Paul W. Leadley

Impacts of climate change on the future of biodiversity

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g. phenology), space (e.g. range) and self (e.g. physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesise their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth.

A mid-term analysis of progress toward international biodiversity targets

In 2010, the international community, under the auspices of the Convention on Biological Diversity, agreed on 20 biodiversity-related “Aichi Targets” to be achieved within a decade. We provide a comprehensive mid-term assessment of progress toward these global targets using 55 indicator data sets. We projected indicator trends to 2020 using an adaptive statistical framework that incorporated the specific properties of individual time series. On current trajectories, results suggest that despite accelerating policy and management responses to the biodiversity crisis, the impacts of these efforts are unlikely to be reflected in improved trends in the state of biodiversity by 2020. We highlight areas of societal endeavor requiring additional efforts to achieve the Aichi Targets, and provide a baseline against which to assess future progress. Although conservation efforts are accelerating, their impact is unlikely to improve the global state of biodiversity by 2020. Indicators of progress and decline The targets set by the Convention on Biological Diversity in 2010 focused international efforts to alleviate global biodiversity decline. However, many of the consequences of these efforts will not be evident by the 2020 deadline agreed to by governments of 150 countries. Tittensor et al. analyzed data on 55 different biodiversity indicators to predict progress toward the 2020 targets—indicators such as protected area coverage, land-use trends, and endangered species status. The analysis pinpoints the problems and areas that will need the most attention in the next few years. Science, this issue p. 241

Global change, nitrification, and denitrification: A review

We reviewed responses of nitrification, denitrification, and soil N2O efflux to elevated CO2, N availability, and temperature, based on published experimental results. We used meta-analysis to estimate the magnitude of response of soil N2O emissions, nitrifying enzyme activity (NEA), denitrifying enzyme activity (DEA), and net and gross nitrification across experiments. We found no significant overall effect of elevated CO2 on N2O fluxes. DEA and NEA significantly decreased at elevated CO2; however, gross nitrification was not modified by elevated CO2, and net nitrification increased. The negative overall response of DEA to elevated CO2 was associated with decreased soil [NO3-], suggesting that reduced availability of electron acceptors may dominate the responses of denitrification to elevated CO2. N addition significantly increased field and laboratory N2O emissions, together with gross and net nitrification, but the effect of N addition on field N2O efflux was not correlated to the amount of N added. The effects of elevated temperature on DEA, NEA, and net nitrification were not significant: The small number of studies available stress the need for more warming experiments in the field. While N addition had large effects on measurements of nitrification and denitrification, the effects of elevated CO2 were less pronounced and more variable, suggesting that increased N deposition is likely to affect belowground N cycling with a magnitude of change that is much larger than that caused by elevated CO2.

Improving the forecast for biodiversity under climate change

BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans. Emerging models are beginning to incorporate six key biological mechanisms that can improve predictions of biological responses to climate change. Models that include biological mechanisms have been used to project (clockwise from top) the evolution of disease-harboring mosquitoes, future environments and land use, physiological responses of invasive species such as cane toads, demographic responses of penguins to future climates, climate-dependent dispersal behavior in butterflies, and mismatched interactions between butterflies and their host plants. Despite these modeling advances, we seldom have the detailed data needed to build these models, necessitating new efforts to collect the relevant data to parameterize more biologically realistic predictive models. New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species’ responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity.

A field study of the effects of elevated CO2 on plant biomass and community structure in a calcareous grassland

Abstract The effects of elevated CO2 on plant biomass and community structure have been studied for four seasons in a calcareous grassland in northwest Switzerland. This highly diverse, semi-natural plant community is dominated by the perennial grass Bromus erectus and is mown twice a year to maintain species composition. Plots of 1.3 m2 were exposed to ambient or elevated CO2 concentrations (n = 8) using a novel CO2 exposure technique, screen-aided CO2 control (SACC) starting in March 1994. In the 1st year of treatment, the annual harvested biomass (sum of aboveground biomass from mowings in June and October) was not significantly affected by elevated CO2. However, biomass increased significantly at elevated CO2 in the 2nd (+20%, P = 0.05), 3rd (+21%, P = 0.02) and 4th years (+29%, P = 0.02). There were no detectable differences in root biomass in the top 8 cm of soil between CO2 treatments on eight out of nine sampling dates. There were significant differences in CO2 responsiveness between functional groups (legumes, non-leguminous forbs, graminoids) in the 2nd (P = 0.07) and 3rd (P < 0.001) years of the study. The order of CO2 responsiveness among functional groups changed substantially from the 2nd to the 3rd year; for example, non-leguminous forbs had the smallest relative response in the 2nd year and the largest in the 3rd year. By the 3rd year of CO2 exposure, large species-specific differences in CO2 response had developed. For five important species or genera the order of responsiveness was Lotus corniculatus (+271%), Carex flacca (+249%), Bromus erectus (+33%), Sanguisorba minor (no significant CO2 effect), and six Trifolium species (a negative response that was not significant). The positive CO2 responses in Bromus and Carex were most closely related to increases in tiller number. Species richness was not affected by CO2 treatment, but species evenness increased under elevated CO2 (modified Hill ratio; P = 0.03) in June of the 3rd year, resulting in a marginally significant increase in species diversity (Simpsons index; P = 0.09). This and other experiments with calcareous grassland plants show that elevated atmospheric CO2 concentrations can substantially alter the structure of calcareous grassland communities and may increase plant community biomass.

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion.

