Regional processes in mangrove ecosystems: spatial scaling relationships, biomass, and turnover rates following catastrophic disturbance

Physiological processes and local-scale structural dynamics of mangroves are relatively well studied. Regional-scale processes, however, are not as well understood. Here we provide long-term data on trends in structure and forest turnover at a large scale, following hurricane damage in mangrove ecosystems of South Florida, U.S.A. Twelve mangrove vegetation plots were monitored at periodic intervals, between October 1992 and March 2005. Mangrove forests of this region are defined by a −1.5 scaling relationship between mean stem diameter and stem density, mirroring self-thinning theory for mono-specific stands. This relationship is reflected in tree size frequency scaling exponents which, through time, have exhibited trends toward a community average that is indicative of full spatial resource utilization. These trends, together with an asymptotic standing biomass accumulation, indicate that coastal mangrove ecosystems do adhere to size-structured organizing principles as described for upland tree communities. Regenerative dynamics are different between areas inside and outside of the primary wind-path of Hurricane Andrew which occurred in 1992. Forest dynamic turnover rates, however, are steady through time. This suggests that ecological, more-so than structural factors, control forest productivity. In agreement, the relative mean rate of biomass growth exhibits an inverse relationship with the seasonal range of porewater salinities. The ecosystem average in forest scaling relationships may provide a useful investigative tool of mangrove community biomass relationships, as well as offer a robust indicator of general ecosystem health for use in mangrove forest ecosystem management and restoration.

R-script modified VS-Lite model

Drought is a key factor affecting forest ecosystem processes at different spatio-temporal scales. For accurately modeling tree functioning ? and thus for producing reliable simulations of forest dynamics ? the consideration of the variability in the timing and extent of drought effects on tree growth is essential, particularly in strongly seasonal climates such as in the Mediterranean area. Yet, most dynamic vegetation models (DVMs) do not include this intra-annual variability of drought effects on tree growth. We present a novel approach for linking tree-ring data to drought simulations in DVMs. A modified forward model of tree-ring width (VS-Lite) was used to estimate seasonal- and site-specific growth responses to drought of Scots pine (Pinus sylvestris L.), which were subsequently implemented in the DVM ForClim. Ring-width data from sixteen sites along a moisture gradient from Central Spain to the Swiss Alps, including the dry inner Alpine valleys, were used to calibrate the forward ring-width model, and inventory data from managed Scots pine stands were used to evaluate ForClim performance. The modified VS-Lite accurately estimated the year-to-year variability in ring-width indices and produced realistic intra-annual growth responses to soil drought, showing a stronger relationship between growth and drought in spring than in the other seasons and thus capturing the strategy of Scots pine to cope with drought. The ForClim version including seasonal variability in growth responses to drought showed improved predictions of stand basal area and stem number, indicating the need to consider intra-annual differences in climate-growth relationships in DVMs when simulating forest dynamics. Forward modeling of ring-width growth may be a powerful tool to calibrate growth functions in DVMs that aim to simulate forest properties in across multiple environments at large spatial scales.

Contrasting fire regimes in a seasonally dry tropical forest and a savanna ecosystem in the western Ghats, India

Tropical dry forests and savannas constitute more than half of all tropical forests and grasslands, but little is known about forest fire regimes within these two extensive types of ecosystems. Forest fire regimes in a predominantly dry forest in India, the Nilgiri landscape, and a predominantly savanna ecosystem in the Sathyamangalam landscape, were examined. Remote sensing data were applied to delineate burned areas, determine fire size characteristics, and to estimate fire-rotation intervals. Belt transects (0.5 ha) were used to estimate forest structure, diversity, and fuel loads. Mean area burned, mean number of fires, and mean fire size per year were substantially higher in the Nilgiri landscape compared to the Sathyamangalam landscape. Mean fire-rotational interval was 7.1 yr in the Nilgiri landscape and 44.1 yr in the Sathyamangalam landscape. Tree (>= 10 cm diameter at breast height) species diversity, tree density, and basal area were significantly higher in the Nilgiri landscape compared to the Sathyamangalam landscape. Total fuel loads were significantly higher in tropical dry and moist deciduous forests in the Nilgiri landscape, but total fuel loads were higher in the tropical dry thorn forests of the Sathyamangalam landscape. Thus, the two landscapes revealed contrasting fire regimes and forest characteristics, with more and four-fold larger fires in the Nilgiri landscape. The dry forests and savannas could be maintained by a combination of factors, such as fire, grazing pressures, and herbivore populations. Understanding the factors maintaining these two ecosystems will be critical for their conservation.

