Large lianas as hyperdynamic elements of the tropical forest canopy

Lianas (woody vines) are an important component of lowland tropical forests. We report large liana and tree inventory and dynamics data from Amazonia over periods of up to 24 years, making this the longest geographically extensive study of liana ecology to date. We use these results to address basic questions about the ecology of large lianas in mature forests and their interactions with trees. In one intensively studied site we find that large lianas (≥10 cm diameter) represent ,5% of liana stems, but 80% of biomass of well-lit upper canopy lianas. Across sites, large lianas and large trees are both most successful in terms of structural importance in richer soil forests, but large liana success may be controlled more by the availability of large tree supports rather than directly by soil conditions. Long-term annual turnover rates of large lianas are 5–8%, three times those of trees. Lianas are implicated in large tree mortality: liana-infested large trees are three times more likely to die than liana-free large trees, and large lianas are involved in the death of at least 30% of tree basal area. Thus large lianas are a much more dynamic component of Amazon forests than are canopy trees, and they play a much more significant functional role than their structural contribution suggests

Increasing dominance of large lianas in Amazonian forests

Ecological orthodoxy suggests that old-growth forests should be close to dynamic equilibrium, but this view has been challenged by recent findings that neotropical forests are accumulating carbon and biomass, possibly in response to the increasing atmospheric concentrations of carbon dioxide. However, it is unclear whether the recent increase in tree biomass has been accompanied by a shift in community composition. Such changes could reduce or enhance the carbon storage potential of old-growth forests in the long term. Here we show that non-fragmented Amazon forests are experiencing a concerted increase in the density, basal area and mean size of woody climbing plants (lianas). Over the last two decades of the twentieth century the dominance of large lianas relative to trees has increased by 1.7–4.6% a year. Lianas enhance tree mortality and suppress tree growth, so their rapid increase implies that the tropical terrestrial carbon sink may shut down sooner than current models suggest. Predictions of future tropical carbon fluxes will need to account for the changing composition and dynamics of supposedly undisturbed forests

Above- and below-ground net primary productivity across ten Amazonian forests on contrasting soils

Copyright © 2009 European Geosciences Union. This is the published version available at http://www.biogeosciences.net/6/2759/2009/bg-6-2759-2009.html © Author(s) 2009. This work is distributed under the Creative Commons Attribution 3.0 License.The net primary productivity (NPP) of tropical forests is one of the most important and least quantified components of the global carbon cycle. Most relevant studies have focused particularly on the quantification of the above-ground coarse wood productivity, and little is known about the carbon fluxes involved in other elements of the NPP, the partitioning of total NPP between its above- and below-ground components and the main environmental drivers of these patterns. In this study we quantify the above- and below-ground NPP of ten Amazonian forests to address two questions: (1) How do Amazonian forests allocate productivity among its above- and below-ground components? (2) How do soil and leaf nutrient status and soil texture affect the productivity of Amazonian forests? Using a standardized methodology to measure the major elements of productivity, we show that NPP varies between 9.3±1.3MgC ha−1 yr−1 (mean±standard error), at a white sand plot, and 17.0±1.4MgC ha−1 yr−1 at a very fertile Terra Preta site, with an overall average of 12.8±0.9MgC ha−1 yr−1. The studied forests allocate on average 64±3% and 36±3% of the total NPP to the above and below-ground components, respectively. The ratio of above-ground and below-ground NPP is almost invariant with total NPP. Litterfall and fine root production both increase with total NPP, while stem production shows no overall trend. Total NPP tends to increase with soil phosphorus and leaf nitrogen status. However, allocation of NPP to below-ground shows no relationship to soil fertility, but appears to decrease with the increase of soil clay content

Methods to estimate aboveground wood productivity from long-term forest inventory plots

Forest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold (“recruits”). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mg ha−1 year−1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6 years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the contribution of recruits should all be accounted for when estimating productivity rates, and suggest methods for doing this.European UnionUK Natural Environment Research CouncilGordon and Betty Moore FoundationCASE sponsorship from UNEP-WCMCRoyal Society University Research FellowshipERC Advanced Grant “Tropical Forests in the Changing Earth System”Royal Society Wolfson Research Merit Awar

