A global assessment of forest surface albedo and its relationships with climate and atmospheric nitrogen deposition

We present a global assessment of the relationships between the short‐wave surface albedo of forests, derived from the MODIS satellite instrument product at 0.5° spatial resolution, with simulated atmospheric nitrogen deposition rates (N_dep), and climatic variables (mean annual temperature T_m and total annual precipitation P), compiled at the same spatial resolution. The analysis was performed on the following five forest plant functional types (PFTs): evergreen needle‐leaf forests (ENF); evergreen broad‐leaf forests (EBF); deciduous needle‐leaf forests (DNF); deciduous broad‐leaf forests (DBF); and mixed‐forests (MF). Generalized additive models (GAMs) were applied in the exploratory analysis to assess the functional nature of short‐wave surface albedo relations to environmental variables. The analysis showed evident correlations of albedo with environmental predictors when data were pooled across PFTs: T_m and N_dep displayed a positive relationship with forest albedo, while a negative relationship was detected with P. These correlations are primarily due to surface albedo differences between conifer and broad‐leaf species, and different species geographical distributions. However, the analysis performed within individual PFTs, strengthened by attempts to select ‘pure’ pixels in terms of species composition, showed significant correlations with annual precipitation and nitrogen deposition, pointing toward the potential effect of environmental variables on forest surface albedo at the ecosystem level. Overall, our global assessment emphasizes the importance of elucidating the ecological mechanisms that link environmental conditions and forest canopy properties for an improved parameterization of surface albedo in climate models.     

Sensitivity of Siberian larch forests to climate change

The Northern Hemisphere's boreal forests, particularly the Siberian boreal forest, may have a strong effect on Earth's climate through changes in dominant vegetation and associated regional surface albedo. We show that warmer climate will likely convert Siberia's deciduous larch (Larix spp.) to evergreen conifer forests, and thus decrease regional surface albedo. The dynamic vegetation model, FAREAST, simulates Russian boreal forest composition and was used to explore the feedback between climate change and forest composition at continental, regional, and local scales. FAREAST was used to simulate the impact of changes in temperature and precipitation on total and genus‐level biomass at sites across Siberia and the Russian Far East (RFE), and for six high‐ and low‐diversity regions. Model runs with and without European Larch (Larix decidua) included in the available species pool were compared to assess the potential for this species, which is adapted to warmer climate conditions, to mitigate the effects of climate change, especially the shift to evergreen dominance. At the continental scale, when temperature is increased, larch‐dominated sites become vulnerable to early replacement by evergreen conifers. At the regional and local scales, the diverse Amur region of the RFE does not show a strong response to climate change, but the low‐diversity regions in central and southern Siberia have an abrupt vegetation shift from larch‐dominated forest to evergreen‐conifer forest in response to increased temperatures. The introduction of L. decidua prevents the collapse of larch in these low‐diversity areas and thus mitigates the response to warming. Using contemporary MODIS albedo measurements, we determined that a conversion from larch to evergreen stands in low‐diversity regions of southern Siberia would generate a local positive radiative forcing of 5.1±2.6 W m^?2. This radiative heating would reinforce the warming projected to occur in the area under climate change.     

The Effects of Adjacent Land Use on Nitrogen Dynamics at Forest Edges in Northern Idaho

The effects of immediately adjacent agricultural fertilization on nitrogen (N) at upland forest edges have not been previously studied. Our objective was to determine whether N from fertilized agriculture enters northern Idaho forest edges and significantly impacts their N status. We stratified 27 forest edge sampling sites by the N fertilization history of the adjacent land: current, historical, and never. We measured N stable isotopes (δ¹⁵N), N concentration (%N), and carbon-to-nitrogen (C/N) ratios of conifer tree and deciduous shrub foliage, shrub roots, and bulk soil, as well as soil available N. Conifer foliage δ¹⁵N and %N, shrub root δ¹⁵N, and bulk soil N were greater and soil C/N ratios lower (P < 0.05) at forest edges than interiors, regardless of adjacent fertilization history. For shrub foliage and bulk soil δ¹⁵N, shrub root %N and C/N ratios, and soil nitrate, significant edge–interior differences were limited to forests bordering lands that had been fertilized currently or historically. Foliage and soil δ¹⁵N were most enriched at forest edges bordering currently fertilized agriculture, suggesting that these forests are receiving N fertilizer inputs. Shrub root %N was greater at forest edges bordering currently fertilized agriculture than at those bordering grasslands that had never been fertilized (P = 0.01). Elevated N at forest edges may increase vegetation growth, as well as susceptibility to disease and insects. The higher N we found at forest edges bordering agriculture may also be found elsewhere, given similar agricultural practices in other regions and the prevalence of forest fragmentation.     

