Widespread woody plant use of water stored in bedrock.

In the past several decades, field studies have shown that woody plants can access substantial volumes of water from the pores and fractures of bedrock1-3. If, like soil moisture, bedrock water storage serves as an important source of plant-available water, then conceptual paradigms regarding water and carbon cycling may need to be revised to incorporate bedrock properties and processes4-6. Here we present a lower-bound estimate of the contribution of bedrock water storage to transpiration across the continental United States using distributed, publicly available datasets. Temporal and spatial patterns of bedrock water use across the continental United States indicate that woody plants extensively access bedrock water for transpiration. Plants across diverse climates and biomes access bedrock water routinely and not just during extreme drought conditions. On an annual basis in California, the volumes of bedrock water transpiration exceed the volumes of water stored in human-made reservoirs, and woody vegetation that accesses bedrock water accounts for over 50% of the aboveground carbon stocks in the state. Our findings indicate that plants commonly access rock moisture, as opposed to groundwater, from bedrock and that, like soil moisture, rock moisture is a critical component of terrestrial water and carbon cycling.

Climate lags and genetics determine phenology in quaking aspen (Populus tremuloides).

Spatiotemporal patterns of phenology may be affected by mosaics of environmental and genetic variation. Environmental drivers may have temporally lagged impacts, but patterns and mechanisms remain poorly known. We combine multiple genomic, remotely sensed, and physically modeled datasets to determine the spatiotemporal patterns and drivers of canopy phenology in quaking aspen, a widespread clonal dioecious tree species with diploid and triploid cytotypes. We show that over 391 km2 of southwestern Colorado: greenup date, greendown date, and growing season length vary by weeks and differ across sexes, cytotypes, and genotypes; phenology has high phenotypic plasticity and heritabilities of 31-61% (interquartile range); and snowmelt date, soil moisture, and air temperature predict phenology, at temporal lags of up to 3 yr. Our study shows that lagged environmental effects are needed to explain phenological variation and that the effect of cytotype on phenology is obscured by its correlation with topography. Phenological patterns are consistent with responses to multiyear accumulation of carbon deficit or hydraulic damage.

Cytotype and genotype predict mortality and recruitment in Colorado quaking aspen (Populus tremuloides).

Species responses to climate change depend on environment, genetics, and interactions among these factors. Intraspecific cytotype (ploidy level) variation is a common type of genetic variation in many species. However, the importance of intraspecific cytotype variation in determining demography across environments is poorly known. We studied quaking aspen (Populus tremuloides), which occurs in diploid and triploid cytotypes. This widespread tree species is experiencing contractions in its western range, which could potentially be linked to cytotype-dependent drought tolerance. We found that interactions between cytotype and environment drive mortality and recruitment across 503 plots in Colorado. Triploids were more vulnerable to mortality relative to diploids and had reduced recruitment on more drought-prone and disturbed plots relative to diploids. Furthermore, there was substantial genotype-dependent variation in demography. Thus, cytotype and genotype variation are associated with decline in this foundation species. Future assessment of demographic responses to climate change will benefit from knowledge of how genetic and environmental mosaics interact to determine species' ecophysiology and demography.

Geomorphic transience moderates topographic controls on tropical canopy foliar traits.

Tropical ecosystems that exist on mountainous terrain harbour enormous species and functional diversity. In addition, the morphology of these complex landscapes is dynamic. Stream channels respond to mountain uplift by eroding into rising rock bodies. Many local factors determine whether channels are actively downcutting, in relative steady-state, or aggrading. It is possible to assess the trajectory of catchment-level landscape evolution utilising lidar-based models, but the effect of these trajectories on biogeochemical gradients and organisation of canopy traits across climatic and geochemical conditions remain uncertain. We use canopy trait maps to assess how variable erosion rate within catchments influence hillslope controls on canopy traits across Mt. Kinabalu, Borneo. While foliar nutrient content generally increased along hillslopes, these relationships were moderated by catchment responses to changing erosion pressure, with active downcutting associated with greater turnover in canopy traits along hillslopes. These results provide an understanding of geomorphic process controls on forest functional diversity.

Landscape evolution and nutrient rejuvenation reflected in Amazon forest canopy chemistry.

Terra firme forests make up more than three quarters of the western Amazon basin and are often considered functionally homogeneous in regional scale mapping and modelling efforts. However, the landforms underlying these systems are subject to dynamic processes of landscape evolution occurring within an otherwise geomorphically stable terrace formation. These processes may introduce systematic variability in local nutrient status of terra firme ecosystems. We utilised high-resolution airborne topographic and imaging spectroscopy data, with directed field soil surveys, to reveal that active stream incision and patterns of soil rock derived nutrient availability drive foliar canopy chemistry distributions across seven catchments within a single terrace formation. These results strongly suggest that fine-scale geomorphic processes directly affect biogeochemical cycles throughout the lowland western Amazon. Furthermore, links between landscape evolution and foliar chemical distributions indicate that geomorphic processes drive the fine-scale spatial organisation of this tropical ecosystem, with implications for the functional assembly and biogeography of Amazonian forests.

Targeted carbon conservation at national scales with high-resolution monitoring.

Terrestrial carbon conservation can provide critical environmental, social, and climate benefits. Yet, the geographically complex mosaic of threats to, and opportunities for, conserving carbon in landscapes remain largely unresolved at national scales. Using a new high-resolution carbon mapping approach applied to Perú, a megadiverse country undergoing rapid land use change, we found that at least 0.8 Pg of aboveground carbon stocks are at imminent risk of emission from land use activities. Map-based information on the natural controls over carbon density, as well as current ecosystem threats and protections, revealed three biogeographically explicit strategies that fully offset forthcoming land-use emissions. High-resolution carbon mapping affords targeted interventions to reduce greenhouse gas emissions in rapidly developing tropical nations.

Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space.

Carbon dioxide and methane emissions are the two primary anthropogenic climate-forcing agents and an important source of uncertainty in the global carbon budget. Uncertainties are further magnified when emissions occur at fine spatial scales (<1 km), making attribution challenging. We present the first observations from NASA's Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer showing quantification and attribution of fine-scale methane (0.3 to 73 tonnes CH4 hour-1) and carbon dioxide sources (1571 to 3511 tonnes CO2 hour-1) spanning the oil and gas, waste, and energy sectors. For selected countries observed during the first 30 days of EMIT operations, methane emissions varied at a regional scale, with the largest total emissions observed for Turkmenistan (731 ± 148 tonnes CH4 hour-1). These results highlight the contributions of current and planned point source imagers in closing global carbon budgets.

Modeling geogenic and atmospheric nitrogen through the East River Watershed, Colorado Rocky Mountains.

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. In this study, we develop the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Several calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed. When accounting for recycling of N through plant litter turnover, rock weathering accounts for approximately 12% of the annual dissolved N sources to the watershed in the most probable calibration scenario (0-31% in other scenarios), and 21% (0-44% in other scenarios) when considering only "new" N sources (i.e. geogenic and atmospheric). On an annual scale, instream dissolved N elimination, plant turnover (including cattle grazing) and atmospheric deposition are the most important controls on N cycling.

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

Human and environmental controls over aboveground carbon storage in Madagascar.

BACKGROUND: Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar. RESULTS: We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR. CONCLUSIONS: High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.