Effects of climate change on the distribution of plant species and plant functional strategies on the Canary Islands

Aim

Oceanic islands possess unique floras with high proportions of endemic species. Island floras are expected to be severely affected by changing climatic conditions as species on islands have limited distribution ranges and small population sizes and face the constraints of insularity to track their climatic niches. We aimed to assess how ongoing climate change affects the range sizes of oceanic island plants, identifying species of particular conservation concern.

Location

Canary Islands, Spain.

Methods

We combined species occurrence data from single-island endemic, archipelago endemic and nonendemic native plant species of the Canary Islands with data on current and future climatic conditions. Bayesian Additive Regression Trees were used to assess the effect of climate change on species distributions; 71% (n = 502 species) of the native Canary Island species had models deemed good enough. To further assess how climate change affects plant functional strategies, we collected data on woodiness and succulence.

Results

Single-island endemic species were projected to lose a greater proportion of their climatically suitable area (x ̃ = −0.36) than archipelago endemics (x ̃ = −0.28) or nonendemic native species (x ̃ = −0.26), especially on Lanzarote and Fuerteventura, which are expected to experience less annual precipitation in the future. Moreover, herbaceous single-island endemics were projected to gain less and lose more climatically suitable area than insular woody single-island endemics. By contrast, we found that succulent single-island endemics and nonendemic natives gain more and lose less climatically suitable area.

Main Conclusions

While all native species are of conservation importance, we emphasise single-island endemic species not characterised by functional strategies associated with water use efficiency. Our results are particularly critical for other oceanic island floras that are not constituted by such a vast diversity of insular woody species as the Canary Islands.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Forecasting climate-driven habitat changes for Australian freshwater fishes

Aims

Climate change is expected to have profound effects on species' distributions into the future. Freshwater fishes, an important component of freshwater ecosystems, are no exception. Here, we project shifts in suitable conditions for Australian freshwater fishes under different climate change scenarios to identify species that may experience significant declines in habitat suitability.

Location

Australia.

Methods

We use MAXENT bioclimatic models to estimate the effect of climate change on the suitable conditions for 154 species of Australian freshwater fishes, of which 109 are endemic and 29 are threatened with extinction. Suitable conditions for freshwater fish species are modelled using three different Earth System climate models (ESMs) under two different emission scenarios to the year 2100. For each species, we examine potential geographic shifts in the distribution of suitable conditions from the present day to 2100 and quantify how habitat suitability may change at currently occupied sites by the end of this century.

Results

Broadscale poleward shifts in suitable conditions are projected for Australian freshwater fishes by an average of up to 0.38° (~180 km) across all species, depending on the emission scenario. Considerable loss of suitable conditions is forecast to occur within currently recognized distributional extents by 2100, with a mean projected loss of up to 17.5% across species. Predicted geographic range shifts and declines are larger under a high-emission scenario. Threatened species are projected to be more adversely affected than nonthreatened species.

Main Conclusions

Our models identify species and geographic regions that may be vulnerable to climate change, enabling freshwater fish conservation into the future.     

Warming drives poleward range contractions of Beringian endemic plant species at high latitudes

Aim

Species are expected to disperse poleward in response to climate change. For species that are endemic to the high latitudes, this implies that many in the future would face a “no-where-to-go” situation as they are currently occupying the northernmost portion of the continent. Further, because endemism may arise from a combination of physical barriers, climate and geological history, the persistence of many species may require spatial matching of multiple environmental factors within a limited dispersal space. Thus, it is not clear how endemic species might spatially adjust their distributions in response to climate change and whether there are future climate change refugia for these species.

Location

Northwest North America.

Taxa

Plants.

Time Period

Current and the future (2040).

Methods

We used ensemble bioclimatic models to evaluate drivers and directional patterns of future change in the distributions of 66 North American Beringian and amphi-Beringian species currently occurring in Alaska and the Yukon. We explored the spatial pattern of species richness, losses and climate change refugia across the region.

Results

More than 80% of the species showed northward shifts in their latitudinal centroids under intermediate warming and are expected to shift their range northward by more than 140 km on average by 2040. Additionally, more than 60% were projected to experience range contractions and up to 20% of the species would have the potential to expand their ranges by more than 100%.

Main Conclusions

Suitable habitat for endemic species in northwest North America is expected to decline significantly, especially for species occupying the Arctic tundra. Although the models identified several potential refugia from future climate change, especially at high latitude and elevation, whether the species would be able to colonize new habitats on their own and/or capitalize sufficiently on in situ refugia remains a pertinent conservation question.     