An improved approach for remotely sensing water stress impacts on forest C uptake

Given that forests represent the primary terrestrial sink for atmospheric CO₂, projections of future carbon (C) storage hinge on forest responses to climate variation. Models of gross primary production (GPP) responses to water stress are commonly based on remotely sensed changes in canopy ‘greenness’ (e.g., normalized difference vegetation index; NDVI). However, many forests have low spectral sensitivity to water stress (SSWS) – defined here as drought‐induced decline in GPP without a change in greenness. Current satellite‐derived estimates of GPP use a vapor pressure deficit (VPD) scalar to account for the low SWSS of forests, but fail to capture their responses to water stress. Our objectives were to characterize differences in SSWS among forested and nonforested ecosystems, and to develop an improved framework for predicting the impacts of water stress on GPP in forests with low SSWS. First, we paired two independent drought indices with NDVI data for the conterminous US from 2000 to 2011, and examined the relationship between water stress and NDVI. We found that forests had lower SSWS than nonforests regardless of drought index or duration. We then compared satellite‐derived estimates of GPP with eddy‐covariance observations of GPP in two deciduous broadleaf forests with low SSWS: the Missouri Ozark (MO) and Morgan Monroe State Forest (MMSF) AmeriFlux sites. Model estimates of GPP that used VPD scalars were poorly correlated with observations of GPP at MO (r² = 0.09) and MMSF (r² = 0.38). When we included the NDVI responses to water stress of adjacent ecosystems with high SSWS into a model based solely on temperature and greenness, we substantially improved predictions of GPP at MO (r² = 0.83) and for a severe drought year at the MMSF (r² = 0.82). Collectively, our results suggest that large‐scale estimates of GPP that capture variation in SSWS among ecosystems could improve predictions of C uptake by forests under drought.     

Climate change decreases the cooling effect from postfire albedo in boreal North America

Fire is a primary disturbance in boreal forests and generates both positive and negative climate forcings. The influence of fire on surface albedo is a predominantly negative forcing in boreal forests, and one of the strongest overall, due to increased snow exposure in the winter and spring months. Albedo forcings are spatially and temporally heterogeneous and depend on a variety of factors related to soils, topography, climate, land cover/vegetation type, successional dynamics, time since fire, season, and fire severity. However, how these variables interact to influence albedo is not well understood, and quantifying these relationships and predicting postfire albedo becomes increasingly important as the climate changes and management frameworks evolve to consider climate impacts. Here we developed a MODIS‐derived ‘blue sky’ albedo product and a novel machine learning modeling framework to predict fire‐driven changes in albedo under historical and future climate scenarios across boreal North America. Converted to radiative forcing (RF), we estimated that fires generate an annual mean cooling of ?1.77 ± 1.35 W/m² from albedo under historical climate conditions (1971–2000) integrated over 70 years postfire. Increasing postfire albedo along a south–north climatic gradient was offset by a nearly opposite gradient in solar insolation, such that large‐scale spatial patterns in RF were minimal. Our models suggest that climate change will lead to decreases in mean annual postfire albedo, and hence a decreasing strength of the negative RF, a trend dominated by decreased snow cover in spring months. Considering the range of future climate scenarios and model uncertainties, we estimate that for fires burning in the current era (2016) the cooling effect from long‐term postfire albedo will be reduced by 15%–28% due to climate change.     

