A fine-scaled predictive model for changes in species distribution patterns of high mountain plants induced by climate warming

Induced by global warming, mountain plant species are migrating upwards. Species inhabiting the nival zone of today are threatened by competitors which move from the alpine zone towards the summits. The manner in which species move depends on their abilities to cope with microtopographical situations. We present a spatially explicit predictive model which draws scenarios of future species distribution patterns at a typical high mountain of the European Alps. The altitudinal temperature gradient is examined. Based on the lapse rate and on definitions of topographical niches of species, a +1 °C- and a +2 °C-warming scenario are modelled using a fine-scaled digital elevation model. Nival species will lose area and become restricted to specific topographical situations. Alpine and subnival grassland species are predicted to expand their area, mainly along stable surface situations. Whether the migration will take place as a filling or a moving process is specific to the particular species. Overall, biodiversity is apparently not threatened on the decadal scale. In special cases, however, genetic losses are likely both on a local and on a regional scale.     

Predicting the potential global distribution of Ageratina adenophora under current and future climate change scenarios

AimInvasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable areas of IAS can prevent their further expansion. Ageratina adenophora is an invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable areas of A. adenophora remain unclear along with its response to climate change. This study explored and mapped the current and future potential suitable areas of Ageratina adenophora.LocationGlobal.TaxaAsteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed.MethodsBased on A. adenophora occurrence data and climate data, we predicted its suitable areas of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the potential suitable area distribution characteristics of this weed and the “ecospat” package in R to analyze its altitudinal distribution changes.ResultsThe area under the curve (AUC) value (>0.9) and true skill statistics (TSS) value (>0.8) indicated excelled model performance. Among environment factors, mean temperature of coldest quarter contributed most to the model. Globally, the suitable areas for A. adenophora invasion decreased under climate change scenarios, although regional increases were observed, including in six biodiversity hotspot regions. The potential suitable areas of A. adenophora under climate change would expand in regions with higher elevation (3,000–3,500 m).Main conclusionsMean temperature of coldest quarter was the most important variable influencing the potential suitable area of A. Adenophora. Under the background of a warming climate, the potential suitable area of A. adenophora will shrink globally but increase in six biodiversity hotspot regions. The potential suitable area of A. adenophora would expand at higher elevation (3,000–3,500 m) under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.     

Climate change and plant distribution: local models predict high-elevation persistence

Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change-induced habitat losses predicted at the European scale (10 × 10' grid cells) are also predicted from local-scale data and modeling (25 m × 25 m grid cells) in two regions of the Swiss Alps. We show that local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10 × 10' cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local-scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.     

Simulating vegetation shifts in north-eastern Mediterranean mountain forests under climatic change scenarios

Aim  To explore potential shifts in vegetation and fire regime in some dominant forest types in the north-eastern part of the Mediterranean basin under climate change.
Location  Two altitudinal gradients in the continental part of Greece.
Methods  We developed a forest gap dynamics simulator that provides feedback from the stand to its water balance and flammability status. The model is used to simulate vegetation dynamics in two mountainous areas, currently found under different aridity conditions. Two climatic change scenarios (Intergovernmental Panel on Climate Change A1 and B2) were applied to explore differences in the response of the established forest types. In addition we explicitly accounted for the role of fire, under both current and altered climate patterns.
Results  Fire was identified to play a significant role in low-altitude sites. Its significance increased with the severity of the climate change scenario. Elevational shifts of the dominant species were simulated for each site, while in some cases these changes were associated with a shorter fire cycle and a frequent resetting of processes of vegetation change.
Main conclusions  Our simulations suggest a greater vulnerability of mountainous Mediterranean drier areas regarding compositional alteration and flammability trends. Changes in vegetation could take place through both a discrete and synergistic realization of changes in the drought stress and fire frequency.     

Lags in the response of mountain plant communities to climate change

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: “dispersal lags” affecting plant species’ spread along elevational gradients, “establishment lags” following their arrival in recipient communities, and “extinction lags” of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species’ range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide.     