Impacts of climate change on dragonflies and damselflies in West and Central Asia

Aim

To project the impact of climate change on dragonfly and damselfly diversity in West and Central Asia.

Location

West and Central Asia.

Time period

1900–2020 data used to predict distributions in 2070 and 2100.

Taxon studied

Odonata.

Methods

Based on 149,001 records, distribution models were created for 159 species using MaxEnt. Environmental variables consisted of climate variables taken from BIOCLIM, river data and soil data. The future climate data were obtained from CHELSA from CMIP6 climate models. The same variables were collected for three scenarios (SSP1-2.6, SSP3-7.0 and SSP5-8.5) of shared socioeconomic pathways for the years 2050–2070 and 2080–2100. For each scenario and period, diversity maps were prepared for six species groups: all species, Lentic, Lotic, Oriental, Afrotropical and Palaearctic species.

Results

Strong declines in diversity are expected in western Turkey, the Levant and Azerbaijan, and to a lesser extent in parts of Iran and southern Central Asia. An increase is expected in eastern Turkey and at higher elevations in Central Asia with a limited increase throughout the Arabian Peninsula. In contrast to expectations, a decrease in areas with <15 species was found. Faunal composition is predicted to show strong shifts, with Palaearctic species declining and Oriental and Afrotropical species increasing. No clear difference between the trend of lentic and lotic species is found, although there are clear spatial differences in trend between these groups.

Main Conclusions

Climate change will result in strong changes in diversity and distribution of dragonflies and damselflies in West and Central Asia with regional declines and increases. None of the species are predicted to go extinct based on the impact of climate change only, however, the combined impact of climate change and anthropogenic forces is likely to push some of the species to near extinction by 2100.     

The impact of climate change measured at relevant spatial scales: new hope for tropical lizards

Much attention has been given to recent predictions that widespread extinctions of tropical ectotherms, and tropical forest lizards in particular, will result from anthropogenic climate change. Most of these predictions, however, are based on environmental temperature data measured at a maximum resolution of 1 km², whereas individuals of most species experience thermal variation on a much finer scale. To address this disconnect, we combined thermal performance curves for five populations of Anolis lizard from the Bay Islands of Honduras with high‐resolution temperature distributions generated from physical models. Previous research has suggested that open‐habitat species are likely to invade forest habitat and drive forest species to extinction. We test this hypothesis, and compare the vulnerabilities of closely related, but allopatric, forest species. Our data suggest that the open‐habitat populations we studied will not invade forest habitat and may actually benefit from predicted warming for many decades. Conversely, one of the forest species we studied should experience reduced activity time as a result of warming, while two others are unlikely to experience a significant decline in performance. Our results suggest that global‐scale predictions generated using low‐resolution temperature data may overestimate the vulnerability of many tropical ectotherms to climate change.     

Climate Change Risks and Conservation Implications for a Threatened Small-Range Mammal Species

Background

Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species.

Methodology/Principal Findings

We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070–2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species'' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming.

Conclusions/Significance

Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change.     

Climate versus weather extremes: Temporal predictor resolution matters for future rather than current regional species distribution models

Aim

Climate is considered a major driver of species distributions. Long‐term climatic means are commonly used as predictors in correlative species distribution models (SDMs). However, this coarse temporal resolution does not reflect local conditions that populations experience, such as short‐term weather extremes, which may have a strong impact on population dynamics and local distributions. We here compare the performance of climate‐ and weather‐based predictors in regional SDMs and their influence on future predictions, which are increasingly used in conservation planning.

Location

South‐western Germany.

Methods

We built different SDMs for 20 Orthoptera species based on three predictor sets at a regional scale for current and future climate scenarios. We calculated standard bioclimatic variables and yearly and seasonal sets of climate change indicating variables of weather extremes. As the impact of extreme events may be stronger for habitat specialists than for generalists, we distinguished species’ degrees of specialization. We computed linear mixed‐effects models to identify significant effects of algorithm, predictor set and specialization on model performance and calculated correlations and geographical niche overlap between spatial predictions.

Results

Current predictions were rather similar among all predictor sets, but highly variable for future climate scenarios. Bioclimatic and seasonal weather predictors performed slightly better than yearly weather predictors, though performance differences were minor. We found no evidence that specialists are more sensitive to weather extremes than generalists.

