Climate change due to greenhouse gas emissions is predicted to raise the mean global temperature by 1.0–3.5°C in the next 50–100 years. The direct and indirect effects of this potential increase in temperature on terrestrial ecosystems and ecosystem processes are likely to be complex and highly varied in time and space. The Global Change and Terrestrial Ecosystems core project of the International Geosphere-Biosphere Programme has recently launched a Network of Ecosystem Warming Studies, the goals of which are to integrate and foster research on ecosystem-level effects of rising temperature. In this paper, we use meta-analysis to synthesize data on the response of soil respiration, net N mineralization, and aboveground plant productivity to experimental ecosystem warming at 32 research sites representing four broadly defined biomes, including high (latitude or altitude) tundra, low tundra, grassland, and forest. Warming methods included electrical heat-resistance ground cables, greenhouses, vented and unvented field chambers, overhead infrared lamps, and passive night-time warming. Although results from individual sites showed considerable variation in response to warming, results from the meta-analysis showed that, across all sites and years, 2–9 years of experimental warming in the range 0.3–6.0°C significantly increased soil respiration rates by 20% (with a 95% confidence interval of 18–22%), net N mineralization rates by 46% (with a 95% confidence interval of 30–64%), and plant productivity by 19% (with a 95% confidence interval of 15–23%). The response of soil respiration to warming was generally larger in forested ecosystems compared to low tundra and grassland ecosystems, and the response of plant productivity was generally larger in low tundra ecosystems than in forest and grassland ecosystems. With the exception of aboveground plant productivity, which showed a greater positive response to warming in colder ecosystems, the magnitude of the response of these three processes to experimental warming was not generally significantly related to the geographic, climatic, or environmental variables evaluated in this analysis. This underscores the need to understand the relative importance of specific factors (such as temperature, moisture, site quality, vegetation type, successional status, land-use history, etc.) at different spatial and temporal scales, and suggests that we should be cautious in "scaling up" responses from the plot and site level to the landscape and biome level. Overall, ecosystem-warming experiments are shown to provide valuable insights on the response of terrestrial ecosystems to elevated temperature.

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A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming

Introduction.- Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- Introduction to mixed modelling.- Univariate tree models.- Measures of association.- Ordination--first encounter.- Principal component analysis and redundancy analysis.- Correspondence analysis and canonical correspondence analysis.- Introduction to discriminant analysis.- Principal coordinate analysis and non-metric multidimensional scaling.- Time series analysis--Introduction.- Common trends and sudden changes.- Analysis and modelling lattice data.- Spatially continuous data analysis and modelling.- Univariate methods to analyse abundance of decapod larvae.- Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugual.- Crop pollination by honeybees in an Argentinean pampas system using additive mixed modelling.- Investigating the effects of rice farming on aquatic birds with mixed modelling.- Classification trees and radar detection of birds for North Sea wind farms.- Fish stock identification through neural network analysis of parasite fauna.- Monitoring for change: using generalised least squares, nonmetric multidimensional scaling, and the Mantel test on western Montana grasslands.- Univariate and multivariate analysis applied on a Dutch sandy beach community.- Multivariate analyses of South-American zoobenthic species--spoilt for choice.- Principal component analysis applied to harbour porpoise fatty acid data.- Multivariate analysis of morphometric turtle data--size and shape.- Redundancy analysis and additive modelling applied on savanna tree data.- Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico.- Estimating common trends in Portuguese fisheries landings.- Common trends in demersal communities on the Newfoundland-Labrador Shelf.- Sea level change and salt marshes in the Wadden Sea: a time series analysis.- Time series analysis of Hawaiian waterbirds.- Spatial modelling of forest community features in the Volzhsko-Kamsky reserve.