Classifying Ecosystem Services for Economic Valuation: The case of forest water services

30 p.

Nitrogen-15 signals of leaf-litter-soil continuum as a possible indicator of ecosystem nitrogen saturation by forest succession and N loads

National Key Research and Development Program [2010CB833502]; National Natural Science Foundation of China [30600071, 40601097, 30590381]; Chinese Academy of Sciences [KZCX2-YW-432, O7V70080SZ, LENOM07LS-01]; GUCAS [O85101PM03]

Impact of cloudiness on net ecosystem exchange of carbon dioxide in different types of forest ecosystems in China

Asia 3 Foresight Program [30721140307]; National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381, 30900198];

Use of Ecosystem Flux Data and a Simulation Model to Examine Seasonal Drought Effects on a Subtropical Coniferous Forest

National Natural Science Foundation of China (NSFC) [30670384, 30590381]

Simulated variations in atmospheric CO2 over a Wisconsin forest using a coupled ecosystem-atmosphere model

Ecosystem fluxes of energy, water, and CO2 result in spatial and temporal variations in atmospheric properties. In principle, these variations can be used to quantify the fluxes through inverse modelling of atmospheric transport, and can improve the understanding of processes and falsifiability of models. We investigated the influence of ecosystem fluxes on atmospheric CO2 in the vicinity of the WLEF-TV tower in Wisconsin using an ecophysiological model (Simple Biosphere, SiB2) coupled to an atmospheric model (Regional Atmospheric Modelling System). Model parameters were specified from satellite imagery and soil texture data. In a companion paper, simulated fluxes in the immediate tower vicinity have been compared to eddy covariance fluxes measured at the tower, with meteorology specified from tower sensors. Results were encouraging with respect to the ability of the model to capture observed diurnal cycles of fluxes. Here, the effects of fluxes in the tower footprint were also investigated by coupling SiB2 to a high-resolution atmospheric simulation, so that the model physiology could affect the meteorological environment. These experiments were successful in reproducing observed fluxes and concentration gradients during the day and at night, but revealed problems during transitions at sunrise and sunset that appear to be related to the canopy radiation parameterization in SiB2.

Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south-central Indiana, USA

Observations of net ecosystem exchange (NEE) of carbon and its biophysical drivers have been collected at the AmeriFlux site in the Morgan-Monroe State Forest (MMSF) in Indiana, USA since 1998. Thus, this is one of the few deciduous forest sites in the world, where a decadal analysis on net ecosystem productivity (NEP) trends is possible. Despite the large interannual variability in NEP, the observations show a significant increase in forest productivity over the past 10 years (by an annual increment of about 10 g C m−2 yr−1). There is evidence that this trend can be explained by longer vegetative seasons, caused by extension of the vegetative activity in the fall. Both phenological and flux observations indicate that the vegetative season extended later in the fall with an increase in length of about 3 days yr−1 for the past 10 years. However, these changes are responsible for only 50% of the total annual gain in forest productivity in the past decade. A negative trend in air and soil temperature during the winter months may explain an equivalent increase in NEP through a decrease in ecosystem respiration.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.

Frugivory by the White-bearded Manakin (Manacus manacus, Pipridae) in restinga forest, an ecosystem associated to the Atlantic forest

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)