Main conclusions

For future projections of species distributions, SDM predictor selection should not solely be based on current performances and predictions. As long‐term climate and short‐term weather predictors represent different environmental drivers of a species’ distribution, we argue to interpret diverging future projections as complements. Even if similar current performances and predictions might imply their equivalency, favouring one predictor set neglects important aspects of future distributions and might mislead conservation decisions based on them.

     

Range contractions and reduced body mass predicted for endemic skinks of the Cameroon Volcanic Line with future warming

Aim

The vulnerability of montane species to environmental change has been increasingly recognized in recent years. However, most of these species are regionally endemic with restricted distributions, limiting dispersal necessary for avoiding extinction. The outcome of threats posed for montane lizards is further complicated in species exhibiting mass–temperature relationships where body size increases with cooling temperatures, and thus with altitude, causing intraspecific physiological and behavioural differences. We aimed to identify areas suitable for montane endemic skinks of the Cameroon Volcanic Line (CVL) under current and future climates to reveal patterns of persistence and vulnerability based on an intersection of climate and body mass.

Location

Cameroon Volcanic Line

Methods

We recorded occurrences and measured body mass in the field for two CVL-endemic skink species. We supplemented occurrences with online repository records. We projected current and future habitat suitability in the region by implementing bioclimatic species distribution models-based on occurrences. We tested for elevational variations in body mass, and integrated both occurrence and body mass information in a trait-based model to estimate current and future body mass.

Results

Projected currently suitable habitat for both species was limited to higher elevation regions, which are inhabited by numerous other threatened herpetofauna. We additionally detected Bergmann clines in body mass for both species. Given this variation in body mass, trait model projections covered slightly larger geographical ranges than bioclimatic estimates. Under future warming, both models project substantial contractions in suitable areas, potentially constraining species to mountain tops. Through the trait-based approach, we further detected potential warming-induced body mass reductions in projected suitable areas.

Main Conclusions

We demonstrate how combining occurrence records with species trait information in ecological modelling can reveal complementary trends for comprehensive warming impact assessments. Overall, challenges toward the persistence of CVL-endemic skinks should prompt urgent responses in national conservation management and local community engagement.     

Resolving the Azorean knot: a response to Carine & Schaefer (2010)

Carine & Schaefer (Journal of Biogeography, 2010, 37 , 77–89) suggest that the lack of past climate oscillations in the Azores may have contributed to the low plant endemism in this archipelago compared to that of the Canary Islands, a pattern they term the Azorean diversity enigma. Here we challenge their hypothesis, and discuss how the particular characteristics of the Azores may have driven current diversification patterns in this archipelago. We argue that the restricted number of Azorean endemic species and their wide distribution is explicable by the geological, geographical and ecological attributes of the archipelago. That is, the Azores are too young, too small, and too environmentally homogeneous to have hosted many in situ diversification events, so they do not host as many endemic species as other Macaronesian archipelagos, such as Madeira and especially the Canary Islands.     

Beyond climate control on species range: The importance of soil data to predict distribution of Amazonian plant species

Aim

To evaluate the relative importance of climatic versus soil data when predicting species distributions for Amazonian plants and to gain understanding of potential range shifts under climate change.

Location

Amazon rain forest.

Methods

We produced species distribution models (SDM) at 5‐km spatial resolution for 42 plant species (trees, palms, lianas, monocot herbs and ferns) using species occurrence data from herbarium records and plot‐based inventories. We modelled species distribution with Bayesian logistic regression using either climate data only, soil data only or climate and soil data together to estimate their relative predictive powers. For areas defined as unsuitable to species occurrence, we mapped the difference between the suitability predictions obtained with climate‐only versus soil‐only models to identify regions where climate and soil might restrict species ranges independently or jointly.

Results

For 40 out of the 42 species, the best models included both climate and soil predictors. The models including only soil predictors performed better than the models including only climate predictors, but we still detected a drought‐sensitive response for most of the species. Edaphic conditions were predicted to restrict species occurrence in the centre, the north‐west and in the north‐east of Amazonia, while the climatic conditions were identified as the restricting factor in the eastern Amazonia, at the border of Roraima and Venezuela and in the Andean foothills.

Main conclusions

Our results revealed that soil data are a more important predictor than climate of plant species range in Amazonia. The strong control of species ranges by edaphic features might reduce species’ abilities to track suitable climate conditions under a drought‐increase scenario. Future challenges are to improve the quality of soil data and couple them with process‐based models to better predict species range dynamics under climate change.     

