Global Change Biology

The effects of land use change on soil carbon stocks are of concern in the context of international policy agendas on greenhouse gas emissions mitigation. This paper reviews the literature for the influence of land use changes on soil C stocks and reports the results of a meta analysis of these data from 74 publications. The meta analysis indicates that soil C stocks decline after land use changes from pasture to plantation (−10%), native forest to plantation (−13%), native forest to crop (−42%), and pasture to crop (−59%). Soil C stocks increase after land use changes from native forest to pasture (+ 8%), crop to pasture (+ 19%), crop to plantation (+ 18%), and crop to secondary forest (+ 53%). Wherever one of the land use changes decreased soil C, the reverse process usually increased soil carbon andvice versa. As the quantity of available data is not large and the methodologies used are diverse, the conclusions drawn must be regarded as working hypotheses from which to design future targeted investigations that broaden the database. Within some land use changes there were, however, sufficient examples to explore the role of other factors contributing to the above conclusions. One outcome of the meta analysis, especially worthy of further investigation in the context of carbon sink strategies for greenhouse gas mitigation, is that broadleaf tree plantations placed onto prior native forest or pastures did not affect soil C stocks whereas pine plantations reduced soil C stocks by 12–15%.

This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration (R_eco). In particular, we analyse the effect of the extrapolation of night‐time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long‐term data sets. For this analysis, we used 16 one‐year‐long data sets of carbon dioxide exchange measurements from European and US‐American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems.

We show that the temperature sensitivity of R_eco, derived from long‐term (annual) data sets, does not reflect the short‐term temperature sensitivity that is effective when extrapolating from night‐ to daytime. Specifically, in summer active ecosystems the long‐term temperature sensitivity exceeds the short‐term sensitivity. Thus, in those ecosystems, the application of a long‐term temperature sensitivity to the extrapolation of respiration from night to day leads to a systematic overestimation of ecosystem respiration from half‐hourly to annual time‐scales, which can reach >25% for an annual budget and which consequently affects estimates of GEP. Conversely, in summer passive (Mediterranean) ecosystems, the long‐term temperature sensitivity is lower than the short‐term temperature sensitivity resulting in underestimation of annual sums of respiration.

We introduce a new generic algorithm that derives a short‐term temperature sensitivity of R_eco from eddy covariance data that applies this to the extrapolation from night‐ to daytime, and that further performs a filling of data gaps that exploits both, the covariance between fluxes and meteorological drivers and the temporal structure of the fluxes. While this algorithm should give less biased estimates of GEP and R_eco, we discuss the remaining biases and recommend that eddy covariance measurements are still backed by ancillary flux measurements that can reduce the uncertainties inherent in the eddy covariance data.

Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high‐temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single‐site or single‐species studies are particularly open to suspicion of being biased towards predominantly reporting climate change‐induced impacts. No comprehensive study or meta‐analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade⁻¹ in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species' phenology is responsive to temperature of the preceding months (mean advance of spring/summer by 2.5 days°C⁻¹, delay of leaf colouring and fall by 1.0 day°C⁻¹). The pattern of observed change in spring efficiently matches measured national warming across 19 European countries (correlation coefficient r=−0.69, P<0.001).

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy‐in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log‐normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait‐based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

The decomposition and transformation of above‐ and below‐ground plant detritus (litter) is the main process by which soil organic matter (SOM) is formed. Yet, research on litter decay and SOM formation has been largely uncoupled, failing to provide an effective nexus between these two fundamental processes for carbon (C) and nitrogen (N) cycling and storage. We present the current understanding of the importance of microbial substrate use efficiency and C and N allocation in controlling the proportion of plant‐derived C and N that is incorporated into SOM, and of soil matrix interactions in controlling SOM stabilization. We synthesize this understanding into the Microbial Efficiency‐Matrix Stabilization (MEMS) framework. This framework leads to the hypothesis that labile plant constituents are the dominant source of microbial products, relative to input rates, because they are utilized more efficiently by microbes. These microbial products of decomposition would thus become the main precursors of stable SOM by promoting aggregation and through strong chemical bonding to the mineral soil matrix.