Analysing Ecological Data

Root turnover is a critical component of ecosystem nutrient dynamics and carbon sequestration and is also an important sink for plant primary productivity. We tested global controls on root turnover across climatic gradients and for plant functional groups by using a database of 190 published studies. Root turnover rates increased exponentially with mean annual temperature for fine roots of grasslands (r2 = 0.48) and forests (r2 = 0.17) and for total root biomass in shrublands (r2 = 0.55). On the basis of the best-fit exponential model, the Q10 for root turnover was 1.4 for forest small diameter roots (5 mm or less), 1.6 for grassland fine roots, and 1.9 for shrublands. Surprisingly, after accounting for temperature, there was no such global relationship between precipitation and root turnover. The slowest average turnover rates were observed for entire tree root systems (10% annually), followed by 34% for shrubland total roots, 53% for grassland fine roots, 55% for wetland fine roots, and 56% for forest fine roots. Root turnover decreased from tropical to high-latitude systems for all plant functional groups. To test whether global relationships can be used to predict interannual variability in root turnover, we evaluated 14 yr of published root turnover data from a shortgrass steppe site in northeastern Colorado, USA. At this site there was no correlation between interannual variability in mean annual temperature and root turnover. Rather, turnover was positively correlated with the ratio of growing season precipitation and maximum monthly temperature (r2 = 0.61). We conclude that there are global patterns in rates of root turnover between plant groups and across climatic gradients but that these patterns cannot always be used for the successful prediction of the relationship of root turnover to climate change at a particular site.

https://nph.onlinelibrary.wiley.com/doi/pdf/10.1046/j.1469-8137.2000.00681.x

Global patterns of root turnover for terrestrial ecosystems

Global climate change is frequently considered a major conservation threat. The Earth's climate has already warmed by 0.5 8 C over the past century, and recent studies show that it is possible to detect the ef- fects of a changing climate on ecological systems. This suggests that global change may be a current and fu- ture conservation threat. Changes in recent decades are apparent at all levels of ecological organization: pop- ulation and life-history changes, shifts in geographic range, changes in species composition of communities, and changes in the structure and functioning of ecosystems. These ecological effects can be linked to recent population declines and to both local and global extinctions of species. Although it is impossible to prove that climate change is the cause of these ecological effects, these findings have important implications for conser- vation biology. It is no longer safe to assume that all of a species' historic range remains suitable. In drawing attention to the importance of climate change as a current threat to species, these studies emphasize the need for current conservation efforts to consider climate change in both in situ conservation and reintroduction efforts. Additional threats will emerge as climate continues to change, especially as climate interacts with other stressors such as habitat fragmentation. These studies can contribute to preparations for future chal- lenges by providing valuable input to models and direct examples of how species respond to climate change.

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Ecological Consequences of Recent Climate Change

[1] The global distribution of C3 and C4 plants is required for accurately simulating exchanges of CO2, water, and energy between the land surface and atmosphere. It is also important to know the C3/C4 distribution for simulations of the carbon isotope composition of atmospheric CO2 owing to the distinct fractionations displayed by each photosynthetic type. Large areas of the land surface are spatial and temporal mosaics of both photosynthetic types. We developed an approach for capturing this heterogeneity by combining remote sensing products, physiological modeling, a spatial distribution of global crop fractions, and national harvest area data for major crop types. Our C3/C4 distribution predicts the global coverage of C4 vegetation to be 18.8 million km2, while C3 vegetation covers 87.4 million km2. We incorporated our distribution into the SiB2 model and simulated carbon fluxes for each photosynthetic type. The gross primary production (GPP) of C4 plants is 35.3 Pg C yr−1, or ∼23% of total GPP, while that of C3 plants is 114.7 Pg C yr−1. The assimilation-weighted terrestrial discrimination against 13CO2 is −16.5‰. If the terrestrial component of the carbon sink is proportional to GPP, this implies a net uptake of 2.4 Pg C yr−1 on land and 1.4 Pg C yr−1 in the ocean using a 13C budgeting approach and average carbon cycle parameter values for the 1990s. We also simulated the biomass of each photosynthetic type using the CASA model. The simulated biomass values of C3 and C4 vegetation are 389.3 and 18.6 Pg C, respectively.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2001GB001807

Global distribution of C3 and C4 vegetation: Carbon cycle implications

Global minimum temperatures (TMIN) are increasing faster than maximum temperatures, but the ecological consequences of this are largely unexplored. Long-term data sets from the shortgrass steppe were used to identify correlations between TMIN and several vegetation variables. This ecosystem is potentially sensitive to increases in TMIN. Most notably, increased spring TMIN was correlated with decreased net primary production by the dominant C4 grass (Bouteloua gracilis) and with increased abundance and production by exotic and native C3 forbs. Reductions in B. gracilis may make this system more vulnerable to invasion by exotic species and less tolerant of drought and grazing.

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Richard D. Alward

Papers

Grassland vegetation changes and nocturnal global warming