Anticipating the spatio-temporal response of plant diversity and vegetation structure to climate and land use change in a protected area

Toward spatially polarized human pressure? A dynamic factor analysis of ecological stability and the role of territorial gradients in Czech Republic

In light of global change, research on ecosystem dynamics and the related environmental policies are increasingly required to face with the inherent polarization in areas with low and high human pressure. Differential levels of human pressure are hypothesized to reflect development paths toward ecological stability of local systems vis à vis socioeconomic resilience. To delineate the latent nexus between socioeconomic development paths and ecological stability of local systems, we proposed a multidimensional, diachronic analysis of 28 indicators of territorial disparities, and ecological stability in 206 homogeneous administrative units of Czech Republic over almost 30 years (1990-2018). Mixing time-invariant factors with time-varying socio-environmental attributes, a dynamic factor analysis investigated the latent relationship between ecosystem functions, environmental pressures, and the background socioeconomic characteristics of the selected spatial units. We identified four geographical gradients in Czech Republic (namely elevation, economic agglomeration, demographic structure, and soil imperviousness) at the base of territorial divides associated with the increased polarization in areas with low and high human pressure. The role of urbanization, agriculture, and loss of natural habitats reflective of rising human pressure was illustrated along the selected gradients. Finally, policy implications of the (changing) geography of ecological disturbances and local development paths in Czech Republic were briefly discussed.

Responses of vegetation to changes in terrestrial water storage and temperature in global mountainous regions

As an important component of terrestrial ecosystem, vegetation acts as a sensitive recorder of changes in hydroclimatic conditions. Long-term time series of remote sensing-based vegetation indices and their influencing environmental driving factors, such as human activities and climate change, have been widely discussed in the literature. Globally, however, little is known about the hydroclimatic processes controlling vegetation changes in mountainous regions, which are conceived as more sensitive to climate change than other landscapes. The present study aims to quantify the respective roles of two dominant hydroclimatic factors, namely, TWS (i.e., terrestrial water storage) and T_air (i.e., temperature), in the spatio-temporal changes of mountainous vegetation over global six contrasting climate zones (i.e., tropical, arid, subtropical, temperate, sub-frigid, and frigid zones) during the period 2003-2016 based on EVI (i.e., enhanced vegetation index), TWS, T_air, and elevation data. Results indicate that the mean EVI shows a larger increasing trend (+0.85 %/decade, p-value < 0.01) and a larger decreasing trend in TWS (-85 mm/decade, p-value < 0.01) across the global mountainous regions than other global regions combined together (+0.61 %/decade, p-value < 0.01), particularly over high latitudes. With the increasing latitudes, the positive effect of temperature more dominates mountainous vegetation growth than moisture, as evidenced by the increasing trends of EVI with warming. However, in certain low-latitude mountainous regions (e.g., East Africa, South Asia, the western Tibetan Plateau, Brazil Plateau, and the southern Rocky Mountains), mountainous vegetation may face degradation due to water deficit induced by increased snowmelt, especially among the high-elevation ecosystems. The water availability controls vegetation activities more than T_air in the mid- and low-latitude regions, including the tropical, arid, and subtropical climate zones. These findings indicate that the potential shifts in mountainous vegetation may occur under the notable interactions with hydroclimatic factors, as the high-latitudes are experiencing ongoing warming and the mid- and low-latitudes are getting dryer.

Faster velocity changes in the near-surface soil freeze state in croplands than in forests across northeast China from 1979 to 2020

Climate warming has significantly changed the near-surface soil freeze state, significantly impacting terrestrial ecosystems and regional agroforestry production. As Northeast China (NEC) is highly sensitive to climate change, this study introduces the concept of velocity to analyze the spatial pattern of frozen days (F_DAY), onset date of soil freeze (F_ON), offset date of soil freeze (F_OFF), and number of soil freeze/thaw cycles in spring (FT_C) in NEC from 1979 to 2020. We observed that the velocity changes of F_DAY, F_ON, and FT_C in croplands were significantly higher than those in forests (difference >1 km yr^-1), with the fastest velocity changes found in the cropland of the Songnen Plain. The highest velocity of F_OFF was found in the forests of the Greater Khingan Range. In most study areas (>60%), the isoline of F_DAY/F_ON/F_OFF/FT_C showed a northward movement. The isoline of F_DAY/F_ON/F_OFF/FT_C moved in the cold direction in each cropland region (Sanjiang, Songnen, and Liaohe River Plains) and forest regions (Greater Khingan and Lesser Khingan Ranges, and the Changbai Mountains). The results of the quantitative analysis indicate that air temperature (T_A) had a more significant effect on the velocity change of F_DAY and F_ON in cropland, whereas snowpack is the dominant factor in forests. In both forests and croplands, the main factor affecting the velocity of F_OFF was snowpack, and T_A mainly affected the FT_C. This study is significant for formulating regional climate change countermeasures and maintaining ecological security in cold regions.

Monthly rather than annual climate variation determines plant diversity change in four temperate grassland nature reserves

Plant diversity is changing in the world; climate variation at annual scale is believed to drive these changes; however, the effects of climate variation at month scale are still unknown. Anxi, West Ordos, Xilingol, and Tumuji grassland nature reserves, located in northern China, have been well protected from human disturbance, are ideal areas to identify the drive forces for plant diversity change. Using Landsat images from 1982 to 2017, we analyzed the evolution of month- and annual-climate variables and spectral plant diversity indices, and explored the effects of the variability of temperature and precipitation on plant diversity and their relationship. The results showed that the diversity of the four grasslands was decreasing. Climate variables, in particular temperature at month scale, significantly related to grassland plant diversity. These results enlarge our understanding in how climate change driving plant diversity during a long term. Measurements coping with plant diversity decreasing may be more effective and earlier based on monthly climate variables.

Maximizing regional biodiversity requires a mosaic of protection levels

Protected areas are the flagship management tools to secure biodiversity from anthropogenic impacts. However, the extent to which adjacent areas with distinct protection levels host different species numbers and compositions remains uncertain. Here, using reef fishes, European alpine plants, and North American birds, we show that the composition of species in adjacent Strictly Protected, Restricted, and Non-Protected areas is highly dissimilar, whereas the number of species is similar, after controlling for environmental conditions, sample size, and rarity. We find that between 12% and 15% of species are only recorded in Non-Protected areas, suggesting that a non-negligible part of regional biodiversity occurs where human activities are less regulated. For imperiled species, the proportion only recorded in Strictly Protected areas reaches 58% for fishes, 11% for birds, and 7% for plants, highlighting the fundamental and unique role of protected areas and their environmental conditions in biodiversity conservation.

This study shows that the dissimilarity in species composition between sites with different levels of protection is consistently high, suggesting that adjacent and connected areas with different protection levels host very dissimilar species assemblages.

Effects of Temperature Rise on Multi-Taxa Distributions in Mountain Ecosystems

Mountain biodiversity is associated with rare and fragile biota that are highly sensitive to climate change. To estimate the vulnerability of biodiversity to temperature rise, long-term field data are crucial. Species distribution models are an essential tool, in particular for invertebrates, for which detailed information on spatial and temporal distributions is largely missing. We applied presence-only distribution models to field data obtained from a systematic survey of 5 taxa (birds, butterflies, carabids, spiders, staphylinids), monitored in the northwestern Italian Alps. We estimated the effects of a moderate temperature increase on the multi-taxa distributions. Only small changes in the overall biodiversity patterns emerged, but we observed significant differences between groups of species and along the altitudinal gradient. The effects of temperature increase could be more pronounced for spiders and butterflies, and particularly detrimental for high-altitude species. We observed significant changes in community composition and species richness, especially in the alpine belt, but a clear separation between vegetation levels was retained also in the warming scenarios. Our conservative approach suggests that even a moderate temperature increase (about 1 °C) could influence animal biodiversity in mountain ecosystems: only long-term field data can provide the information to improve quantitative predictions, allowing us to readily identify the most informative signals of forthcoming changes.

Drought effects on the stability of forest-grassland ecotones under gradual climate change

Plant communities in forest-grassland ecotones of the European Alps are already suffering from gradual climate change and will likely be exposed to more frequent and intense drought periods in the future. Yet, how gradual climate change and extreme drought will affect the stability of these plant communities is largely unknown. Here, we investigated how drought modulates the effects of gradual climate change on the long-term structural stability of these ecotone communities using a multidimensional approach. Using a spatially explicit landscape vegetation model, we simulated three drought scenarios, on top of gradual changes of climate variables, and their impacts on the dynamics of 24 plant functional groups, distinguishing between forests and grasslands, as well as different land uses. We then used n-dimensional hypervolumes to define community states under the different drought scenarios, and compared them to initial conditions to assess changes in community structural stability. In general, added drought effects did not counteract the long-term consequences of gradual climate changes, although they resulted in quantitatively different effects. Importantly, drought and climate change had non-negligible consequences for taxonomic and functional structure that differed between communities and land-use regimes. For instance, forest taxonomic structure was more overall more stable than grassland’s, despite the observed functional shifts towards more warm-adapted species compositions. Conversely, unmanaged grasslands were the least stable, suffering the loss of characteristic alpine species. Also, while frequent and severe drought regimes caused forests to become more variable in time, they had the opposite effect on grasslands. Our results agree with observations of drought- and climate-driven changes in mountain communities of the Alps, and we discuss their relevance for ecosystem management. Importantly, we demonstrate the utility of this multidimensional approach to study community stability for analysing cross-community and cross-disturbance responses to global change.

Simulating plant invasion dynamics in mountain ecosystems under global change scenarios

Across the globe, invasive alien species cause severe environmental changes, altering species composition and ecosystem functions. So far, mountain areas have mostly been spared from large-scale invasions. However, climate change, land-use abandonment, the development of tourism and the increasing ornamental trade will weaken the barriers to invasions in these systems. Understanding how alien species will react and how native communities will influence their success is thus of prime importance in a management perspective. Here, we used a spatially and temporally explicit simulation model to forecast invasion risks in a protected mountain area in the French Alps under future conditions. We combined scenarios of climate change, land-use abandonment and tourism-linked increases in propagule pressure to test if the spread of alien species in the region will increase in the future. We modelled already naturalized alien species and new ornamental plants, accounting for interactions among global change components, and also competition with the native vegetation. Our results show that propagule pressure and climate change will interact to increase overall species richness of both naturalized aliens and new ornamentals, as well as their upper elevational limits and regional range-sizes. Under climate change, woody aliens are predicted to more than double in range-size and herbaceous species to occupy up to 20% of the park area. In contrast, land-use abandonment will open new invasion opportunities for woody aliens, but decrease invasion probability for naturalized and ornamental alien herbs as a consequence of colonization by native trees. This emphasizes the importance of interactions with the native vegetation either for facilitating or potentially for curbing invasions. Overall, our work highlights an additional and previously underestimated threat for the fragile mountain flora of the Alps already facing climate changes, land-use transformations and overexploitation by tourism.

How disturbance, competition, and dispersal interact to prevent tree range boundaries from keeping pace with climate change

Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change, disturbance and competitive interactions to produce range shifts are poorly understood. We used a physiologically based mechanistic landscape model to study these interactions in the northeastern United States. We designed a series of disturbance scenarios to represent varied disturbance regimes in terms of both disturbance extent and intensity. We simulated forest succession by incorporating climate change under a high-emissions future, disturbances, seed dispersal, and competition using the landscape model parameterized with forest inventory data. Tree species range boundary shifts in the next century were quantified as the change in the location of the 5th (the trailing edge) and 95th (the leading edge) percentiles of the spatial distribution of simulated species. Simulated tree species range boundary shifts in New England over the next century were far below (usually <20 km) that required to track the velocity of temperature change (usually more than 110 km over 100 years) under a high-emissions scenario. Simulated species` ranges shifted northward at both the leading edge (northern boundary) and trailing edge (southern boundary). Disturbances may expedite species' recruitment into new sites, but they had little effect on the velocity of simulated range boundary shifts. Range shifts at the trailing edge tended to be associated with photosynthetic capacity, competitive ability for light and seed dispersal ability, whereas shifts at the leading edge were associated only with photosynthetic capacity and competition for light. This study underscores the importance of understanding the role of interspecific competition and disturbance when studying tree range shifts.

A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Population-level genetic variation and climate change in a biodiversity hotspot

INTRODUCTION

Estimated future climate scenarios can be used to predict where hotspots of endemism may occur over the next century, but life history, ecological and genetic traits will be important in informing the varying responses within myriad taxa. Essential to predicting the consequences of climate change to individual species will be an understanding of the factors that drive genetic structure within and among populations. Here, I review the factors that influence the genetic structure of plant species in California, but are applicable elsewhere; existing levels of genetic variation, life history and ecological characteristics will affect the ability of an individual taxon to persist in the presence of anthropogenic change.

