, 11:00 on days 1-6 is referred to as Dose Time (DT). Terminal sampling and tissue collection occurred 24 h after the third dose was administered. Birds were sacrificed by decapitation following isoflurane overdose, and whole blood, flight muscle, liver, brain, and heart tissues were rapidly excised, flash frozen in liquid nitrogen, and stored at ({-80},^{circ }hbox {C}) until downstream analysis, except in the case of blood which was immediately used for blood smear preparation.
Figure 3

Daily experimental timeline for days 1 through 6 of trials where on days 1 through 3, a control solution (20% w/v sucrose solution) is given in all groups and on days 4 through 6, dosing solutions were administered. Times of data collection are shown relative to Dose Time (DT). Terminal tissue sampling occurred on day 7 at DT, 24 h after the final dose was administered.

Full size image

Respirometry
Oxygen consumption and carbon dioxide production rates were measured using open-flow chamber respirometry65. Airflow through three metabolic chambers and one empty reference chamber was maintained at a rate of ({300},hbox {mL min}^{-1}). Excurrent air from the chambers was sub-sampled at ({100},hbox {mL min}^{-1}) sequentially starting with the reference chamber at using a Turbofox-5 (Sable Systems International Las Vegas, NV, USA). Sub-sampled air was passed through a water vapour pressure analyzer, a drying column (Indicating Drierite, W.A. Hammond Drierite, Xenia, Ohio, USA), carbon dioxide meter, and finally an oxygen analyzer (Turbofox-5, Sable Systems International). The oxygen and carbon dioxide analyzers were calibrated according to manufacturer instructions using well-mixed ambient air for the oxygen analyzer, and zero and (0.25 ,%hbox {CO}_{2}) reference gases for the (hbox {CO}_2) analyzer. Respirometry data were recorded at a frequency of 1 Hz using Expedata software (v. 1.84, Sable Systems) for 5 min while sampling from the empty reference chamber, followed by three 7 min recording periods from each of the chambers holding a bird. After this 26 min period, sub-sampling was resumed from the reference chamber for another 5 min followed by another 7 min sub-sampling period from experimental chambers. A final 5 min sampling of the reference chamber concluded the respirometry data collection, and birds were returned to the cloacal fluid collection chambers approximately 60 min after initially being placed in respirometry chambers.
Behavioural data collection and processing
Video recordings of birds were collected for 2 h, starting 4 h after DT (15:00–17:00). At the start of the recording period, birds were returned to their home cages where they could feed ad libitum by hovering and tracking a syringe on a 10 cm arm oscillating through a ({90}^{circ }) range along a lateral arc at a speed of 15 RPM. Video recordings were analyzed for time spent in flight, subdivided into foraging and non-foraging flights. Foraging flights were defined as flights where the bird contacted the hover feeder with their bill. Total consumption of the maintenance diet over this 2 h period was recorded.
Heterophil/lymphocyte ratios
Approximately ({2},upmu hbox {L}) of blood was collected for blood smear preparation immediately following sacrifice. After smearing, slides were left to air dry for a minimum of 3 h before fixing with 100 % methanol and staining with Giemsa–Wright solution (Fisher Scientific Cat. No. 123869). Slides were stained by immersion in eosinophilic dye (5times 1,hbox {s}) followed by (5times {1},hbox {s}) in basophilic dye.
Cholinesterase activity assay
Brain and muscle tissues were homogenized using a sonic dismembrator ((hbox {Fisherbrand}^{mathrm{TM}}) Model 120 Sonic Dismembrator) 1:10 w:v with ice-cold 0.1 M potassium phosphate buffer (pH 7.2). Samples were centrifuged at 10,000 RPM in a Beckman Coulter microfuge 22R centrifuge held at ({4},^{circ }hbox {C}) for 5 min. Total protein concentrations in tissue homogenates were determined by the Bradford assay (Sigma-Aldrich Cat. No. B6916). Cholinesterase activity was measured by the Ellman method adapted for a microplate reader (BioTek Synergy HT)66. Optimal assay conditions were 0.1 M potassium phosphate buffer (pH 7.2), 0.48 mM acetylcholine, 0.64 mM DTNB (Sigma-Aldrich Cat. No. D8130), 1.1 mM sodium bicarbonate. Assays were initiated through the addition of acetylcholine (Sigma-Aldrich, Cat. No. 01480) in a total volume of ({300},upmu hbox {L}). Absorbance was read at 412 nm every 2.5 min for 10 min.