Leaf life span as a simple predictor of evergreen forest zonation in China

Aim Our aim was to investigate how the average life span of canopy leaves might be used to predict the geographical distribution of natural forests at large geographical scales, and to explore the link between leaf characteristics and ecosystem functioning. We examine whether there is a general relationship between canopy mean leaf life span and climate (i.e. temperature and precipitation) that can be used to predict evergreen forest zonation in China. Location Forest areas in China. Methods During July and August of 2002–2004, we conducted a latitudinal forest transect spanning about 30° of latitude in eastern China. The canopy mean leaf life span was calculated to include all tree species (groups) in each forest plot through weighted averages scaled up from branch‐level measurements. Data from our previous work conducted in the Tibetan Alpine Vegetation Transects (TAVT) and from other investigators were compiled to supplement our results. Based on regression equations developed on the pooled data, and using gridded temperature and precipitation datasets, we simulated the distribution of canopy mean leaf life span for forests in China. The predicted leaf life span zonation was compared with a map of Chinese forest vegetation divisions published in 1980. Results Canopy mean leaf life span across 10 evergreen forest plots in eastern China showed a decreasing trend as mean annual temperature increased, following a common logistic pattern consistent with the data from the TAVT and other investigators. In pooled data for 40 evergreen forest plots across tropical and boreal regions, canopy mean leaf life span generally showed a negative relationship with mean annual temperature (r² = 0.72, P < 0.001), and a positive correlation with mean annual precipitation where mean annual temperature was > 8°C (r² = 0.45, P < 0.01). The climate‐based simulations of leaf life span zonation compared well with the previously published boundaries of forest vegetation divisions in eastern China. Main conclusions Our results reveal that mean leaf life span in evergreen forests follows a common logistic pattern associated with mean annual temperature and precipitation, which can in turn be used to predict evergreen forest zonation in eastern China.     

Phenological influences on the albedo of prairie grassland and crop fields

 The albedo of land surfaces is strongly affected by transient surface conditions. For a vegetated surface, albedo can change with soil moisture, fractional canopy cover, and plant phenology as well as solar zenith angle (θ_s). In this study, the relationships between albedo and plant phenology in prairie grassland and agricultural crops were examined by removing the effect of variations in θ_s. Albedos were evaluated at a constant θ_s, which was assigned to be 20° in this study. For days with a minimum θ_s larger than 20°, a polynomial function that relates albedos to θ_s was derived and applied to estimate the albedos at 20°. After the removal of θ_s variations, the observed albedos of grassland at the Konza Prairie showed a linearly decreasing trend from spring to winter due to prairie phenology. The observed albedo of a maize field showed a clear increase from seedling to peak green stage, except when drought caused a decrease in near-infrared reflectance. The observed albedos of a winter wheat field showed an uninterrupted decrease from peak green to harvesting stage. Received: 30 May 1998 / Accepted 15 July1998     

Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO₂ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO₂ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr^?1 for CASA′ vs. 1.2 Pg C yr^?1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.     

Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa

BIOME 6000 is an international project to map vegetation globally at mid‐Holocene (6000 ¹⁴C yr bp ) and last glacial maximum (LGM, 18,000 ¹⁴C yr bp ), with a view to evaluating coupled climate‐biosphere model results. Primary palaeoecological data are assigned to biomes using an explicit algorithm based on plant functional types. This paper introduces the second Special Feature on BIOME 6000. Site‐based global biome maps are shown with data from North America, Eurasia (except South and Southeast Asia) and Africa at both time periods. A map based on surface samples shows the method’s skill in reconstructing present‐day biomes. Cold and dry conditions at LGM favoured extensive tundra and steppe. These biomes intergraded in northern Eurasia. Northern hemisphere forest biomes were displaced southward. Boreal evergreen forests (taiga) and temperate deciduous forests were fragmented, while European and East Asian steppes were greatly extended. Tropical moist forests (i.e. tropical rain forest and tropical seasonal forest) in Africa were reduced. In south‐western North America, desert and steppe were replaced by open conifer woodland, opposite to the general arid trend but consistent with modelled southward displacement of the jet stream. The Arctic forest limit was shifted slighly north at 6000 ¹⁴C yr bp in some sectors, but not in all. Northern temperate forest zones were generally shifted greater distances north. Warmer winters as well as summers in several regions are required to explain these shifts. Temperate deciduous forests in Europe were greatly extended, into the Mediterranean region as well as to the north. Steppe encroached on forest biomes in interior North America, but not in central Asia. Enhanced monsoons extended forest biomes in China inland and Sahelian vegetation into the Sahara while the African tropical rain forest was also reduced, consistent with a modelled northward shift of the ITCZ and a more seasonal climate in the equatorial zone. Palaeobiome maps show the outcome of separate, independent migrations of plant taxa in response to climate change. The average composition of biomes at LGM was often markedly different from today. Refugia for the temperate deciduous and tropical rain forest biomes may have existed offshore at LGM, but their characteristic taxa also persisted as components of other biomes. Examples include temperate deciduous trees that survived in cool mixed forest in eastern Europe, and tropical evergreen trees that survived in tropical seasonal forest in Africa. The sequence of biome shifts during a glacial‐interglacial cycle may help account for some disjunct distributions of plant taxa. For example, the now‐arid Saharan mountains may have linked Mediterranean and African tropical montane floras during enhanced monsoon regimes. Major changes in physical land‐surface conditions, shown by the palaeobiome data, have implications for the global climate. The data can be used directly to evaluate the output of coupled atmosphere‐biosphere models. The data could also be objectively generalized to yield realistic gridded land‐surface maps, for use in sensitivity experiments with atmospheric models. Recent analyses of vegetation‐climate feedbacks have focused on the hypothesized positive feedback effects of climate‐induced vegetation changes in the Sahara/Sahel region and the Arctic during the mid‐Holocene. However, a far wider spectrum of interactions potentially exists and could be investigated, using these data, both for 6000 ¹⁴C yr bp and for the LGM.     