Optimal thermal conditions for corals extend poleward with oceanic warming

Aim

The capacity for poleward range expansions beyond the tropics in corals hinges on ecophysiological constraints and resulting responses to climatic variability. We aimed to determine how future warming will affect coral habitat suitability at the poleward range edges of these foundational species in the Northwest Pacific.

Location

Northwest Pacific.

Methods

We generated models integrating thermal physiological constraints of corals adapted to extreme seasonality in Hong Kong, specifically the minimum annual temperature and the proportion of time annually spent at seasonal extremes. With these models, we projected habitat suitability for five coral species under current and future climatic conditions across the Northwest Pacific.

Results

Climate model projections reveal an easing of thermal constraints on the leading-edge of coral ecophysiological limits with an expansion of thermally suitable habitat poleward by 2°–7° in latitude depending on the coral species and model considered. We also highlight a potential divergence of present and future thermal regimes that may lead to a mismatch in suitability for corals currently inhabiting high latitude reefs.

Main Conclusions

Understanding the thermal constraints on coral distributions and defining the potential range of corals under climate change is critical for adaptive management that focuses on coral conservation and ensuring ecosystem function of existing subtropical and temperate ecosystems.     

Climate tracking by freshwater fishes suggests that fish diversity in temperate lakes may be increasingly threatened by climate warming

Aim

Many freshwater fishes are migrating poleward to more thermally suitable habitats in response to warming climates. In this study, we aimed to identify which freshwater fishes are most sensitive to climatic changes and asked: (i) how fast are lakes warming? (ii) how fast are fishes moving? and (iii) are freshwater fishes tracking climate?

Location

Ontario, Canada.

Methods

We assembled a database containing time series data on climate and species occurrence data from 10,732 lakes between 1986 and 2017. We calculated the rate of lake warming and climate velocity for these lakes. Climate velocities were compared with biotic velocities, specifically the rate at which the northernmost extent of each species shifted north.

Results

Lakes in Ontario warmed by 0.2°C decade⁻¹ on average, at a climate velocity of 9.4 km decade⁻¹ between 1986 and 2017. In response, some freshwater fishes have shifted their northern range boundaries with considerable interspecific variation ranging from species moving southwards at a rate of −58.9 km decade⁻¹ to species ranges moving northwards at a rate of 83.6 km decade⁻¹ over the same time period. More freshwater fish species are moving into northern lakes in Ontario than those being lost. Generally, predators are moving their range edges northwards, whereas prey fishes are being lost from northern lakes.

Main Conclusions

The concurrent loss of cooler refugia, combined with antagonistic competitive and predatory interactions with the range expanding species, has resulted in many commercially important predators moving their range edges northwards, whereas prey species have contracted their northern range edge boundaries. Trophic partitioning of range shifts highlights a previously undocumented observation of the loss of freshwater fishes from lower trophic levels in response to climate-driven migrations.     

Biotic interactions improve prediction of boreal bird distributions at macro-scales

Aim The role of biotic interactions in influencing species distributions at macro‐scales remains poorly understood. Here we test whether predictions of distributions for four boreal owl species at two macro‐scales (10 × 10 km and 40 × 40 km grid resolutions) are improved by incorporating interactions with woodpeckers into climate envelope models. Location Finland, northern Europe. Methods Distribution data for four owl and six woodpecker species, along with data for six land cover and three climatic variables, were collated from 2861 10 × 10 km grid cells. Generalized additive models were calibrated using a 50% random sample of the species data from western Finland, and by repeating this procedure 20 times for each of the four owl species. Models were fitted using three sets of explanatory variables: (1) climate only; (2) climate and land cover; and (3) climate, land cover and two woodpecker interaction variables. Models were evaluated using three approaches: (1) examination of explained deviance; (2) four‐fold cross‐validation using the model calibration data; and (3) comparison of predicted and observed values for independent grid cells in eastern Finland. The model accuracy for approaches (2) and (3) was measured using the area under the curve of a receiver operating characteristic plot. Results At 10‐km resolution, inclusion of the distribution of woodpeckers as a predictor variable significantly improved the explanatory power, cross‐validation statistics and the predictive accuracy of the models. Inclusion of land cover led to similar improvements at 10‐km resolution, although these improvements were less apparent at 40‐km resolution for both land cover and biotic interactions. Main conclusions Predictions of species distributions at macro‐scales may be significantly improved by incorporating biotic interactions and land cover variables into models. Our results are important for models used to predict the impacts of climate change, and emphasize the need for comprehensive evaluation of the reliability of species–climate impact models.     