Cloacal fluid
Collection
Cloacal fluid was collected for 1 h at 3 time points each day according to one of two schedules: starting (1) 1 h, 6 h, and 23 h, or (2) 2.5 h, 6.5 h, and 23 h after DT. Cloacal fluid was collected according to schedule (1) in pilot experiments, and (2) in the subsequent trials. A watch glass was placed beneath birds perching in 10 cm W (times) 12 cm H glass cylinder enclosures stopped with 19-gauge galvanized 1 cm hardware mesh openings in order to obtain cloacal fluid. To encourage greater cloacal fluid production, and to simulate the regular feeding behaviour of wild birds, individuals fed ad libitum from a syringe containing a 20% (w/v) sucrose solutions every 5 min to 10 min for the duration of cloacal fluid collection, which took place over 1 h as described under Sect. 4.2. After the collection period, cloacal fluid samples were stored at ({-20},^{circ }hbox {C}) until pooling and refreezing prior to chemical analysis.
Chemical analyses
Cloacal fluid samples and dosing solutions were analyzed for IMI by HPLC-ESI-MS/MS by Laboratory Services, NWRC (National Wildlife Research Centre, Ottawa, ON, Canada). Cloacal fluid samples were pooled by time point across dosing days by individual to reach the necessary minimum volume of ({100},upmu hbox {L}).
Cloacal fluid sample pools from 2018 trials were thawed at room temperature. Each pool was diluted 4 (times) with DI water (({25},upmu hbox {L}) cloacal fluid + ({75},upmu hbox {L}) DI water). The resulting ({100},upmu hbox {L}) diluted samples were then spiked with ({100},upmu hbox {L}) of internal standard (IS) solution. Spiked samples were filtered directly into ({300},upmu hbox {L}) glass inserts using 4 mm PVDF ({0.45},upmu text {m}) Millex filters and ({50},upmu hbox {L}) aliquots were injected. For the 2018 analyses, the minimum detection limit (MDL) and minimum reporting limit (MRL) were ({0.204},hbox {ng}hbox { mL}^{-1}) and ({0.616},hbox {ng}hbox { mL}^{-1}) respectively.
Cloacal fluid sample pools from 2019 trials were thawed at room temperature and ({50},upmu hbox {L}) of IS solution was added to (200,upmu text {L}) of pooled cloacal fluid. In cases where the sample volume was too small, volumes were adjusted: ({100},upmu hbox {L}) cloacal fluid + ({25},upmu hbox {L}) IS or ({80},upmu hbox {L}) cloacal fluid + ({20},upmu hbox {L}) IS as required. In these cases, duplicate injections of ({50},upmu hbox {L}) were not possible. All samples were filtered with 4 mm PVDF ({0.45},upmu text {m}) Millex filters prior to injection. For the 2019 analysis, the MDL and MRL were ({0.051},hbox {ng}hbox { mL}^{-1}) and ({0.154},hbox {ng}hbox { mL}^{-1}) respectively.
Cloacal fluid sample pools and dosing solutions were analyzed according to modifications to the methods of Main et al.9. Briefly, IMI in a cloacal fluid or DI water matrix was quantified by the internal standard method using the API5000 Triple Quadropole Mass Spectrometer (AB Sciex) and the TurboSpray ion source in positive polarity. The calibration curve was constructed from 8 concentrations ranging from ({0.1},hbox {ng}hbox { mL}^{-1}) to ({20},hbox {ng}hbox { mL}^{-1}) yielding an R greater than 0.995 (linear regression, no weighting). Injection cross-contamination was monitored by injecting solvent blanks (water:acetonitrile 80:20) before and after each set of samples. Contamination was also monitored by using a DI water sample blank spiked at ({20},hbox {ng}hbox { mL}^{-1}) IMI. In all cases, no IMI above MDLs was detected. Method precision was evaluated by duplicate injections and/or duplicate dilutions: the RPDs (relative percent differences) were all less than 15 %, demonstrating good method precision. Method accuracy was evaluated by analyzing a ({20},hbox {ng}hbox { mL}^{-1}) QC spike per set: the recoveries ranged between 96 % and 106 %, demonstrating good method accuracy.
Statistical analyses
All statistical analyses were conducted in R version 3.5.267. Birds exhibiting weight loss outside the lower bound of the 95 % confidence interval (CI) of 20 % over the study period ((n=3)) were omitted and data were reanalyzed. Birds exhibiting extreme weight loss across the pre-dose and post-dose conditions were in the control group ((n=2)) and the low dose group ((n=1)) suggesting a adverse response to the experimental period rather than the treatment itself. Data are presented as mean ± standard error. Significance ((p More

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Selection of species
The list of species for the vulnerability assessment was based on five different criteria. First, we considered the proportion of each species in the total Portuguese landings between 1989 and 2015, using public landings data from the Direção Geral dos Recursos Marinhos de Portugal (DGRM). The most landed species, accounting for 95% of purse seine, 70% of trawling and 70% of the multigear landings, were included. This selection was carried out separately for each combination of gear and region (Supplementary Table SI1-1). Second, species were chosen in regards of their economic relevance, considering the species representing more than 3% of the total economic revenue of the marine landings within each combination of region and gear (DGRM, Supplementary Table SI1-2). Third, we included the most frequent species in the discards of Portuguese fisheries, according to the work of Leitão et al.42, where the top-ten discarded species per métier are listed (Supplementary Table SI1-3). Fourth, we included the species of importance for the canning industry, obtained by means of a survey covering the main can enterprises of Portugal (Supplementary Table SI1-5). Fifth, a selection of the species of relevance for the Moroccan fisheries sector was carried out, using the reports from the Department of Marine Fisheries of the Kingdom of Morocco43 and the FAO software FishStatJ (most captured species between 2007 and 201744) (Supplementary Table SI1-6). Additionally, due to their importance for specific fleet segments, we included some shark species of interest that were not included by the previous criteria. The selection of shark species was based on reports from the Instituto Português do Mar e as Pescas (IPMA) and included: Galeus melastomus, Prionace glauca, Squalus acanthias, Scyliorhinus canicula, and Hexanchus griseus. Some riverine species were finally removed from the list (Petromyzon marinus, Salmo trutta), as well as cod (Gadus morhua), since it is not captured within the area of study. Finally, some extra species were pointed out by experts during the evaluation process as species with economic interest (Pollicipes pollicipes) or with potential distribution shift into/from the area of study in the context of climate change such as the bivalves Callista chione and Ruditapes philippinarum, and the crabs Callinectes sapidus and Carcinus maenas. The final list of species considered, and their functional group are shown in Table 1.
Table 1 Species and functional groups considered during the climate change vulnerability assessment.
Full size table

Environmental change
RCP (representative concentration pathway) scenarios of atmospheric greenhouse gas concentration have been proposed by the IPCC for use in research to project the evolution of environmental variables. Using scenarios RCP 4.5 and RCP 8.5 (predicting a global warming of 1.8 and 3.7 °C respectively by the end of the twenty-first century) as forcing, the POLCOMS-ERSEM model45 forecasted a wide array of physical, chemical and biological variables for the Northeast Atlantic and adjacent seas at a resolution of 0.1 degree (approximately 11 km). For the evaluation of the vulnerability of the species of interest, a selection of the most cited variables with impact on the ecology of marine organisms in the Portuguese marine environment was carried out (e.g. Refs.7,8,9). As a result, these variables were finally considered: sea surface temperature (SST, °C), surface pH, surface salinity (psu), surface zooplankton biomass (mol m−3), surface phytoplankton biomass (mol m−3), surface northward and eastward current velocities (m s−1) and river discharge (m−3 year−1). The zooplankton and phytoplankton biomass were summed to obtain an overall plankton biomass (mol m−3) which was finally used in the assessment of vulnerability. Surface variables were calculated using the top sigma layer of the outputs of the model.
Two time slices of the POLCOMS-ERSEM outputs were used to define two periods for comparison. The first was between 2000 and 2019 setting a reference point for the state of the environment at the beginning of the century (hereafter “reference”), then, the period between 2040 and 2059 served to define the likely state of the environment in the near future (hereafter “future”). Defining the future and reference periods allowed us to compare the expected degree of change of the environmental variables between both periods. To do this on a regional basis, we considered the outputs of the model for each region of Portugal (North, Centre, and South; Fig. 1) and calculated a dimensionless variation index (VI) using the mean of each variable during the reference and future periods, and the standard deviation of the reference period:

$$ {text{VI}} = frac{{left( {mu ,future – mu ,reference} right)}}{sigma ,reference} , $$
(1)

where µ future and µ reference represent the regional average values of the corresponding time slice of the variable, and σ reference is the standard deviation of the regional values in the reference time slice (except for the variable river discharge, for which the average and standard deviation are calculated on a temporal basis) VI takes theoretical values between 0 (when there is no variation between future and reference) and ± infinite (when reference shows no variation all over the region of study). VI was used to weight the influence of each variable in the assessment of the exposure of the species to climate change n Table 2. The idea was to capture the degree of variability of each physical variable, so species exposed to the most variable environmental conditions would be more exposed to the effects of climate change. Then, a weight factor was calculated normalizing between 1 and 2 the absolute values of the VI defined above (“weight factor 1” in Table 2).
Table 2 Expected physical variability between 2000–2019 (reference) and 2040–2059 (future) according to POLCOMS-ERSEM physical-biogeochemical model. Outputs are shown considering three regions of Portugal (North, Centre, South) and two scenarios of climate change (RCP 4.5 and RCP 8.5). Weight factor 1 captures the degree of variability of the physical variables (see “Methods”). Weight factor 2 represents the likely impact on the physiology of the marine organisms and was obtained from the experts’ criteria. The final weight factor, used in the vulnerability assessment, is the average between weight factor 1 and 2.
Full size table

Since two versions of the future period were available (climate change scenarios RCP 4.5 and RCP 8.5), the level of exposure to changing environmental variables was calculated separately for both climate change scenarios, making it possible to estimate the overall vulnerability of the species under each scenario separately.
Beyond the degree of variability of each variable, a panel of experts on the ecology of marine organisms of Portugal was asked to rank, according to the likely impact on the physiology of marine organisms, the physical variables under consideration. Each expert was asked to order the variables independently, but a consensus answer was finally asked from them. The ranking of the physical variables was posteriorly transformed numerically between 1 and 2, being 1 the less relevant variable and 2 the most relevant variable. Intermediate variables got a value between 1 and 2 following equally distanced steps (see “weight factor 2” in Table 2). The final weight given to each physical variable during the vulnerability assessment was calculated as the average between weight factors 1 and 2 (“final weight factor” in Table 2). It was possible to estimate this parameter for all the exposure indicators with exception of the extreme events frequency, which was not included in the POLCOMS-ERSEM outputs. The likely evolution of this parameter is controversial and thus, a final weight factor of 1 was assigned by consensus with the panel of experts. In the case of oceanic currents, considered as a proxy for upwelling, we considered eastward currents in the North and Centre regions (North–South oriented coast) and northward currents in the South region (East–West oriented coast).
Vulnerability assessment
Indicators
The vulnerability of the species to climate change was evaluated following the conceptual framework described in the 4th Assessment Report of the IPCC29. This approach assumes that the vulnerability (V) of species to environmental change is a function of: (1) their exposure (E) to the changing environmental variables (defined as the overlap between the expected geographic range of change of the variables and the area/habitats of occurrence of a given species), (2) their sensitivity (S) to environmental change (considered as the degree to a which extent a given species will be affected—in terms of population dynamics or life-history traits—by a change in the environment), and (3) their adaptive capacity (AC) to environmental change (understood as the mechanisms of a given species to resist to a specific change of the environment and recover to the state prior to the perturbation).
For each species, the degree of exposure, sensitivity and adaptive capacity was evaluated considering different aspects (hereafter “indicators”) of its biology, ecology, and exploitation (see Supplementary SI2 for a description of the indicators). The selection of the indicators was made considering the context of climate change in the Portuguese marine environment. Hence, for the level of exposure, the most referenced environmental variables with impact on the ecology of the species of interest were chosen. For the analysis of the sensitivity, a selection of life history traits driving the relationship between the species’ population dynamics and the environment was carried out based on existing literature (e.g. Refs.23,26,28,36). The traits finally considered were: trophic level, fecundity, number of reproductive events in a lifetime, egg spawning strategy, individual growth parameters (growth coefficient, k, in Von Bertalanffy’s growth function), age at maturity, longevity, intrinsic population growth rate (r), sexual strategy (gonochorism, hermaphroditism or protogyny/protandry), length of the spawning seasons, planktonic larval duration (PLD), latitudinal range of distribution, temperature range of distribution, adult mobility, seasonal migrations, sociability, and complexity of the reproductive strategy. The adaptive capacity of the species was analysed considering different aspects related to the degree of conservation or exploitation of the species and the kind of fisheries associated, which give an idea of the capacity of response of the populations to environmental change at a national or regional scale. In this case we considered: the ICES stock status (referred to Portuguese or Iberian stocks when available), the general replenishment potential of the species, related to different life-history parameters such as growth and reproduction, the vulnerability degree assigned by the IUCN, the specific vulnerability to fisheries assessed in Cheung et al.26, and the fishing pressure suffered by each species in Portuguese waters.
Expert’s assessment
To evaluate each species from the point of view of each indicator, a fuzzy logic expert-judgement method was applied26. This method consists of categorizing the range of possible answers or values of each indicator into three levels (bins) corresponding to low, moderate, or high levels of exposure, sensitivity and adaptive capacity, respectively. The number of levels considered (3) has been found to be sufficient for this kind of study28,46, and their ranges were defined for each indicator following the existing literature, adjusting their values to the reality of the Portuguese marine environment. For a description of the levels within each indicator see Supplementary SI2.
Assigning each species to each bin of each indicator was carried by a group of experts in marine biology and ecology with experience in the Portuguese marine environment. A variable number of species was assigned to each expert in regards of their field of knowledge and previous experience. Each species received a minimum of three experts and a maximum of four. The number of tallies assigned to each bin of each indicator (variable between 0 and 5) represented the degree of confidence in the answer. In this way, an absolute confidence in the answer provided was represented by allocating 5 tallies in the corresponding bin, while spreading the five tallies among the three bins meant the highest level of uncertainty. In order to avoid biases in the expert evaluations, each expert was provided with the description of the indicators and their bins found in Supplementary SI2, the maps of climate variability found in Supplementary SI3, and a list of online resources to consult. The experts were allowed to consult any other scientific literature for their evaluations if needed.
After the evaluation of each indicator of exposure, sensitivity and adaptive capacity, each expert was asked to provide a formed opinion on the likely direction of the effects of climate change for each species. This directional effect (DE) evaluation had two steps: (1) the allocation of five tallies among three bins representing negative, neutral, or positive DE, and (2) providing a short rationale text explaining the allocation of tallies among the bins.
Experts were also asked to score the quality of the data used to distribute the tallies among the bins of each indicator following the methodology of Hare et al.23. In this case, the experts should assign a value between 0 and 3 to describe the quality of the information. These values correspond to (0) No Data. No information is available to provide an opinion; (1) Expert Judgement. The distribution of tallies among the bins reflects the expert judgement, based on knowledge of the general ecology of the species and its role on the ecosystem; (2) Limited Data. The data used to distribute the tallies may come from similar species or from other geographic regions out of the Iberian Peninsula; (3) Adequate Data. The score is based on data observed, modelled or directly measured for the species in question and is provided by scientific work carried out in the Iberian Peninsula.
After the individual assessments, a 2-day workshop was carried out where the experts were asked to discuss their evaluations and provide a summarizing text on the likely sign of directional effects of climate change on each species. They were also allowed to modify the distribution of tallies of their votes for the directional effects after the discussion.
Regional evaluation
Each expert was asked to perform the evaluation of each indicator independently for each region of Portugal (North, Centre and South; Fig. 1). This procedure made it possible to obtain, for a given species, region-specific assessments of E, S, AC and DE, which could be finally translated into region-specific overall vulnerability assessments.
Calculation of the overall vulnerability score
For each species, the number of tallies assigned by the experts to each bin of each indicator was averaged. Then, each tally was assigned a different value in regards of the bin where it was assigned: 1-low, 2-moderate, 3-high, making possible to calculate the value of each indicator by summing the value of the tallies. The final score of the indicator (minimum: 5; maximum: 15) was standardized between 0 and 1. To obtain the value of each dimension of the vulnerability (E, S, or AC) the sum of the values of the related indicators standardized between 0 and 1 was computed. All the indicators had the same weight.
Finally, to calculate the overall vulnerability, the value of each dimension was standardized between 0 and 1, being V calculated as:

$$ {text{V}}_{{{text{r}} – {text{cc}}}} = , left( {{text{E}}_{{{text{r}} – {text{cc}}}} + {text{ S}}_{{text{r}}} } right) , {-}{text{ Ac}}_{{text{r}}} , $$
(2)

where subscripts indicate region (r) and climate change (cc) specificity, respectively.
The vulnerability score (Vr-cc) obtained was finally categorized as: “very low vulnerability” (Vr-cc  More