Dataset Information

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

ABSTRACT: Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomass?ha(-1)?y(-1) were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1-16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.

SUBMITTER: Chambers JQ

PROVIDER: S-EPMC3593828 | biostudies-other | 2013 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

Chambers Jeffrey Q JQ Negron-Juarez Robinson I RI Marra Daniel Magnabosco DM Di Vittorio Alan A Tews Joerg J Roberts Dar D Ribeiro Gabriel H P M GH Trumbore Susan E SE Higuchi Niro N

Proceedings of the National Academy of Sciences of the United States of America 20130128 10

Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data ...[more]

PMID: 23359707

Similar Datasets

Project description:In order to prevent irreversible impacts of climate change on the biosphere it is imperative to phase out the use of fossil fuels. Consequently, the provisioning of renewable resources such as timber and biomass from forests is an ecosystem service of increasing importance. However, risk factors such as changing disturbance regimes are challenging the continuous provisioning of ecosystem services, and are thus a key concern in forest management. We here used simulation modeling to study different risk management strategies in the context of timber production under changing climate and disturbance regimes, focusing on a 8127 ha forest landscape in the Northern Front Range of the Alps in Austria. We show that under a continuation of historical management, disturbances from wind and bark beetles increase by +39.5% on average over 200 years in response to future climate change. Promoting mixed forests and climate-adapted tree species as well as increasing management intensity effectively reduced future disturbance risk. Analyzing the spatial patterns of disturbance on the landscape, we found a highly uneven distribution of risk among stands (Gini coefficients up to 0.466), but also a spatially variable effectiveness of silvicultural risk reduction measures. This spatial variability in the contribution to and control of risk can be used to inform disturbance management: Stands which have a high leverage on overall risk and for which risks can effectively be reduced (24.4% of the stands in our simulations) should be a priority for risk mitigation measures. In contrast, management should embrace natural disturbances for their beneficial effects on biodiversity in areas which neither contribute strongly to landscape-scale risk nor respond positively to risk mitigation measures (16.9% of stands). We here illustrate how spatial heterogeneity in forest landscapes can be harnessed to address both positive and negative effects of changing natural disturbance regimes in ecosystem management.

Dataset Information

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

Publications

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets