Predicting the impact of climate change on Australia's most endangered snake, Hoplocephalus bungaroides

Aim  To predict how the bioclimatic envelope of the broad-headed snake (BHS) ( Hoplocephalus bungaroides ) may be redistributed under future climate warming scenarios.
Location  South-eastern New South Wales, Australia.
Methods  We used 159 independent locations for the species and 35 climatic variables to model the bioclimatic envelope for the BHS using two modelling approaches – B ioclim and M axent . Predictions were made under current climatic conditions and we also predicted the species distribution under low and high climate change scenarios for 2030 and 2070.
Results  Broad-headed snakes currently encompass their entire bioclimatic envelope. Both modelling approaches predict that suitable climate space for BHS will be lost to varying degrees under both climate warming scenarios, and under the worst case, only 14% of known snake populations may persist.
Main conclusions  Areas of higher elevation within the current range will be most important for persistence of this species because they will remain relatively moist and cool even under climate change and will match the current climate envelope. Conservation efforts should focus on areas where suitable climate space may persist under climate warming scenarios. Long-term monitoring programs should be established both in these areas and where populations are predicted to become extirpated, so that we can accurately determine changes in the distribution of this species throughout its range.     

Transactions of the Botanical Society of Edinburgh

Summary

Evidence is adduced that the ‘hypogynous bodies’ found in two unrelated sections of Hypericum are, at the same time, ‘new’ organs in Hypericum and yet homologous with sterile stamen facicles in other genera of the Guttiferae. Their reappearance is related to the development of specialised insect pollination.     

Biotic attrition from tropical forests correcting for truncated temperature niches

Species migration in response to warming temperatures is expected to lead to ‘biotic attrition,’ or loss of local diversity, in areas where the number of species emigrating or going locally extinct exceeds the number immigrating. Biotic attrition is predicted be especially severe in the low‐lying hot tropics since elevated temperatures may surpass the observed tolerances of most extant species. It is possible, however, that the estimated temperature niches of many species are inaccurate and truncated with respect to their true tolerances due to the absence of hotter areas under current global climate. If so, these species will be capable of persisting in some areas where future temperatures exceed current temperatures, reducing rates of biotic attrition. Here, we use natural history collections data to estimate the realized thermal niches of > 2000 plant species from the tropical forests of South America. In accord with the truncation hypothesis, we find that the thermal niches of species from hot lowland areas are several degrees narrower than the thermal niches of species from cooler areas. We estimate rates of biotic attrition for South American tropical forests due to temperature increases ranging from 1 to 5 °C, and under two niche assumptions. The first is that the observed thermal niches truly reflect the plant's tolerances and that the reduction in niche breadth is due to increased specialization. The second is that lowland species have the same mean thermal niche breadth as nonlowland and nonequatorial species. The differences between these two models are dramatic. For example, using observed thermal niches we predict an almost complete loss of plant diversity in most South American tropical forests due to a 5 °C temperature increase, but correcting for possible niche truncation we estimate that most forests will retain > 50–70% of their current species richness. The different predictions highlight the importance of using fundamental vs. realized niches in predicting the responses of species to global climate change.     

Multi‐species distribution modelling highlights the Adelaide Geosyncline,South Australia,as an important continental‐scale arid‐zone refugium

The mainland portion of the Adelaide Geosyncline (Mount Lofty and Flinders Ranges) has been postulated as an important arid‐zone climate refugium for Australia. To test the sensitivity of this putative Australian arid biome refugium to contemporary climate change, we compared Generalized Additive Modelling and MaxEnt distribution models for 20 vascular plant species. We aimed to identify shared patterns to inform priority areas for management. Models based on current climate were projected onto a hypothetical 2050 climate with a 1.5°C increase in temperature and 8% decrease in rainfall. Individual comparisons and combined outputs of logistic models for all 20 species showed range contraction to shared refugia in the Flinders Ranges and southern Mount Lofty Ranges. Modelling suggests the Flinders Ranges will experience species turnover while suitable climatic habitat will be retained in the Mount Lofty Ranges for the current suite of species. Fragmentation of the southern Mount Lofty Ranges poses management challenges for conserving species diversity with warming and drying. Although projected models must be interpreted carefully, they suggest the region will remain an important but threatened refugium for mesic species at a continental scale.     

Current distribution and potential extent of the most invasive alien plant species on La Réunion (Indian Ocean,Mascarene islands)

Abstract La Réunion Island has the largest area of intact vegetation of the islands in the Mascarene archipelago. Biological invasions are the primary threat to biodiversity in the intact habitats of the island (those not already transformed by agriculture and urbanization). Our study aimed to identify areas to prioritize in managing invasive alien plants for biodiversity conservation. We used extensive surveys of 238 distinct untransformed areas on La Réunion to define the current distribution patterns of all invasive species. Using expert knowledge, we compiled maps of the current distribution of the 46 most widespread/important invasive plants at the habitat scale (identified according to vegetation structure). Data from 440 botanical relevés for the 20 most threatening invasive alien plant species across the island and climatic envelope models were used to derive climatic suitability surfaces; these were used to map potential distributions for these species. More than 10 species invade 16.7% of the remaining habitat. Five habitat types are invaded by 25 or more species, and eight have fewer than 10 invasive alien plant species. Cluster analysis based on presence/absence of species in the 18 habitat types produced eight groups of species that invade particular habitats. Potential distribution models show that some species have invaded large parts of their potential range (e.g. Fuchsia magellanica, Furcraea foetida, Hiptage benghalensis), whereas others have the potential to increase their range substantially (e.g. Clidemia hirta, Strobilanthes hamiltonianus, Ulex europaeus). Management implications are identified for both groups. Three broad groups of habitats were identified: (i) intact habitats with a low level of invasion (e.g. subalpine shrubland); (ii) moderately invaded habitats with varying levels of intactness (ranging from windward submountain rainforest to the Acacia heterophylla forest); and (iii) habitats with little remaining intact area and high levels of invasion (e.g. lowland rainforest). Different management interventions are appropriate for these three groups.     

Where will species go? Incorporating new advances in climate modelling into projections of species distributions

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, T_max, T_min, and T_mean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.     

Inclusion of soil data improves the performance of bioclimatic envelope models for insect species distributions in temperate Europe

Aim To analyse the effect of the inclusion of soil and land‐cover data on the performance of bioclimatic envelope models for the regional‐scale prediction of butterfly (Rhopalocera) and grasshopper (Orthoptera) distributions. Location Temperate Europe (Belgium). Methods Distributional data were extracted from butterfly and grasshopper atlases at a resolution of 5 km for the period 1991–2006 in Belgium. For each group separately, the well‐surveyed squares (n = 366 for butterflies and n = 322 for grasshoppers) were identified using an environmental stratification design and were randomly divided into calibration (70%) and evaluation (30%) datasets. Generalized additive models were applied to the calibration dataset to estimate occurrence probabilities for 63 butterfly and 33 grasshopper species, as a function of: (1) climate, (2) climate and land‐cover, (3) climate and soil, and (4) climate, land‐cover and soil variables. Models were evaluated as: (1) the amount of explained deviance in the calibration dataset, (2) Akaike’s information criterion, and (3) the number of omission and commission errors in the evaluation dataset. Results Information on broad land‐cover classes or predominant soil types led to similar improvements in the performance relative to the climate‐only models for both taxonomic groups. In addition, the joint inclusion of land‐cover and soil variables in the models provided predictions that fitted more closely to the species distributions than the predictions obtained from bioclimatic models incorporating only land‐cover or only soil variables. The combined models exhibited higher discrimination ability between the presence and absence of species in the evaluation dataset. Main conclusions These results draw attention to the importance of soil data for species distribution models at regional scales of analysis. The combined inclusion of land‐cover and soil data in the models makes it possible to identify areas with suitable climatic conditions but unsuitable combinations of vegetation and soil types. While contingent on the species, the results indicate the need to consider soil information in regional‐scale species–climate impact models, particularly when predicting future range shifts of species under climate change.     

Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah

In this study, we test for the key bioclimatic variables that significantly explain the current distribution of plant species richness in a southern African ecosystem as a preamble to predicting plant species richness under a changed climate. We used 54,000 records of georeferenced plant species data to calculate species richness and spatially interpolated climate data to derive nineteen bioclimatic variables. Next, we determined the key bioclimatic variables explaining variation in species richness across Zimbabwe using regression analysis. Our results show that two bioclimatic variables, that is, precipitation of the warmest quarter (R² = 0.92, P < 0.001) and temperature of the warmest month (R² = 0.67, P < 0.001) significantly explain variation in plant species richness. In addition, results of bioclimatic modelling using future climate change projections show a reduction in the current bio‐climatically suitable area that supports high plant species richness. However, in high‐altitude areas, plant richness is less sensitive to climate change while low‐altitude areas show high sensitivity. Our results have important implications to biodiversity conservation in areas sensitive to climate change; for example, high‐altitude areas are likely to continue being biodiversity hotspots, as such future conservation efforts should be concentrated in these areas.     

