Do plant species influence soil gas fluxes in tropical forests?

Abstract ID: 53. Publicado também on-line

The long-solved problem of the best-fit straight line: application to isotopic mixing lines

It has been almost 50 years since York published an exact and general solution for the best-fit straight line to independent points with normally distributed errors in both x and y. York's solution is highly cited in the geophysical literature but almost unknown outside of it, so that there has been no ebb in the tide of books and papers wrestling with the problem. Much of the post-1969 literature on straight-line fitting has sown confusion not merely by its content but by its very existence. The optimal least-squares fit is already known; the problem is already solved. Here we introduce the non-specialist reader to York's solution and demonstrate its application in the interesting case of the isotopic mixing line, an analytical tool widely used to determine the isotopic signature of trace gas sources for the study of biogeochemical cycles. The most commonly known linear regression methods – ordinary least-squares regression (OLS), geometric mean regression (GMR), and orthogonal distance regression (ODR) – have each been recommended as the best method for fitting isotopic mixing lines. In fact, OLS, GMR, and ODR are all special cases of York's solution that are valid only under particular measurement conditions, and those conditions do not hold in general for isotopic mixing lines. Using Monte Carlo simulations, we quantify the biases in OLS, GMR, and ODR under various conditions and show that York's general – and convenient – solution is always the least biased

The Threat of Multiâ Year Drought in Western Amazonia

Recent â onceâ inâ aâ centuryâ Amazonian droughts highlight the impacts of drought and climate change on this region’s vegetation, carbon storage, water cycling, biodiversity, land use, and economy. The latest climate model simulations suggest this region will experience worsening future drought. However, the instrumental record is too short to quantify the range of background drought variability, or to evaluate extended drought risk in climate models. To overcome these limitations, we generated a new, highly resolved lake record of hydroclimatic variability within the western Amazon Basin. We find that Amazonia has regularly experienced multiâ year droughts over the last millennium. Our results indicate that current climate model simulations likely underestimate the background risk of multiâ year Amazonian drought. These findings illustrate that the future sustainability of the Amazonian forest and its many services may require management strategies that consider the likelihood of multiâ year droughts superimposed on a continued warming trend.Plain Language SummaryThe Amazon basin recently experienced multiple â onceâ inâ aâ centuryâ droughts that impacted the region’s water cycle, economy, vegetation, and carbon storage. However, the instrumental record in this region tends to be too short to determine if these droughts are abnormal in a longâ term context. Paleoclimate data can extend drought records that help water and land managers plan for these events in the face of climate change. To provide additional information about preâ instrumental drought, here we present results from a new paleoclimate lake record based on sediments we recovered from Lake Limón in the Peruvian Amazon. We find that concentrations of elements in the Lake Limón sediment cores are likely recording past changes in rainfall variability. We use this elemental variability to generate a new, millennialâ length record of drought for the western Amazon. We show that this region has experienced multiâ year droughts at least twice a century over the last â ¼1,400 years. The frequency and severity of these paleoclimateâ inferred droughts may exceed most climate model and instrumentalâ era drought risk estimates. Our findings illustrate that the future sustainability of the Amazonian forest and its many ecosystem services may require management strategies that consider the likelihood of multiâ year droughts in addition to continued warming.Key PointsWe present results from a highâ resolution paleoclimate record of hydroclimatic variability in western AmazoniaOur paleoclimate record suggests western Amazonia has regularly experienced multiâ year drought over the last millenniumEarth system model simulations may underestimate the background risk of multiâ year western Amazonian droughtPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146272/1/wrcr23386_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146272/2/wrcr23386.pd

Amazon rainforests green-up with sunlight in dry season

Metabolism and phenology of Amazon rainforests significantly influence global dynamics of climate, carbon and water, but remain poorly understood. We analyzed Amazon vegetation phenology at multiple scales with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements from 2000 to 2005. MODIS Enhanced Vegetation Index (EVI, an index of canopy photosynthetic capacity) increased by 25% with sunlight during the dry season across Amazon forests, opposite to ecosystem model predictions that water limitation should cause dry season declines in forest canopy photosynthesis. In contrast to intact forests, areas converted to pasture showed dry-season declines in EVI-derived photosynthetic capacity, presumably because removal of deep-rooted forest trees reduced access to deep soil water. Local canopy photosynthesis measured from eddy flux towers in both a rainforest and forest conversion site confirm our interpretation of satellite data, and suggest that basin-wide carbon fluxes can be constrained by integrating remote sensing and local flux measurements

In situ permafrost thaw due to climate change drives holistic microbial community shifts with implications for methane cycling

Thawing permafrost is a potentially significant source of radiative forcing feedback due to increased emissions of methane, a biogenic greenhouse gas (GHG). This study investigated changes in the microbial community along a permafrost thaw gradient at Stordalen Mire, Sweden using 16S rRNA gene amplicon and metagenomic methods. In situ measurements of geochemical parameters, including CH4 and C isotopes, enabled linkage of community dynamics to significant shifts in C balance. The thaw gradient ranged from intact at a palsa (low productivity and GHG emissions), through partially thawed in a bog (high productivity, low GHG emissions) to a completely thawed fen (high productivity and GHG emissions). Microbial assemblages in both the palsa and fen were highly diverse (in both richness and evenness), consistent with climax communities. The microbial community in the bog had distinctly lower diversity, characteristic of ecosystem disturbance. The palsa community was dominated by Acidobacteria and Proteobacteria, as is typical of a range of soils including permafrost. Methanogens dominated both the bog and fen and were most abundant within the zone of water table fluctuation. Inferring methanogens’ production pathway from phylogeny showed a shift from mostly hydrogenotrophic methanogens in the bog towards acetotrophic methanogens in the fen. This corroborated porewater and flux emitted CH4 and CO2 carbon isotopic 13C signatures of CH4 and CO2. The fen, where the highest CH4 flux was recorded, was significantly richer in methanogenic archaea. A novel archaea, Candidatus Methanoflorens stordalenmirensis, was present at up to 70% relative abundance in the bog, enabling recovery of a population genome. The genome (and associated metaproteome) of ’M. stordalenmirensis’ indicates that hydrogenotrophic methane production is its main energy conservation pathway. ’Methanoflorens’ may be an indicator species of permafrost thaw, it is globally ubiquitous, and appears a major contributor to global methane production. Our results revealed a distinct difference in the microbial community structure and membership at each site, which can be directly associated with increasing methane emission and thaw state

Do plant species influence soil CO2 and N2O fluxes in a diverse tropical forest?

To test whether plant species influence greenhouse gas production in diverse ecosystems, we measured wet season soil CO2 and N2O fluxes close to ~300 large (>35 cm in diameter at breast height (DBH)) trees of 15 species at three clay-rich forest sites in central Amazonia. We found that soil CO2 fluxes were 38% higher near large trees than at control sites >10 m away from any tree (P < 0.0001). After adjusting for large tree presence, a multiple linear regression of soil temperature, bulk density, and liana DBH explained 19% of remaining CO2 flux variability. Soil N2O fluxes adjacent to Caryocar villosum, Lecythis lurida, Schefflera morototoni, and Manilkara huberi were 84%-196% greater than Erisma uncinatum and Vochysia maxima, both Vochysiaceae. Tree species identity was the most important explanatory factor for N2O fluxes, accounting for more than twice the N2O flux variability as all other factors combined. Two observations suggest a mechanism for this finding: (1) sugar addition increased N2O fluxes near C. villosum twice as much (P < 0.05) as near Vochysiaceae and (2) species mean N2O fluxes were strongly negatively correlated with tree growth rate (P = 0.002). These observations imply that through enhanced belowground carbon allocation liana and tree species can stimulate soil CO2 and N2O fluxes (by enhancing denitrification when carbon limits microbial metabolism). Alternatively, low N2O fluxes potentially result from strong competition of tree species with microbes for nutrients. Species-specific patterns in CO2 and N2O fluxes demonstrate that plant species can influence soil biogeochemical processes in a diverse tropical forest

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods