Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the ...cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models.
Vegetation-type conversions between grasslands and shrublands have occurred worldwide in semiarid regions over the last 150 years. Areas once covered by drought-deciduous shrubs in Southern ...California (coastal sage scrub) are converting to grasslands dominated by nonnative species. Increasing fire frequency, drought, and nitrogen deposition have all been hypothesized as causes of this conversion, though there is little direct evidence. We constructed rain-out shelters in a coastal sage scrub community following a wildfire, manipulated water and nitrogen input in a split-plot design, and collected annual data on community composition for four years. While shrub cover increased through time in all plots during the postfire succession, both drought and nitrogen significantly slowed recovery. Four years after the fire, average native shrub cover ranged from over 80% in water addition, ambient-nitrogen plots to 20% in water reduction, nitrogen addition plots. Nonnative grass cover was high following the fire and remained high in the water reduction plots through the third spring after the fire, before decreasing in the fourth year of the study. Adding nitrogen decreased the cover of native plants and increased the cover of nonnative grasses, but also increased the growth of one crown-sprouting shrub species. Our results suggest that extreme drought during postfire succession may slow or alter succession, possibly facilitating vegetation-type conversion of coastal sage scrub to grassland. Nitrogen addition slowed succession and, when combined with drought, significantly decreased native cover and increased grass cover. Fire, drought, and atmospheric N deposition are widespread aspects of environmental change that occur simultaneously in this system. Our results imply these drivers of change may reinforce each other, leading to a continued decline of native shrubs and conversion to annual grassland.
We used leaf gas exchange, sap flow, and eddy covariance measurements to investigate whether high temperature substantially limits CO2 uptake at the LBA‐ECO (Large‐scale Biosphere‐Atmosphere) km‐83 ...tropical forest site in Brazil. Leaf‐level temperature‐photosynthesis curves, and comparisons of whole‐canopy net ecosystem CO2 exchange (NEE) with air temperature, showed that CO2 uptake declined sharply during warm periods. Observations of ambient leaf microclimate showed that leaves oscillate between two states: a cool, dimly lit stage and a hot, brightly illuminated stage where leaf temperatures are often greater than 35°C. The leaf‐level rates of photosynthesis decreased when shaded leaves (∼ambient air temperature and < 500 μmol m−2 s−1) were transferred into a prewarmed, brightly illuminated chamber (35° to 38°C and 1000 μmol m−2 s−1), coincident with increased leaf temperature, increased evaporative demand, and stomatal closure. The rates of whole‐canopy CO2 uptake calculated at 5‐min intervals increased initially at the onset of sunny periods that followed extended cloudy periods, but then decreased as the sunlight continued, leaf temperature and evaporative demand increased, and canopy conductance decreased. The forest at km‐83 appears to be close to a high temperature threshold, above which CO2 uptake drops sharply. This sensitivity results in part from the covariance between leaf temperature and leaf illumination; the brightly illuminated leaves that contribute disproportionately to canopy photosynthesis are warmed to the point that leaf gas exchange is curtailed.
Hyperspectral remote sensing provides unique and abundant spectral information for quantification of the land surface shortwave radiation budget, which can be used to calibrate climate models and to ...estimate surface energy budget for monitoring agriculture and urban environment. However, only single broadband or multispectral data have been used in previous studies. In the present study, two methods are proposed to estimate the instantaneous land surface net shortwave radiation (NSR) with high spatial resolutions using hyperspectral remote sensing observations from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data. Method A calculates the NSR based on separate estimation of downward radiation and surface broadband albedo, which requires ancillary information for aerosol optical depth; and Method B directly estimates the NSR from the observed radiance. Results based on radiative transfer simulations showed that the use of hyperspectral data can significantly improve NSR estimation compared with the multispectral data method. Atmospheric water vapor correction was applied to adjust the surface radiation estimation. Validation of AVIRIS NSR estimates against ground measurements from two flux networks for the period of 2006–2014 showed that the two methods were similar and had consistent accuracy in the all-sky instantaneous NSR estimation with root-mean-square-errors (RMSEs) of approximately 28–56W/m2. The pixel-based water vapor content estimation from AVIRIS data provided slightly different results than those obtained using coarse resolution remote sensing data. A simplified topographic correction algorithm was found to be able to improve the results generated from Method A; however, the degree of improvement provided by Method B was unclear, possibly because of the lack of consideration of horizontal atmospheric scattering effects from adjacent pixels. In general, hyperspectral remote sensing data have been shown to improve the NSR estimation accuracies compared with results obtained in previous studies. Additional efforts are needed to refine the NSR estimation for application to future satellite hyperspectral data.
•Two methods are proposed to estimate net shortwave radiation (NSR) from AVIRIS data.•Two methods have similar accuracies in the NSR estimation with RMSEs of 28–56W/m2.•Hyperspectral data were proved to improve NSR estimation over multispectral data.•More efforts are needed to consider topography and atmosphere adjacency effects.
•Differences in forest seasonal productivity cannot be explained by access to water or sunlight.•Equatorial climates benefit species that support high levels of dry-season photosynthesis.•PAR levels ...predicted the degree to which canopy photosynthetic capacity drives GEP.•Converted sites at Central Amazon show the disruption of the productivity cycle.