FACTORS INFLUENCING THE DISTRIBUTION OF GENETIC VARIATION

Persistence in the face of climate change is likely determined by life history characteristics: dispersal ability, generation time, reproductive ability, degree of habitat specialization, plant-insect interactions, existing genetic diversity and availability of habitat or migration corridors. Existing levels of genetic diversity in plant populations vary based on a number of evolutionary scenarios that include endemism, expansion since the last glacial maximum, breeding system and current range sizes.

REGIONAL PRIORITIES AND EXAMPLES

A number of well-documented examples are provided from the California Floristic Province. Some predictions can be made for the responses of plant taxa to rapid environmental changes based on geographic position, evolutionary history, existing genetic variation, and ecological amplitude.

CONCLUSIONS, SOLUTIONS AND RECOMMENDATIONS

The prediction of how species will respond to climate change will require a synthesis drawing from population genetics, geography, palaeontology and ecology. The important integration of the historical factors that have shaped the distribution and existing genetic structure of California's plant taxa will enable us to predict and prioritize the conservation of species and areas most likely to be impacted by rapid climate change, human disturbance and invasive species.

When Climate Reshuffles Competitors: A Call for Experimental Macroecology

Climate change will likely reshuffle ecological communities, causing novel species interactions that could profoundly influence how populations and communities respond to changing conditions. Nonetheless, predicting the impacts of novel interactions is challenging, partly because many methods of inference are contingent on the current configuration of climatic variables and species distributions. Focusing on competition, we argue that experiments designed to quantify novel interactions in ways that can inform species distribution models are urgently needed, and suggest an empirical agenda to pursue this goal, illustrated using plants. An emerging convergence of ideas from macroecology and demographically focused competition theory offers opportunities to mechanistically incorporate competition into species distribution models, while forging closer ties between experimental ecology and macroecology.

Extreme climate events counteract the effects of climate and land-use changes in Alpine treelines

1. Climate change and extreme events, such as drought, threaten ecosystems worldwide and in particular mountain ecosystems, where species often live at their environmental tolerance limits. In the European Alps, plant communities are also influenced by land-use abandonment leading to woody encroachment of subalpine and alpine grasslands. 2. In this study, we explored how the forest-grassland ecotone of Alpine treelines will respond to gradual climate warming, drought events and land-use change in terms of forest expansion rates, taxonomic diversity and functional composition. We used a previously validated dynamic vegetation model, FATE-HD, parameterised for plant communities in the Ecrins National Park in the French Alps. 3. Our results showed that intense drought counteracted the forest expansion at higher elevations driven by land-use abandonment and climate change, especially when combined with high drought frequency (occurring every 2 or less than 2 years). 4. Furthermore, intense and frequent drought accelerated the rates of taxonomic change and resulted in overall higher taxonomic spatial heterogeneity of the ecotone than would be expected under gradual climate and land-use changes only. 5. Synthesis and applications. The results from our model show that intense and frequent drought counteracts forest expansion driven by climate and land-use changes in the forest-grassland ecotone of Alpine treelines. We argue that land-use planning must consider the effects of extreme events, such as drought, as well as climate and land-use changes, since extreme events might interfere with trends predicted under gradual climate warming and agricultural abandonment.

N-dimensional hypervolumes to study stability of complex ecosystems

Although our knowledge on the stabilising role of biodiversity and on how it is affected by perturbations has greatly improved, we still lack a comprehensive view on ecosystem stability that is transversal to different habitats and perturbations. Hence, we propose a framework that takes advantage of the multiplicity of components of an ecosystem and their contribution to stability. Ecosystem components can range from species or functional groups, to different functional traits, or even the cover of different habitats in a landscape mosaic. We make use of n-dimensional hypervolumes to define ecosystem states and assess how much they shift after environmental changes have occurred. We demonstrate the value of this framework with a study case on the effects of environmental change on Alpine ecosystems. Our results highlight the importance of a multidimensional approach when studying ecosystem stability and show that our framework is flexible enough to be applied to different types of ecosystem components, which can have important implications for the study of ecosystem stability and transient dynamics.

Global change and terrestrial plant community dynamics

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework

AIM

Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods.

LOCATION

Eastern North America (as an example).

METHODS

Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America.

RESULTS

For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model.

MAIN CONCLUSIONS

We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making.