Uncertainty in predicting range dynamics of endemic alpine plants under climate warming

Correlative species distribution models have long been the predominant approach to predict species’ range responses to climate change. Recently, the use of dynamic models is increasingly advocated for because these models better represent the main processes involved in range shifts and also simulate transient dynamics. A well‐known problem with the application of these models is the lack of data for estimating necessary parameters of demographic and dispersal processes. However, what has been hardly considered so far is the fact that simulating transient dynamics potentially implies additional uncertainty arising from our ignorance of short‐term climate variability in future climatic trends. Here, we use endemic mountain plants of Austria as a case study to assess how the integration of decadal variability in future climate affects outcomes of dynamic range models as compared to projected long‐term trends and uncertainty in demographic and dispersal parameters. We do so by contrasting simulations of a so‐called hybrid model run under fluctuating climatic conditions with those based on a linear interpolation of climatic conditions between current values and those predicted for the end of the 21st century. We find that accounting for short‐term climate variability modifies model results nearly as differences in projected long‐term trends and much more than uncertainty in demographic/dispersal parameters. In particular, range loss and extinction rates are much higher when simulations are run under fluctuating conditions. These results highlight the importance of considering the appropriate temporal resolution when parameterizing and applying range‐dynamic models, and hybrid models in particular. In case of our endemic mountain plants, we hypothesize that smoothed linear time series deliver more reliable results because these long‐lived species are primarily responsive to long‐term climate averages.     

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.     

Population genetics reveals origin and number of founders in a biological invasion

Propagule pressure is considered the main determinant of success of biological invasions: when a large number of individuals are introduced into an area, the species is more likely to establish and become invasive. Nevertheless, precise data on propagule pressure exist only for a small sample of invasive species, usually voluntarily introduced. We studied the invasion of the American bullfrog, Rana catesbeiana, into Europe, a species that is considered a major cause of decline for native amphibians. For this major invader with scarce historical data, we used population genetics data (a partial sequence of the mitochondrial cytochrome b gene) to infer the invasion history and to estimate the number of founders of non-native populations. Based on differences between populations, at least six independent introductions from the native range occurred in Europe, followed by secondary translocations. Genetic diversity was strongly reduced in non-native populations, indicating a very strong bottleneck during colonization. We used simulations to estimate the precise number of founders and found that most non-native populations derive from less than six females. This capability of invasion from a very small number of propagules challenges usual management strategies; species with such ability should be identified at an early stage of introduction.     

Propagule pressure and an invasion syndrome determine invasion success in a plant community model

The success of species invasions depends on multiple factors, including propagule pressure, disturbance, productivity, and the traits of native and non‐native species. While the importance of many of these determinants has already been investigated in relative isolation, they are rarely studied in combination. Here, we address this shortcoming by exploring the effect of the above‐listed factors on the success of invasions using an individual‐based mechanistic model. This approach enables us to explicitly control environmental factors (temperature as surrogate for productivity, disturbance, and propagule pressure) as well as to monitor whole‐community trait distributions of environmental adaptation, mass, and dispersal abilities. We simulated introductions of plant individuals to an oceanic island to assess which factors and species traits contribute to invasion success. We found that the most influential factors were higher propagule pressure and a particular set of traits. This invasion trait syndrome was characterized by a relative similarity in functional traits of invasive to native species, while invasive species had on average higher environmental adaptation, higher body mass, and increased dispersal distances, that is, had greater competitive and dispersive abilities. Our results highlight the importance in management practice of reducing the import of alien species, especially those that display this trait syndrome and come from similar habitats as those being managed.     

Twenty‐five years of plant community dynamics and invasion in New Zealand tussock grasslands

Understanding how plant communities respond to plant invasions is important both for understanding community structure and for predicting future ecosystem change. In a system undergoing intense plant invasion for 25 years, we investigated patterns of community change at a regional scale. Specifically, we sought to quantify how tussock grassland plant community structure had changed and whether changes were related to increases in plant invasion. Frequency data for all vascular plants were recorded on 124, permanent transects in tussock grasslands across the lower eastern South Island of New Zealand measured three times over a period of 25 years. Multivariate analyses of species richness were used to describe spatial and temporal patterns in the vegetation. Linear mixed‐effects models were used to relate temporal changes in community structure to the level and rate of invasion of three dominant invasive species in the genus Hieracium while accounting for relationships with other biotic and abiotic variables. There was a strong compositional gradient from exotic‐ to native‐dominated plant communities that correlated with increasing elevation. Over the 25 years, small‐scale species richness significantly decreased and then increased again; however, these changes differed in different plant communities. Exotic species frequency consistently increased on some transects and consistently declined on others. Species richness changes were correlated with the level of Hieracium invasion and abiotic factors, although the relationship with Hieracium changed from negative to positive over time. Compositional changes were not related to measured predictors. Our results suggest that observed broad‐scale fluctuations in species richness and community composition dynamics were not driven by Hieracium invasion. Given the relatively minor changes in community composition over time, we conclude that there is no evidence for widespread degradation of these grasslands over the last 25 years. However, because of continuing weed invasion, particularly at lower elevations, impacts may emerge in the longer term.     