Bioclimatic characterisation of an urban area: a case study in Bologna (Italy)

Summer bioclimatic discomfort is a significant public health problem. Bioclimatic characterisations of populations living in urban areas are usually very poor, although the risks are relatively higher in cities because of the phenomenon known as the “urban heat island”. We compared airport, rural, and urban bioclimatic conditions in terms of apparent temperature, Thom index, and temperature alone in several sites within a radius of approximately 25 km from the city of Bologna (Italy). The comparison between meteorological monitoring stations within and near the urban area showed the large impact of the urban heat island effect. Nighttime data showed the largest differences among the investigated sites. Minimum apparent temperatures at rural stations were about 3.5°C lower than the urban 30 m reference station, and 6°C lower than the 2 m urban site. The 2 m apparent temperature values within the urban area were several degrees higher (typically 2°C) than those taken above the roof, both for minimum and maximum values. Temporal trends in the different sites were highly correlated (generally above 0.90), but regression residuals were sometimes quite large. Finally, epidemiological implications are briefly addressed.     

Range reshuffling: Climate change,invasive species,and the case of Nothofagus forests in Aotearoa New Zealand

Aim

The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions.

Location

Aotearoa New Zealand.

Methods

We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native Nothofagus species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in future.

Results

Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for Nothofagus was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space.

Main Conclusion

If the predicted changes in habitat distribution translate to shifts in forest distribution, it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may prevent/delay some changes. But we also highlight that the poor establishment capacity of Nothofagus, and the contrasting ability of the conifers to invade, will present persistent conservation challenges in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.     

An initial assessment of the bioclimatic comfort in an outdoor public space in Lisbon

This paper describes the application of a methodology designed to analyse the relationship between climatic conditions and the perception of bioclimatic comfort. The experiment consisted of conducting simultaneous questionnaire surveys and weather measurements during 2 sunny spring days in an open urban area in Lisbon. The results showed that under outdoor conditions, thermal comfort can be maintained with temperatures well above the standard values defined for indoor conditions. There seems to be a spontaneous adaptation in terms of clothing whenever the physiological equivalent temperature threshold of 31°C is surpassed. The perception of air temperature is difficult to separate from the perception of the thermal environment and is modified by other parameters, particularly wind. The perception of solar radiation is related to the intensity of fluxes from various directions (i.e. falling upon both vertical and horizontal surfaces), weighted by the coefficients of incidence upon the human body. Wind was found to be the most intensely perceived variable, usually negatively. Wind perception depends largely on the extreme values of wind speed and wind variability. Women showed a stronger negative reaction to high wind speed than men. The experiment proved that this methodology is well-suited to achieving the proposed objectives and that it may be applied in other areas and in other seasons.     

Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale

Predicting the probability of successful establishment of plant species by matching climatic variables has considerable potential for incorporation in early warning systems for the management of biological invasions. We select South Africa as a model source area of invasions worldwide because it is an important exporter of plant species to other parts of the world because of the huge international demand for indigenous flora from this biodiversity hotspot. We first mapped the five ecoregions that occur both in South Africa and other parts of the world, but the very coarse definition of the ecoregions led to unreliable results in terms of predicting invasible areas. We then determined the bioclimatic features of South Africa's major terrestrial biomes and projected the potential distribution of analogous areas throughout the world. This approach is much more powerful, but depends strongly on how particular biomes are defined in donor countries. Finally, we developed bioclimatic niche models for 96 plant taxa (species and subspecies) endemic to South Africa and invasive elsewhere, and projected these globally after successfully evaluating model projections specifically for three well‐known invasive species (Carpobrotus edulis, Senecio glastifolius, Vellereophyton dealbatum) in different target areas. Cumulative probabilities of climatic suitability show that high‐risk regions are spatially limited globally but that these closely match hotspots of plant biodiversity. These probabilities are significantly correlated with the number of recorded invasive species from South Africa in natural areas, emphasizing the pivotal role of climate in defining invasion potential. Accounting for potential transfer vectors (trade and tourism) significantly adds to the explanatory power of climate suitability as an index of invasibility. The close match that we found between the climatic component of the ecological habitat suitability and the current pattern of occurrence of South Africa alien species in other parts of the world is encouraging. If species' distribution data in the donor country are available, climatic niche modelling offers a powerful tool for efficient and unbiased first‐step screening. Given that eradication of an established invasive species is extremely difficult and expensive, areas identified as potential new sites should be monitored and quarantine measures should be adopted.     