Weather, not climate, defines distributions of vagile bird species

Background

Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species.

Methodology

We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed “weather” models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950–2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables.

Conclusions

Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species'' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions.     

On the use of climate covariates in aquatic species distribution models: are we at risk of throwing out the baby with the bath water?

Species distribution models (SDMs) in river ecosystems can incorporate climate information by using air temperature and precipitation as surrogate measures of instream conditions or by using independent models of water temperature and hydrology to link climate to instream habitat. The latter approach is preferable but constrained by the logistical burden of developing water temperature and hydrology models. We therefore assessed whether regional scale, freshwater SDM predictions are fundamentally different when climate data versus instream temperature and hydrology are used as covariates. Maximum entropy (MaxEnt) SDMs were built for 15 freshwater fishes using one of two covariate sets: 1) air temperature and precipitation (climate variables) in combination with physical habitat variables; or 2) water temperature, hydrology (instream variables) and physical habitat. Three procedures were then used to compare results from climate vs instream models. First, equivalence tests assessed average pairwise differences (site‐specific comparisons throughout each species’ range) among climate and instream models. Second, ‘congruence’ tests determined how often the same stream segments were assigned high habitat suitability by climate and instream models. Third, Schoener's D and Warren's I niche overlap statistics quantified range‐wide similarity in predicted habitat suitability from climate vs instream models. Equivalence tests revealed small, pairwise differences in habitat suitability between climate and instream models (mean pairwise differences in MaxEnt raw scores for all species < 3 × 10^–4). Congruence tests showed a strong tendency for climate and instream models to predict high habitat suitability at the same stream segments (median congruence = 68%). D and I statistics reflected a high margin of overlap among climate and instream models (median D = 0.78, median I = 0.96). Overall, we found little support for the hypothesis that SDM predictions are fundamentally different when climate versus instream covariates are used to model fish species’ distributions at the scale of the Columbia Basin.     

Modelling invasive alien species distributions from digital biodiversity atlases. Model upscaling as a means of reconciling data at different scales

Aim

There is a wealth of information on species occurrences in biodiversity data banks, albeit presence‐only, biased and scarce at fine resolutions. Moreover, fine‐resolution species maps are required in biodiversity conservation. New techniques for dealing with this kind of data have been reported to perform well. These fine‐resolution maps would be more robust if they could explain data at coarser resolutions at which species distributions are well represented. We present a new methodology for testing this hypothesis and apply it to invasive alien species (IAS).

Location

Catalonia, Spain.

Methods

We used species presence records from the Biodiversity data bank of Catalonia to model the distribution of ten IAS which, according to some recent studies, achieve their maximum distribution in the study area. To overcome problems inherent with the data, we prepared different correction treatments: three for dealing with bias and five for autocorrelation. We used the MaxEnt algorithm to generate models at 1‐km resolution for each species and treatment. Acceptable models were upscaled to 10 km and validated against independent 10 km occurrence data.

Results

Of a total of 150 models, 20 gave acceptable results at 1‐km resolution and 12 passed the cross‐scale validation test. No apparent pattern emerged, which could serve as a guide on modelling. Only four species gave models that also explained the distribution at the coarser scale.

Main conclusions

Although some techniques may apparently deliver good distribution maps for species with scarce and biased data, they need to be taken with caution. When good independent data at a coarser scale are available, cross‐scale validation can help to produce more reliable and robust maps. When no independent data are available for validation, however, new data gathering field surveys may be the only option if reliable fine‐scale resolution maps are needed.     

Simulating tick distributions over sub-Saharan Africa: the use of observed and simulated climate surfaces