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.     

Disturbance, invasion and re-invasion: managing the weed-shaped hole in disturbed ecosystems

We aim to develop a simple model to explore how disturbance and propagule pressure determine conditions for successful invasion in systems where recruitment occurs only in disturbed sites. Disturbance is often thought to favour invaders as it allows recruitment; however, the effects of disturbance are more complicated when it results in mortality of the invader. When disturbance rates in both invader occupied and unoccupied sites are the same, recruitment and mortality effects are exactly balanced, and successful invasion is independent of the disturbance regime. Differences in the disturbance rates between invader occupied and unoccupied sites can occur through invader modification or management of disturbance. Under these conditions, we found a novel mechanism for the generation of an Allee effect, which occurs when the invader promotes disturbance in sites it already occupies. When Allee effects occur one-off, large-scale disturbances can result in permanent, dramatic shifts in invader abundance; and conversely, reducing the population below a critical threshold can cause extinction.     

Predicting changes in the distribution and abundance of species under environmental change

Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes.     

全球变化情景下的中国木本植物受威胁物种名录

生物多样性正面临快速丧失的风险, 气候和土地利用变化已成为生物多样性的主要威胁之一。受威胁物种名录是区域和全球生物多样性保护的重要基础数据, 也是保护区规划的基础。作为一个生物多样性大国, 中国已开展了高等植物受威胁状况的系统性评估, 建立了受威胁植物名录, 为植物多样性保护规划提供了支撑。但由于数据和方法限制, 现有受威胁植物名录制定时未定量考虑全球变化对植物分布的潜在影响, 因而可能低估物种的受威胁等级及未来生物多样性的丧失风险。本研究基于高精度的木本植物分布数据和物种分布模型, 评估了未来气候和土地利用变化对木本植物分布的潜在影响。基于每个物种适宜分布区大小的变化, 并依据IUCN红色名录评估指标A3c的阈值标准, 更新了木本植物的受威胁等级, 补充了未来中国潜在受威胁木本植物名录。结果显示: 综合不同的气候变化情景(RCP 2.6、RCP 6.0和RCP 8.5)和扩散情景(完全扩散、20 km/10年、不扩散), 约12.9%-40.5%的木本植物被评估为受威胁物种。该名录将为制定木本植物保护优先级、开展保护区规划、提升全球变化情景下的生物多样性保护成效提供基础数据, 也为其他类群制定全面的受威胁物种名录提供参考。     

Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model

The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO₂ concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO₂. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.     

Areas of high conservation value at risk by plant invaders in Georgia under climate change

Invasive alien plants (IAP) are a threat to biodiversity worldwide. Understanding and anticipating invasions allow for more efficient management. In this regard, predicting potential invasion risks by IAPs is essential to support conservation planning into areas of high conservation value (AHCV) such as sites exhibiting exceptional botanical richness, assemblage of rare, and threatened and/or endemic plant species. Here, we identified AHCV in Georgia, a country showing high plant richness, and assessed the susceptibility of these areas to colonization by IAPs under present and future climatic conditions. We used actual protected areas and areas of high plant endemism (identified using occurrences of 114 Georgian endemic plant species) as proxies for AHCV. Then, we assessed present and future potential distribution of 27 IAPs using species distribution models under four climate change scenarios and stacked single‐species potential distribution into a consensus map representing IAPs richness. We evaluated present and future invasion risks in AHCV using IAPs richness as a metric of susceptibility. We show that the actual protected areas cover only 9.4% of the areas of high plant endemism in Georgia. IAPs are presently located at lower elevations around the large urban centers and in western Georgia. We predict a shift of IAPs toward eastern Georgia and higher altitudes and an increased susceptibility of AHCV to IAPs under future climate change. Our study provides a good baseline for decision makers and stakeholders on where and how resources should be invested in the most efficient way to protect Georgia's high plant richness from IAPs.     

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.