Terrestrial and Inland Water Systems

The topics assessed in this chapter were last assessed by the IPCC in 2007, principally in WGII AR4 Chapters 3 (Kundzewicz et al., 2007) and 4 (Fischlin et al., 2007), but also in WGII AR4 Sections 1.3.4 and 1.3.5 (Rosenzweig et al., 2007). The WGII AR4 SPM stated “Observational evidence from all continents and most oceans shows that many natural systems are being affected by regional climate changes, particularly temperature increases,” though they noted that documentation of observed changes in tropical regions and the Southern Hemisphere was sparse (Rosenzweig et al., 2007). Fischlin et al. (2007) found that 20 to 30% of the plant and animal species that had been assessed to that time were considered to be at increased risk of extinction if the global average temperature increase exceeds 2°C to 3°C above the preindustrial level with medium confidence, and that substantial changes in structure and functioning of terrestrial, marine, and other aquatic ecosystems are very likely under that degree of warming and associated atmospheric CO2 concentration. No time scale was associated with these findings. The carbon stocks in terrestrial ecosystems were considered to be at high risk from climate change and land use change. The report warned that the capacity of ecosystems to adapt naturally to the combined effect of climate change and other stressors is likely to be exceeded if greenhouse gas (GHG) emission continued at or above the then-current rate.

No consistent effects of plant diversity on root biomass, soil biota and soil abiotic conditions in temperate grassland communities

Abstract We examined the effects of decreasing plant diversity and functional group identity on root biomass, soil bulk density, soil nitrate and ammonium concentrations, microbial basal respiration, density of predaceous and non-predaceous nematodes, earthworm biomass and density and Shannon–Wiener indices of earthworm diversity in a temperate grassland. Plant species and functional group diversity did not have significant effects on any of these measured variables. However, functional group identity of the plants did significantly affect root biomass and soil abiotic factors. In addition, root biomass, Shannon–Wiener indices of earthworm diversity and density of epigeic earthworms were significantly higher in the presence of legumes, while we found no correlation between functional group identity and other groups of soil biota. We also found several significant relationships among root biomass density, soil microbial basal respiration, nematodes and earthworms. Thus, how can the lack of correlation between soil variables and plant diversity manipulation be explained? Firstly, plant litter input and historical land use have long-term effects on soil properties, which suggests effects of plant diversity manipulation might only be manifested over the long-term. However, we found significant relationships between root biomass density and soil biota suggesting that changes in root biomass density with declining plant diversity could lead to changes in soil biota that might be detectable despite large temporal lags in the soil system. Secondly, we did not find significant effects of plant diversity on root biomass but we found that it was significantly related to the identity of functional groups. Thirdly, we observed complex interactions among trophic levels of soil organisms, which may counteract and buffer effects of changes in plant diversity on soil biota. Fourth, our results suggest that belowground properties might be much more influenced by the identity (and litter quality) of plant functional groups than plant species diversity per se.

REGENERATION IN GAP MODELS: PRIORITY ISSUES FOR STUDYING FOREST RESPONSES TO CLIMATE CHANGE

Recruitment algorithms in forest gap models are examined withparticular regard to their suitability for simulating forestecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seedproduction, dispersal, storage, germination and seedling establishment) is likely to result in less accurate predictionsof responses as compared to treating each stage separately. Second, the related assumptions that seeds of all species are uniformly available and that environmental conditions arehomogeneous, are likely to cause overestimates of future speciesdiversity and forest migration rates. Third, interactions between herbivores (ungulates and insect pests) and forest vegetation are a big unknown with potentially serious impactsin many regions. Possible strategies for developing better gapmodel representations for the climate-sensitive aspects of eachof these key areas are discussed. A working example of a relatively new model that addresses some of these limitations is also presented for each case. We conclude that better modelsof regeneration processes are desirable for predicting effectsof climate change, but that it is presently impossible to determine what improvements can be expected without carrying outrigorous tests for each new formulation.

SOIL CHARACTERISTICS PLAY A KEY ROLE IN MODELING NUTRIENT COMPETITION IN PLANT COMMUNITIES

Soil and nutrient properties, via their influence on nutrient diffusion rates in the soil, may play a key role in determining the outcome of plant competition for nutrients. We used two models to explore the potential contributions of nutrient uptake kinetics, root density, soil properties, and nutrient type to interspecific plant competition for soil nutrients. The first model uses well-known nutrient diffusion and absorption relationships to generate soil nutrient concentration maps and nutrient uptake at the scale of individual roots (PARIS- M). A second model (PARIS-E) was developed based on a fit of the Hill equation to the output of PARIS-M. The PARIS-E model provides an accurate and simple means of de- termining the relative contributions of sink strength (root surface area X uptake kinetics) vs. space occupation (number of roots per unit area) to competition at equilibrium as modeled by PARIS-M. An analysis based on these two models suggests the following: (1) Diffusive supply (soil nutrient buffer capacity x effective diffusion coefficient) determines the relative im- portance of space occupation vs. sink strength for nutrient competition. (2) At the low range of reported values of diffusive supply, competition depends on space occupation and, therefore, the species with the most roots per unit area is the most competitive. Sink strength gains in importance as diffusive supply increases and dominates competitive interactions at the high end of the range of reported diffusive supplies. (3) The relative importance of space occupation vs. sink strength depends primarily on soil water content and soil texture, because diffusive supply is sensitive to these factors. Diffusive supply is relatively insen- sitive to nutrient type. This analysis suggests that nutrient competition models should include the effects of soil properties as a determinant of the relative contributions of sink strength vs. space occupation.