Climate warming feedback from mountain birch forest expansion: reduced albedo dominates carbon uptake

Expanding high‐elevation and high‐latitude forest has contrasting climate feedbacks through carbon sequestration (cooling) and reduced surface reflectance (warming), which are yet poorly quantified. Here, we present an empirically based projection of mountain birch forest expansion in south‐central Norway under climate change and absence of land use. Climate effects of carbon sequestration and albedo change are compared using four emission metrics. Forest expansion was modeled for a projected 2.6 °C increase in summer temperature in 2100, with associated reduced snow cover. We find that the current (year 2000) forest line of the region is circa 100 m lower than its climatic potential due to land‐use history. In the future scenarios, forest cover increased from 12% to 27% between 2000 and 2100, resulting in a 59% increase in biomass carbon storage and an albedo change from 0.46 to 0.30. Forest expansion in 2100 was behind its climatic potential, forest migration rates being the primary limiting factor. In 2100, the warming caused by lower albedo from expanding forest was 10 to 17 times stronger than the cooling effect from carbon sequestration for all emission metrics considered. Reduced snow cover further exacerbated the net warming feedback. The warming effect is considerably stronger than previously reported for boreal forest cover, because of the typically low biomass density in mountain forests and the large changes in albedo of snow‐covered tundra areas. The positive climate feedback of high‐latitude and high‐elevation expanding forests with seasonal snow cover exceeds those of afforestation at lower elevation, and calls for further attention of both modelers and empiricists. The inclusion and upscaling of these climate feedbacks from mountain forests into global models is warranted to assess the potential global impacts.     

Higher climate warming sensitivity of Siberian larch in small than large forest islands in the fragmented Mongolian forest steppe

Forest fragmentation has been found to affect biodiversity and ecosystem functioning in multiple ways. We asked whether forest size and isolation in fragmented woodlands influences the climate warming sensitivity of tree growth in the southern boreal forest of the Mongolian Larix sibirica forest steppe, a naturally fragmented woodland embedded in grassland, which is highly affected by warming, drought, and increasing anthropogenic forest destruction in recent time. We examined the influence of stand size and stand isolation on the growth performance of larch in forests of four different size classes located in a woodland‐dominated forest‐steppe area and small forest patches in a grassland‐dominated area. We found increasing climate sensitivity and decreasing first‐order autocorrelation of annual stemwood increment with decreasing stand size. Stemwood increment increased with previous year's June and August precipitation in the three smallest forest size classes, but not in the largest forests. In the grassland‐dominated area, the tree growth dependence on summer rainfall was highest. Missing ring frequency has strongly increased since the 1970s in small, but not in large forests. In the grassland‐dominated area, the increase was much greater than in the forest‐dominated landscape. Forest regeneration decreased with decreasing stand size and was scarce or absent in the smallest forests. Our results suggest that the larch trees in small and isolated forest patches are far more susceptible to climate warming than in large continuous forests pointing to a grim future for the forests in this strongly warming region of the boreal forest that is also under high land use pressure.     