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities

1. The forests of Amazonia are among the most biodiverse on Earth, yet accurately quantifying how species composition varies through space (i.e., beta‐diversity) remains a significant challenge. Here, we use high‐fidelity airborne imaging spectroscopy from the Carnegie Airborne Observatory to quantify a key component of beta‐diversity, the distance decay in species similarity through space, across three landscapes in Northern Peru. We then compared our derived distance decay relationships to theoretical expectations obtained from a Poisson Cluster Process, known to match well with empirical distance decay relationships at local scales. 2. We used an unsupervised machine learning approach to estimate spatial turnover in species composition from the imaging spectroscopy data. We first validated this approach across two landscapes using an independent dataset of forest composition in 49 forest census plots (0.1–1.5 ha). We then applied our approach to three landscapes, which together represented terra firme clay forest, seasonally flooded forest and white‐sand forest. We finally used our approach to quantify landscape‐scale distance decay relationships and compared these with theoretical distance decay relationships derived from a Poisson Cluster Process. 3. We found a significant correlation of similarity metrics between spectral data and forest plot data, suggesting that beta‐diversity within and among forest types can be accurately estimated from airborne spectroscopic data using our unsupervised approach. We also found that estimated distance decay in species similarity varied among forest types, with seasonally flooded forests showing stronger distance decay than white‐sand and terra firme forests. Finally, we demonstrated that distance decay relationships derived from the theoretical Poisson Cluster Process compare poorly with our empirical relationships. 4. Synthesis. Our results demonstrate the efficacy of using high‐fidelity imaging spectroscopy to estimate beta‐diversity and continuous distance decay in lowland tropical forests. Furthermore, our findings suggest that distance decay relationships vary substantially among forest types, which has important implications for conserving these valuable ecosystems. Finally, we demonstrate that a theoretical Poisson Cluster Process poorly predicts distance decay in species similarity as conspecific aggregation occurs across a range of nested scales within larger landscapes

Understanding different dominance patterns in western Amazonian forests

Dominance of neotropical tree communities by a few species is widely documented, but dominant trees show a variety of distributional patterns still poorly understood. Here, we used 503 forest inventory plots (93,719 individuals ≥2.5 cm diameter, 2609 species) to explore the relationships between local abundance, regional frequency and spatial aggregation of dominant species in four main habitat types in western Amazonia. Although the abundance-occupancy relationship is positive for the full dataset, we found that among dominant Amazonian tree species, there is a strong negative relationship between local abundance and regional frequency and/or spatial aggregation across habitat types. Our findings suggest an ecological trade-off whereby dominant species can be locally abundant (local dominants) or regionally widespread (widespread dominants), but rarely both (oligarchs). Given the importance of dominant species as drivers of diversity and ecosystem functioning, unravelling different dominance patterns is a research priority to direct conservation efforts in Amazonian forests.Publisher PDFPeer reviewe

Does the disturbance hypothesis explain the biomass increase in basin-wide Amazon forest plot data?

Positive aboveground biomass trends have been reported from old-growth forests across the Amazon basin and hypothesized to reflect a large-scale response to exterior forcing. The result could, however, be an artefact due to a sampling bias induced by the nature of forest growth dynamics. Here, we characterize statistically the disturbance process in Amazon old-growth forests as recorded in 135 forest plots of the RAINFOR network up to 2006, and other independent research programmes, and explore the consequences of sampling artefacts using a data-based stochastic simulator. Over the observed range of annual aboveground biomass losses, standard statistical tests show that the distribution of biomass losses through mortality follow an exponential or near-identical Weibull probability distribution and not a power law as assumed by others. The simulator was parameterized using both an exponential disturbance probability distribution as well as a mixed exponential–power law distribution to account for potential large-scale blowdown events. In both cases, sampling biases turn out to be too small to explain the gains detected by the extended RAINFOR plot network. This result lends further support to the notion that currently observed biomass gains for intact forests across the Amazon are actually occurring over large scales at the current time, presumably as a response to climate change