Variation in soil temperature can account for most of the seasonal and diel variation in soil CO₂ efflux, but the temperature effect is not always consistent, and other factors such as soil water content are known to influence soil respiration. The objectives of this research were to study the spatial and temporal variation in soil respiration in a temperate forested landscape and to evaluate temperature and soil water functions as predictors of soil respiration. Soil CO₂ fluxes were measured with chambers throughout an annual cycle in six study areas at the Harvard Forest in central Massachusetts that include soil drainage classes from well drained to very poorly drained. The mean annual estimate of soil CO₂ efflux was 7.2 Mg ha^–1, but ranged from 5.3 in the swamp site to 8.5 in a well‐drained site, indicating that landscape heterogeneity is related to soil drainage class. An exponential function relating CO₂ fluxes to soil temperature accounted for 80% of the seasonal variation in fluxes across all sites (Q₁₀ = 3.9), but the Q₁₀ ranged from 3.4 to 5.6 for the individual study sites. A significant drought in 1995 caused rapid declines in soil respiration rates in August and September in five of the six sites (a swamp site was the exception). This decline in CO₂ fluxes correlated exponentially with decreasing soil matric potential, indicating a mechanistic effect of drought stress. At moderate to high water contents, however, soil water content was negatively correlated with soil temperature, which precluded distinguishing between the effects of these two confounded factors on CO₂ flux. Occurrence of high Q₁₀ values and variation in Q₁₀ values among sites may be related to: (i) confounding effects of high soil water content; (ii) seasonal and diel patterns in root respiration and turnover of fine roots that are linked to above ground phenology and metabolism; and (iii) variation in the depth where CO₂ is produced. The Q₁₀ function can yield reasonably good predictions of annual fluxes of CO₂, but it is a simplification that masks responses of root and microbial processes to variation in temperature and water content throughout the soil.

Microplastics (plastics <5 mm, including nanoplastics which are <0.1 μm) originate from the fragmentation of large plastic litter or from direct environmental emission. Their potential impacts in terrestrial ecosystems remain largely unexplored despite numerous reported effects on marine organisms. Most plastics arriving in the oceans were produced, used, and often disposed on land. Hence, it is within terrestrial systems that microplastics might first interact with biota eliciting ecologically relevant impacts. This article introduces the pervasive microplastic contamination as a potential agent of global change in terrestrial systems, highlights the physical and chemical nature of the respective observed effects, and discusses the broad toxicity of nanoplastics derived from plastic breakdown. Making relevant links to the fate of microplastics in aquatic continental systems, we here present new insights into the mechanisms of impacts on terrestrial geochemistry, the biophysical environment, and ecotoxicology. Broad changes in continental environments are possible even in particle‐rich habitats such as soils. Furthermore, there is a growing body of evidence indicating that microplastics interact with terrestrial organisms that mediate essential ecosystem services and functions, such as soil dwelling invertebrates, terrestrial fungi, and plant‐pollinators. Therefore, research is needed to clarify the terrestrial fate and effects of microplastics. We suggest that due to the widespread presence, environmental persistence, and various interactions with continental biota, microplastic pollution might represent an emerging global change threat to terrestrial ecosystems.

Evidence is accumulating of shifts in species' distributions during recent climate warming. However, most of this information comes predominantly from studies of a relatively small selection of taxa (i.e., plants, birds and butterflies), which may not be representative of biodiversity as a whole. Using data from less well‐studied groups, we show that a wide variety of vertebrate and invertebrate species have moved northwards and uphill in Britain over approximately 25 years, mirroring, and in some cases exceeding, the responses of better‐known groups.

Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground‐ and remote sensing‐ based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process‐based phenology modeling, and on the scaling of phenology from species to landscape‐level.

New analyses are presented addressing the global impacts of recent climate change on phenology of plant and animal species. A meta‐analysis spanning 203 species was conducted on published datasets from the northern hemisphere. Phenological response was examined with respect to two factors: distribution of species across latitudes and taxonomic affiliation or functional grouping of target species. Amphibians had a significantly stronger shift toward earlier breeding than all other taxonomic/functional groups, advancing more than twice as fast as trees, birds and butterflies. In turn, butterfly emergence or migratory arrival showed three times stronger advancement than the first flowering of herbs, perhaps portending increasing asynchrony in insect–plant interactions. Response was significantly stronger at higher latitudes where warming has been stronger, but latitude explained < 4% of the variation. Despite expectation, latitude was not yet an important predictor of climate change impacts on phenology. The only two previously published estimates of the magnitude of global response are quite different: 2.3 and 5.1 days decade⁻¹ advancement. The scientific community has assumed this difference to be real and has attempted to explain it in terms of biologically relevant phenomena: specifically, differences in distribution of data across latitudes, taxa or time periods. Here, these and other possibilities are explored. All analyses indicate that the difference in estimated response is primarily due to differences between the studies in criteria for incorporating data. It is a clear and automatic consequence of the exclusion by one study of data on ‘stable’ (nonresponsive) species. Once this is accounted for, the two studies support each other, generating similar conclusions despite analyzing substantially nonoverlapping datasets. Analyses here on a new expanded dataset estimate an overall spring advancement across the northern hemisphere of 2.8 days decade⁻¹. This is the first quantitative analysis showing that data‐sampling methodologies significantly impact global (synthetic) estimates of magnitude of global warming response.