Matteo Detto

Consequences of defaunation for a tropical tree community.

Hunting affects a considerably greater area of the tropical forest biome than deforestation and logging combined. Often even large remote protected areas are depleted of a substantial proportion of their vertebrate fauna. However, understanding of the long-term ecological consequences of defaunation in tropical forests remains poor. Using tree census data from a large-scale plot monitored over a 15-year period since the approximate onset of intense hunting, we provide a comprehensive assessment of the immediate consequences of defaunation for a tropical tree community. Our data strongly suggest that over-hunting has engendered pervasive changes in tree population spatial structure and dynamics, leading to a consistent decline in local tree diversity over time. However, we do not find any support for suggestions that over-hunting reduces above-ground biomass or biomass accumulation rate in this forest. To maintain critical ecosystem processes in tropical forests increased efforts are required to protect and restore wildlife populations.

Understanding strategies for seed dispersal by wind under contrasting atmospheric conditions

Traits associated with seed dispersal vary tremendously among sympatric wind-dispersed plants. We used two contrasting tropical tree species, seed traps, micrometeorology, and a mechanistic model to evaluate how variation in four key traits affects seed dispersal by wind. The conceptual framework of movement ecology, wherein external factors (wind) interact with internal factors (plant traits) that enable movement and determine when and where movement occurs, fully captures the variable inputs and outputs of wind dispersal models and informs their interpretation. We used model calculations to evaluate the spatial pattern of dispersed seeds for the 16 factorial combinations of four traits. The study species differed dramatically in traits related to the timing of seed release, and a strong species by season interaction affected most aspects of the spatial pattern of dispersed seeds. A rich interplay among plant traits and seasonal differences in atmospheric conditions caused this interaction. Several of the same plant traits are crucial for both seed dispersal and other aspects of life history variation. Observed traits that limit dispersal are likely to be constrained by their life history consequences.

Hydrologic and atmospheric controls on initiation of convective precipitation events

[1] The pathway to summertime convective precipitation remains a vexing research problem because of the nonlinear feedback between soil moisture content and the atmosphere. Understanding this feedback is important to the southeastern U. S. region, given the high productivity of the timberland area and the role of summertime convective precipitation in maintaining this productivity. Here we explore triggers of convective precipitation for a wide range of soil moisture states and air relative humidity in a mosaic landscape primarily dominated by hardwood forests, pine plantations, and abandoned old field grassland. Using half-hourly sensible heat flux, micrometeorological, hydrological time series measurements collected at adjacent HW, PP, and OF ecosystems, and a simplified mixed layer slab model, we developed a conditional sampling scheme to separate convective from nonconvective precipitation events in the observed precipitation time series. The series analyzed (2001–2004) includes some of the wettest and driest periods within the past 57 years. We found that convective precipitation events have significantly larger intensities (mean of 2.1 mm per 30 min) when compared to their nonconvective counterparts (mean of 1.1 mm per 30 min). Interestingly, the statistics of convective precipitation events, including total precipitation, mean intensity, and maximum intensity, are statistically different when convective precipitation is triggered by moist and dry soil conditions but are robust in duration. Using the data, we also showed that a ‘‘boundary line’’ emerges such that for a given soil moisture state, air relative humidity must exceed a defined minimum threshold before convective precipitation is realized.

Gross ecosystem photosynthesis causes a diurnal pattern in methane emission from rice

Author(s): Hatala, JA; Detto, M; Baldocchi, DD | Abstract: Understanding the relative contribution of environmental and substrate controls on rice paddy methanogenesis is critical for developing mechanistic models of landscape-scale methane (CH4) flux. A diurnal pattern in observed rice paddy CH4 flux has been attributed to fluctuations in soil temperature physically driving diffusive CH4 transport from the soil to atmosphere. Here we make direct landscape-scale measurements of carbon dioxide and CH4 fluxes and show that gross ecosystem photosynthesis (GEP) is the dominant cause of the diurnal pattern in CH4 flux, even after accounting for the effects of soil temperature. The time series of GEP and CH4 flux show strong spectral coherency throughout the rice growing season at the diurnal timescale, where the peak in GEP leads that of CH 4 flux by 1.3±0.08 hours. By applying the method of conditional Granger causality in the spectral domain, we demonstrated that the diurnal pattern in CH4 flux is primarily caused by GEP. Copyright 2012 by the American Geophysical Union.

Hydrological Networks and Associated Topographic Variation as Templates for the Spatial Organization of Tropical Forest Vegetation

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10–1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30–600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20–300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.

Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest.

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflux from a humid tropical forest in Puerto Rico. We measured hourly soil CO2 efflux, temperature and moisture in control and exclusion plots (n = 6) for 6-months. The variance of each time series was analyzed using orthonormal wavelet transformation and Haar-wavelet coherence. We found strong negative coherence between soil moisture and soil respiration in control plots corresponding to a two-day periodicity. Across all plots, there was a significant parabolic relationship between soil moisture and soil CO2 efflux with peak soil respiration occurring at volumetric soil moisture of approximately 0.375 m3/m3. We additionally found a weak positive coherence between CO2 and temperature at longer time-scales and a significant positive relationship between soil temperature and CO2 efflux when the analysis was limited to the control plots. The coherence between CO2 and both temperature and soil moisture were reduced in exclusion plots. The reduced CO2 response to temperature in exclusion plots suggests that the positive effect of temperature on CO2 is constrained by soil moisture availability.

Spatial variability in tropical forest leaf area density from multireturn lidar and modeling

Leaf area index and leaf area density profiles are key variables for upscaling from leaves to ecosystems yet are difficult to measure well in dense and tall forest canopies. We present a new model to estimate leaf area density profiles from discrete multireturn data derived by airborne waveform light detection and ranging (lidar), a model based on stochastic radiative transfer theory. We tested the method on simulated ray tracing data for highly clumped forest canopies, both vertically homogenous and vertically inhomogeneous. Our method was able to reproduce simulated vertical foliage profiles with small errors and predictable biases in dense canopies (leaf area index = 6) including layers below densely foliated upper canopies. As a case study, we then applied the method to real multireturn airborne lidar data for a 50 ha plot of moist tropical forest on Barro Colorado Island, Panama. The method is suitable for estimating foliage profiles in a complex tropical forest, which opens new avenues for analyses of spatial and temporal variations in foliage distributions.

Detecting and projecting changes in forest biomass from plot data

14.

Variation of energy and carbon fluxes from a restored temperate freshwater wetland and implications for carbon market verification protocols

Temperate freshwater wetlands are among the most productive terrestrial ecosystems, stimulating interest in using restored wetlands as biological carbon sequestration projects for greenhouse gas reduction programs. In this study, we used the eddy covariance technique to measure surface energy carbon fluxes from a constructed, impounded freshwater wetland during two annual periods that were 8 years apart: 2002–2003 and 2010–2011. During 2010–2011, we measured methane (CH4) fluxes to quantify the annual atmospheric carbon mass balance and its concomitant influence on global warming potential (GWP). Peak growing season fluxes of latent heat and carbon dioxide (CO2) were greater in 2002–2003 compared to 2010–2011. In 2002, the daily net ecosystem exchange reached as low as −10.6 g C m−2 d−1, which was greater than 3 times the magnitude observed in 2010 (−2.9 g C m−2 d−1). CH4 fluxes during 2010–2011 were positive throughout the year and followed a strong seasonal pattern, ranging from 38.1 mg C m−2 d−1 in the winter to 375.9 mg C m−2 d−1 during the summer. The results of this study suggest that the wetland had reduced gross ecosystem productivity in 2010–2011, likely due to the increase in dead plant biomass (standing litter) that inhibited the generation of new vegetation growth. In 2010–2011, there was a net positive GWP (675.3 g C m−2 yr−1), and when these values are evaluated as a sustained flux, the wetland will not reach radiative balance even after 500 years.

Multivariate Conditional Granger Causality Analysis for Lagged Response of Soil Respiration in a Temperate Forest

Ecological multivariate systems offer a suitable data set on which to apply recent advances in information theory and causality detection. These systems are driven by the interplay of various environmental factors: meteorological and hydrological forcing, which are often correlated with each other at different time lags; and biological factors, primary producers and decomposers with both autonomous and coupled dynamics. Here, using conditional spectral Granger causality, we quantify directional causalities in a complex atmosphere-plant-soil system involving the carbon cycle. Granger causality is a statistical approach, originating in econometrics, used to identify the presence of linear causal interactions between time series of data, based on prediction theory. We first test to see if there was a significant difference in the causal structure among two treatments where carbon allocation to roots was interrupted by girdling. We then expanded the analysis, introducing radiation and soil moisture. The results showed a complex pattern of multilevel interactions, with some of these interactions depending upon the number of variables in the system. However, no significant differences emerged in the causal structure of above and below ground carbon cycle among the two treatments.