A multi‐Gaussian model for predicting crawler occurrence of Unaspis yanonensis in citrus orchards

Arrowhead scale, Unaspis yanonensis (Kuwana) (Hemiptera: Diaspididae), feeds on the foliage, stems, and fruits of citrus trees and causes tree dieback when heavy infestations occur. Multi‐Gaussian models (three‐ and two‐peak models) were developed for better management of the arrowhead scale in citrus orchards and later validated against several field data sets. The oviposition activities observed in the laboratory were highly correlated with both models (r² = 0.88). The three peak oviposition times estimated by the three‐peak model were at 282, 500, and 694 degree‐days, based on a low threshold temperature of 13 °C. Also, the peak oviposition times of the two‐peak model were identical to the first and second peak times of the three‐peak model. Both models accurately predicted the first oviposition peak period of field populations. In the later peak period, both model outputs well predicted the actual crawler populations, except for the tail end of actual peak periods which were underestimated in the two‐peak model and overestimated in the three‐peak model. Overall, both models showed a strong robustness for correlation with actual data. The newly developed multi‐Gaussian models better described the actual population phenology of U. yanonensis than the previously published models, and either model would be useful for the management of U. yanonensis in the field.     

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem‐scale CO₂ exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long‐term measurements (emphasizing the period 2000–2006) from 10 forested sites within the AmeriFlux and Fluxnet‐Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over‐prediction of gross ecosystem photosynthesis by +160 ± 145 g C m^?2 yr^?1 during the spring transition period and +75 ± 130 g C m^?2 yr^?1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under‐predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO₂ exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere–atmosphere feedbacks and interactions in coupled global climate models.     

Modelling biome shifts and tree cover change for 2050 in West Africa

Aim Africa is expected to face severe changes in climatic conditions. Our objectives are: (1) to model trends and the extent of future biome shifts that may occur by 2050, (2) to model a trend in tree cover change, while accounting for human impact, and (3) to evaluate uncertainty in future climate projections. Location West Africa. Methods We modelled the potential future spatial distribution of desert, grassland, savanna, deciduous and evergreen forest in West Africa using six bioclimatic models. Future tree cover change was analysed with generalized additive models (GAMs). We used climate data from 17 general circulation models (GCMs) and included human population density and fire intensity to model tree cover. Consensus projections were derived via weighted averages to: (1) reduce inter‐model variability, and (2) describe trends extracted from different GCM projections. Results The strongest predicted effect of climate change was on desert and grasslands, where the bioclimatic envelope of grassland is projected to expand into the desert by an area of 2 million km². While savannas are predicted to contract in the south (by 54 ± 22 × 10⁴ km²), deciduous and evergreen forest biomes are expected to expand (64 ± 13 × 10⁴ km² and 77 ± 26 × 10⁴ km²). However, uncertainty due to different GCMs was particularly high for the grassland and the evergreen biome shift. Increasing tree cover (1–10%) was projected for large parts of Benin, Burkina Faso, Côte d’Ivoire, Ghana and Togo, but a decrease was projected for coastal areas (1–20%). Furthermore, human impact negatively affected tree cover and partly changed the direction of the projected change from increase to decrease. Main conclusions Considering climate change alone, the model results of potential vegetation (biomes) show a ‘greening’ trend by 2050. However, the modelled effects of human impact suggest future forest degradation. Thus, it is essential to consider both climate change and human impact in order to generate realistic future tree cover projections.     

Including albedo in time‐dependent LCA of bioenergy

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time‐dependent LCA, which accounts for the timing of emissions and their impacts. We employed field‐measured albedo and life cycle emissions data along with time‐dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (?T) and as GWP. The bioenergy system analysed was heat and power production from short‐rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ?T per hectare (?3.8 × 10^–11 K in year 100) and GWP₁₀₀ per MJ fuel (?12.2 g CO₂e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP₁₀₀, 36% of ?T in year 50 and 6% of ?T in year 100. Albedo dominated the short‐term temperature response (10–20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ?T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first‐order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.     