We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5° N–5° S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three non-water limited equatorial forest sites peak in the dry season, in correlation with high dry season light levels. The higher photosynthetic capacity that follows persists into the wet season, driving high GEP that is out of phase with sunlight, explaining the negative observed relationship with sunlight. Overall, these patterns suggest that at sites where water is not limiting, light interacts with adaptive mechanisms to determine photosynthetic capacity indirectly through leaf flush and litterfall seasonality. These mechanisms are poorly represented in ecosystem models, and represent an important challenge to efforts to predict tropical forest responses to climatic variations.
Predicting sediment yield from recently burned areas remains a challenge but is important for hazard and resource management as wildfire impacts increase. Here we use lidar‐based monitoring of two ...fires in southern California, USA to study the movement of sediment during pre‐rainfall periods and postfire periods of flooding and debris flows over multiple storm events. Using a data‐driven approach, we examine the relative importance of terrain, vegetation, burn severity, and rainfall amounts through time on sediment yield. We show that incipient fire‐activated dry sediment loading and pre‐fire colluvium were rapidly flushed out by debris flows and floods but continued erosion occurred later in the season from soil erosion and, in ∼9% of catchments, from shallow landslides. Based on these observations, we develop random forest regression models to predict dry ravel and incipient runoff‐driven sediment yield applicable to small steep headwater catchments in southern California.
Plain Language Summary
Wildfire makes watersheds more susceptible to hazardous flash flooding and debris flows, yet characterization and prediction of these hazards remains limited. In this study, we used repeat airborne laser mapping to quantify the movement of sediment in steep burn areas during initial dry periods and subsequent erosion from runoff events. Based on these observations, we developed two predictive models: one to predict the filling of channels with sediment prior to rainfall and a second one to predict erosion by debris flows and floods during initial storm events, which showed improvement over another commonly used model. After initial runoff events, much of the available sediment in channels was transported downstream, however small landslides and extensive erosion of soils across the landscape continued to supply sediment to floods and debris flows, in line with studies elsewhere showing continued debris flow activity despite reduced sediment in channels. Our study demonstrates that airborne laser mapping together with data‐driven modeling offer opportunities to increase predictive ability of post‐fire erosion and such approaches should be further explored in regions such as northern California, where fire is expanding and models of post‐fire erosion need to be tested and refined.
Key Points
Postfire dry and wet sediment transport were quantified with lidar and dominant controls were identified using random forest regression
Slope and sediment supply, including dry ravel, were the strongest controls on initial sediment yield by debris flows and floods
Continued sediment bulking occurred from soil erosion and patchy mass wasting later in the wet season as channels became supply limited
Bacteria and fungi drive the decomposition of dead plant biomass (litter), an important step in the terrestrial carbon cycle. Here we investigate the sensitivity of litter microbial communities to ...simulated global change (drought and nitrogen addition) in a California annual grassland. Using 16S and 28S rDNA amplicon pyrosequencing, we quantify the response of the bacterial and fungal communities to the treatments and compare these results to background, temporal (seasonal and interannual) variability of the communities. We found that the drought and nitrogen treatments both had significant effects on microbial community composition, explaining 2-6% of total compositional variation. However, microbial composition was even more strongly influenced by seasonal and annual variation (explaining 14-39%). The response of microbial composition to drought varied by season, while the effect of the nitrogen addition treatment was constant through time. These compositional responses were similar in magnitude to those seen in microbial enzyme activities and the surrounding plant community, but did not correspond to a consistent effect on leaf litter decomposition rate. Overall, these patterns indicate that, in this ecosystem, temporal variability in the composition of leaf litter microorganisms largely surpasses that expected in a short-term global change experiment. Thus, as for plant communities, future microbial communities will likely be determined by the interplay between rapid, local background variability and slower, global changes.
Aim: The controls of gross radiation use efficiency (RUE), the ratio between gross primary productivity (GPP) and the radiation intercepted by terrestrial vegetation, and its spatial and temporal ...variation are not yet fully understood. Our objectives were to analyse and synthesize the spatial variability of GPP and the spatial and temporal variability of RUE and its climatic controls for a wide range of vegetation types. Location: A global range of sites from tundra to rain forest. Methods: We analysed a global dataset on photosynthetic uptake and climatic variables from 35 eddy covariance (EC) flux sites spanning between 100 and 2200 mm mean annual rainfall and between -13 and 26°C mean annual temperature.RUE was calculated from the data provided by EC flux sites and remote sensing (MODIS). Results: Rainfall and actual evapotranspiration (AET) positively influenced the spatial variation of annual GPP, whereas temperature only influenced the GPP of forests. Annual and maximum RUE were also positively controlled primarily by annual rainfall. The main control parameters of the growth season variation of gross RUE varied for each ecosystem type. Overall, the ratio between actual and potential evapotranspiration and a surrogate for the energy balance explained a greater proportion of the seasonal variation of RUE than the vapour pressure deficit (VPD), AET and precipitation. Temperature was important for determining the intra-annual variability of the RUE at the coldest energy-limited sites. Main conclusions: Our analysis supports the idea that the annual functioning of vegetation that is adapted to its local environment is more constrained by water availability than by temperature. The spatial variability of annual and maximum RUE can be largely explained by annual precipitation, more than by vegetation type. The intra-annual variation of RUE was mainly linked to the energy balance and water availability along the climatic gradient. Furthermore, we showed that intra-annual variation of gross RUE is only weakly influenced by VPD and temperature, contrary to what is frequently assumed. Our results provide a better understanding of the spatial and temporal controls of the RUE and thus could lead to a better estimation of ecosystem carbon fixation and better modelling.
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