Aim A broad suit of climate data sets is becoming available for use in predictive species modelling. We compare the efficacy of using interpolated climate surfaces [Center for Resource and Environmental Studies (CRES) and Climate Research Unit (CRU)] or high‐resolution model‐derived climate data [Division of Atmospheric Research limited‐area model (DARLAM)] for predictive species modelling, using tick distributions from sub‐Saharan Africa. Location The analysis is restricted to sub‐Saharan Africa. The study area was subdivided into 3000 grids cells with a resolution of 60 × 60 km. Methods Species distributions were predicted using an established multivariate climate envelope modelling approach and three very different climate data sets. The recorded variance in the climate data sets was quantified by employing omnidirectional variograms. To further compare the interpolated tick distributions that flowed from using three climate data sets, we calculated true positive (TP) predictions, false negative (FN) predictions as well as the proportional overlaps between observed and modelled tick distributions. In addition, the effect of tick data set size on the performance of the climate data sets was evaluated by performing random draws of known tick distribution records without replacement. Results The predicted distributions were consistently wider ranging than the known records when using any of the three climate data sets. However, the proportional overlap between predicted and known distributions varied as follows: for Rhipicephalus appendiculatus Neumann (Acari: Ixodidae), these were 60%, 60% and 70%; for Rhipicephalus longus Neumann (Acari: Ixodidae) 60%, 57% and 75%; for Rhipicephalus zambeziensis Walker, Norval & Corwin (Acari: Ixodidae) 57%, 51% and 62%, and for Rhipicephalus capensis Koch (Acari: Ixodidae) 70%, 60% and 60% using the CRES, CRU and DARLAM climate data sets, respectively. All data sets were sensitive to data size but DARLAM performed better when using smaller species data sets. At a 20% data subsample level, DARLAM was able to capture more than 50% of the known records and captured more than 60% of known records at higher subsample levels. Main conclusions The use of data derived from high‐resolution nested climate models (e.g. DARLAM) provided equal or even better species distribution modelling performance. As the model is dynamic and process based, the output data are available at the modelled resolution, and are not hamstrung by the sampling intensity of observed climate data sets (c. one sample per 30,000 km² for Africa). In addition, when exploring the biodiversity consequences of climate change, these modelled outputs form a more useful basis for comparison with modelled future climate scenarios.     

Ecological traits influence the current distribution and range of an island endemic bird

Aim  The aim of this paper is to investigate the causes of the current restricted distribution of a narrow-range endemic bird species, the Canary Islands stonechat, Saxicola dacotiae .
Location  Eastern islands of the Canary Islands archipelago.
Methods  We compared climatic patterns (temperature and rainfall), habitat and microhabitat structure, food availability during a full annual cycle, and the abundance of native avian competitors and predators inside and outside the species' range. Three study areas, located in similar habitats on nearby islands, were studied: northern Fuerteventura, close to the northern border of the species' range; southern Lanzarote, 22 km from the nearest site occupied by stonechats; and the Lobos islet, 10 km from the nearest occupied site and 2 km from the coast of Fuerteventura.
Results  The cover of suitable habitats (slopes with high cover of large shrubs, stony fields and ravines) and microhabitats (shrubs and boulders) and the abundance of arthropods during the breeding period of Canary Islands stonechats were lower outside than inside the species' range. Temperature, rainfall and the abundance of competitors and predators inside and outside the species' range did not differ significantly.
Main conclusions  Ecological requirements explaining the distribution of the Canary Islands stonechat within its range seem to be the main factor hindering its settlement on nearby islands. Geological and palaeoclimatic processes, as well as past and current human impact, could also have constrained the distribution of this narrow-range endemic bird species.     

Climate change impacts on Mediterranean vegetation are amplified at low altitudes

Aim

In the face of ongoing climate warming, we wanted to quantify impacts on vegetation at one of the major climatic and biogeographical boundaries of Europe, the limit between the Mediterranean and Eurosiberian biogeographical regions. We analyse temperature and moisture requirements of plants along altitudinal gradients at regional scale in the period 1980–2020 and we explore if changes coincide with observed changes in the same regions in terms of measured climatic data.

Location

Southern France.

Time period

1980–2020.

Taxa

Vascular plants.

Methods

We calculated shifts in plants’ temperature and moisture requirements for a large floristic database from south-eastern France (SIMETHIS) during the period 1980–2020 along altitudinal gradients by using ecological indicator values (EIV). Additionally, we analysed standardized weather station data from the same area and period, to investigate whether floristic changes are synchronized with climate changes.

Results

Vegetation data suggest a linear increase in temperature requirements of plant communities from 1980 to 2020 with a greater change at low altitudes. Upward shifts in temperature requirements coincided with observed climate change although warming did not show a general trend towards greater increases at low altitudes. Data on vegetation and climate suggest an upward shift of respectively 150 and 300 m for the boundary between Mediterranean and temperate belts. Moisture requirements of vegetation indicate an increase of the frequency of dry adapted species at low altitudes but an increase towards higher moisture requirements at high altitudes. Comparing vegetation responses with climate data suggests that responses are faster at low altitudes.

Main conclusions

Our analyses show that strong general changes in vegetation are underway and highlight faster responses of vegetation to warming in low altitudes compared to high altitudes and demonstrate the need for reliable data on vegetation and climate changes, especially on water balance.