Seasonal respiration of foliage, fine roots, and woody tissues in relation to growth, tissue N, and photosynthesis

Autotrophic respiration may regulate how ecosystem productivity responds to changes in temperature, atmospheric [CO₂] and N deposition. Estimates of autotrophic respiration are difficult for forest ecosystems, because of the large amount of biomass, different metabolic rates among tissues, and seasonal variation in respiration rates. We examined spatial and seasonal patterns in autotrophic respiration in a Pinus strobus ecosystem, and hypothesized that seasonal patterns in respiration rates at a common temperature would vary with [N] for fully expanded foliage and fine roots, with photosynthesis for foliage, and with growth for woody tissues (stems, branches, and coarse roots). We also hypothesized that differences in [N] would largely explain differences in maintenance or dormant‐season respiration among tissues. For April–November, mean respiration at 15 °C varied from 1.5 to 2.8 μmol kg^?1 s^?1 for fully expanded foliage, 1.7–3.0 for growing foliage, 0.8–1.6 for fine roots, 0.6–1.1 (sapwood) for stems, 0.5–1.8 (sapwood) for branches, and 0.2–1.5 (sapwood) for coarse roots. Growing season variation in respiration for foliage produced the prior year was strongly related to [N] (r² = 0.94), but fine root respiration was not related to [N]. For current‐year needles, respiration did not covary with [N]. Night‐time foliar respiration did not vary in concert with previous‐day photosynthesis for either growing or fully expanded needles. Stem growth explained about one‐third of the seasonal variation in stem respiration (r² = 0.38), and also variation among trees (r² = 0.43). We did not determine the cause of seasonal variation in branch and coarse root respiration, but it is unlikely to be directly related to growth, as the pattern of respiration in coarse roots and branches was not synchronized with stem growth. Seasonal variations in temperature‐corrected respiration rates were not synchronized among tissues, except foliage and branches. Spatial variability in dormant‐season respiration rates was significantly related to tissue N content in foliage (r² = 0.67), stems (r² = 0.45), coarse roots (r² = 0.36), and all tissues combined (r² = 0.83), but not for fine roots and branches. Per unit N, rates for P. strobus varied from 0.22 to 3.4 μmol molN^?1 s^?1 at 15 °C, comparable to those found for other conifers. Accurate estimates of annual autotrophic respiration should reflect seasonal and spatial variation in respiration rates of individual tissues.     

北方典型农牧交错带草地开垦对地表辐射收支与水热平衡的影响

以北方典型农牧交错带草原和农田生态系统的涡度相关数据为基础,对比分析了生长季两种不同土地利用类型的辐射和水热通量之异同,揭示了草地开垦影响地表辐射收支与水热平衡的机制。结果表明:在植被生长季(5月—9月),草地开垦引起太阳总辐射增加了10.74%,短波反射辐射减少了14.20%,净辐射增加了35.16%;在水热通量方面,草地开垦引起潜热通量日积分平均值增加了0.20MJ/m~2,同时显热通量减少了0.09 MJ/m~2;生长季内地表反照率减小,表征地表吸收太阳辐射增加,有升高气温的趋势;非生长季内地表反照率增加,有降低气温趋势,此外地表反照率与土壤湿度存在负指数关系;波文比在植被生长早期和末期增加,生长旺期减小,说明草地开垦与影响着近地表大气状态,从而改变了区域气候。     

APPLIED ISSUES: Exploring the response of functional indicators of stream health to land‐use gradients

1. Broad‐scale assessment of stream health is often based on correlative relationships between catchment land‐use categories and measurements of stream biota or water chemistry. Few studies have attempted to characterise the response curves that describe how measures of ecosystem function change along gradients of catchment land use, or explored how these responses vary at broad spatial scales. 2. In autumn 2008, we conducted a survey of 84 streams in three bioregions of New Zealand to assess the sensitivity of functional indicators to three land‐use gradients: percentage of native vegetation cover, percentage of impervious cover (IC) and predicted nitrogen (N) concentration. We examined these relationships using general linear models and boosted regression trees to explore monotonic, non‐monotonic and potential threshold components of the response curves. 3. When viewing the responses to individual land‐use gradients, four of five functional indicators were positively correlated with the removal of native vegetation cover and N. In general, weaker and less responsive models were observed for the IC gradient. An analysis of the response to multiple stressors showed δ¹⁵N of primary consumers and gross primary productivity (GPP) to be the most responsive functional indicators to land‐use gradients. The multivariate models identified thresholds for change in the relationship between the functional indicators and all three land‐use gradients. Apparent thresholds were <10%IC, between 40 and 80% loss of native vegetation cover and at 0.5 and 3.2 mg L^?1 N. 4. The strength of regression models and the nature of the response curves suggest that measures of ecosystem function exhibit predictable relationships with land use. Furthermore, the responses of functional indicators varied little among three bioregions. This information provides a strong argument for the inclusion of functional indicators in a holistic assessment of stream health.