Will climate change be beneficial or detrimental to the invasive swede midge in North America? Contrasting predictions using climate projections from different general circulation models

Climate change may dramatically affect the distribution and abundance of organisms. With the world's population size expected to increase significantly during the next 100 years, we need to know how climate change might impact our food production systems. In particular, we need estimates of how future climate might alter the distribution of agricultural pests. We used the climate projections from two general circulation models (GCMs) of global climate, the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre model (HadCM3), for the A2 and B2 scenarios from the Special Report on Emissions Scenarios in conjunction with a previously published bioclimatic envelope model (BEM) to predict the potential changes in distribution and abundance of the swede midge, Contarinia nasturtii, in North America. The BEM in conjunction with either GCM predicted that C. nasturtii would spread from its current initial invasion in southern Ontario and northwestern New York State into the Canadian prairies, northern Canada, and midwestern United States, but the magnitude of risk depended strongly on the GCM and the scenario used. When the CGCM2 projections were used, the BEM predicted an extensive shift in the location of the midges' climatic envelope through most of Ontario, Quebec, and the maritime and prairie provinces by the 2080s. In the United States, C. nasturtii was predicted to spread to all the Great Lake states, into midwestern states as far south as Colorado, and west into Washington State. When the HadCM3 was applied, southern Ontario, Saskatchewan, and Washington State were not as favourable for C. nasturtii by the 2080s. Indeed, when used with the HadCM3 climate projections, the BEM predicted the virtual disappearance of ‘very favourable’ regions for C. nasturtii. The CGCM2 projections generally caused the BEM to predict a small increase in the mean number of midge generations throughout the course of the century, whereas, the HadCM3 projections resulted in roughly the same mean number of generations but decreased variance. Predictions of the likely potential of C. nasturtii spatial spread are thus strongly dependent on the source of climate projections. This study illustrates the importance of using multiple GCMs in combination with multiple scenarios when studying the potential for spatial spread of an organism in response to climate change.     

Temperature dependence of two parameters in a photosynthesis model

The temperature dependence of the photosynthetic parameters V_cmax, the maximum catalytic rate of the enzyme Rubisco, and J_max, the maximum electron transport rate, were examined using published datasets. An Arrehenius equation, modified to account for decreases in each parameter at high temperatures, satisfactorily described the temperature response for both parameters. There was remarkable conformity in V_cmax and J_max between all plants at T_leaf < 25 °C, when each parameter was normalized by their respective values at 25 °C (V_cmax0 and J_max0), but showed a high degree of variability between and within species at T_leaf > 30 °C. For both normalized V_cmax and J_max, the maximum fractional error introduced by assuming a common temperature response function is < ± 0·1 for most plants and < ± 0·22 for all plants when T_leaf < 25 °C. Fractional errors are typically < ± 0·45 in the temperature range 25–30 °C, but very large errors occur when a common function is used to estimate the photosynthetic parameters at temperatures > 30 °C. The ratio J_max/V_cmax varies with temperature, but analysis of the ratio at T_leaf = 25 °C using the fitted mean temperature response functions results in J_max0/V_cmax0 = 2·00 ± 0·60 (SD, n = 43).     

Modelling biome shifts and tree cover change for 2050 in West Africa

Aim Africa is expected to face severe changes in climatic conditions. Our objectives are: (1) to model trends and the extent of future biome shifts that may occur by 2050, (2) to model a trend in tree cover change, while accounting for human impact, and (3) to evaluate uncertainty in future climate projections. Location West Africa. Methods We modelled the potential future spatial distribution of desert, grassland, savanna, deciduous and evergreen forest in West Africa using six bioclimatic models. Future tree cover change was analysed with generalized additive models (GAMs). We used climate data from 17 general circulation models (GCMs) and included human population density and fire intensity to model tree cover. Consensus projections were derived via weighted averages to: (1) reduce inter‐model variability, and (2) describe trends extracted from different GCM projections. Results The strongest predicted effect of climate change was on desert and grasslands, where the bioclimatic envelope of grassland is projected to expand into the desert by an area of 2 million km². While savannas are predicted to contract in the south (by 54 ± 22 × 10⁴ km²), deciduous and evergreen forest biomes are expected to expand (64 ± 13 × 10⁴ km² and 77 ± 26 × 10⁴ km²). However, uncertainty due to different GCMs was particularly high for the grassland and the evergreen biome shift. Increasing tree cover (1–10%) was projected for large parts of Benin, Burkina Faso, Côte d’Ivoire, Ghana and Togo, but a decrease was projected for coastal areas (1–20%). Furthermore, human impact negatively affected tree cover and partly changed the direction of the projected change from increase to decrease. Main conclusions Considering climate change alone, the model results of potential vegetation (biomes) show a ‘greening’ trend by 2050. However, the modelled effects of human impact suggest future forest degradation. Thus, it is essential to consider both climate change and human impact in order to generate realistic future tree cover projections.     

Spatio-temporal impact of climate change on the activity and voltinism of the spruce bark beetle, Ips typographus

The spruce bark beetle Ips typographus is one of the major insect pests of mature Norway spruce forests. In this study, a model describing the temperature-dependent thresholds for swarming activity and temperature requirement for development from egg to adult was driven by transient regional climate scenario data for Sweden, covering the period of 1961–2100 for three future climate change scenarios (SRES A2, A1B and B2). During the 20th century, the weather supported the production of one bark beetle generation per year, except in the north-western mountainous parts of Sweden where the climate conditions were too harsh. A warmer climate may sustain a viable population also in the mountainous part; however, the distributional range of I. typographus may be restricted by the migration speed of Norway spruce. Modelling suggests that an earlier timing of spring swarming and fulfilled development of the first generation will significantly increase the frequency of summer swarming. Model calculations suggest that the spruce bark beetle will be able to initiate a second generation in South Sweden during 50% of the years around the mid century. By the end of the century, when temperatures during the bark beetle activity period are projected to have increased by 2.4–3.8 °C, a second generation will be initiated in South Sweden in 63–81% of the years. The corresponding figures are 16–33% for Mid Sweden, and 1–6% for North Sweden. During the next decades, one to two generations per year are predicted in response to temperature, and the northern distribution limit for the second generation will vary. Our study addresses questions applicable to sustainable forest management, suggesting that adequate countermeasures require monitoring of regional differences in timing of swarming and development of I. typographus , and planning of control operations during summer periods with large populations of bark beetles.     

Impact of climate change on the distribution of populations of an endemic Mexican columnar cactus in the Tehuacán-Cuicatlán Valley,Mexico

In this paper, we present a bioclimatic approach to (1) differentiate populations of the endemic Mexican columnar cactus Neobuxbaumia tetetzo within the Tehuacán-Cuicatlán Valley and (2) evaluate, under two possible future scenarios (years 2050 and 2080), the effects of climate change on the total species distribution in this area, as well as on groups of populations defined by their bioclimatic models. Four population groups were identified, and principal component analysis showed that the variables that explained more than 40% of the climatic variation were precipitation of the wettest quarter and temperature seasonality. Bioclimatic models under the different scenarios indicated that when the overall species distribution was analyzed, this area will probably have contracted by 19.5% by the year 2050 and 47.05% by the year 2080, whereas the separate analysis of population groups projected area contractions of 18.4% by the year 2050 and 51.95% by the year 2080. These results demonstrate the importance of exploring new approaches for evaluating and predicting current and future distribution of plant species.     

Climate change at the landscape scale: predicting fine-grained spatial heterogeneity in warming and potential refugia for vegetation

Current predictions of how species will respond to climate change are based on coarse‐grained climate surfaces or idealized scenarios of uniform warming. These predictions may erroneously estimate the risk of extinction because they neglect to consider spatially heterogenous warming at the landscape scale or identify refugia where species can persist despite unfavourable regional climate. To address this issue, we investigated the heterogeneity in warming that has occurred in a 10 km × 10 km area from 1972 to 2007. We developed estimates by combining long‐term daily observations from a limited number of weather stations with a more spatially comprehensive dataset (40 sites) obtained during 2005–2006. We found that the spatial distribution of warming was greater inland, at lower elevations, away from streams, and at sites exposed to the northwest (NW). These differences corresponded with changes in weather patterns, such as an increasing frequency of hot, dry NW winds. As plant species were biased in the topographic and geographic locations they occupied, these differences meant that some species experienced more warming than others, and are at greater risk from climate change. This species bias could not be detected at coarser scales. The uneven seasonal nature of warming (e.g. more warming in winter, minimums increased more than maximums) means that climate change predictions will vary according to which predictors are selected in species distribution models. Models based on a limited set of predictors will produce erroneous predictions when the correct limiting factor is not selected, and this is difficult to avoid when temperature predictors are correlated because they are produced using elevation‐sensitive interpolations. The results reinforce the importance of downscaling coarse‐grained (∼50 km) temperature surfaces, and suggest that the accuracy of this process could be improved by considering regional weather patterns (wind speed, direction, humidity) and topographic exposure to key wind directions.