The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest

Groeneveld, Jürgen; Alves, Luciana F.; Bernacci, Luís Carlos; Catharino, Eduardo Luı́s Martins; Knogge, Christoph; Metzger, Jean Paul; Pütz, Sandro; Huth, Andreas

doi:10.1016/j.ecolmodel.2009.06.015

Cited by 63 publications

(48 citation statements)

References 55 publications

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“…Several factors suggest that our estimates are conservative: first, edge effects may reach far more into forests than the 100-m wide edges our study used 32,33,35 , (for example, due to fire invading forests via edges 28 ); second, carbon loss in fragments with 40 . Despite globally increasing efforts to conserve tropical forests, fragmentation processes are likely to remain a highly relevant process affecting carbon dynamics in the Amazon Forest and other tropical forests.…”

Section: Discussionmentioning

confidence: 99%

“…3); the forest-edge model estimates higher carbon losses for smaller fragments. Results of the process-based forest model have been compared with forest inventories of fragments in the Brazilian Atlantic Forest 32,33 ( Supplementary Fig. 4).…”

Section: Resultsmentioning

confidence: 99%

“…Second, we obtained carbon loss in the border area of forest fragments with the dynamic, process-based forest-growth model FORMIND 32,33 and compared results for single forest fragments with the results of the simple edgeeffect model. FORMIND models tree growth, seed dispersal, recruitment, mortality, competition for light and space and disturbances by grouping trees into functional types 32,33 . FORMIND is an individual-and process-based forest model, which has already been applied and tested in many different regions of the tropics 32,33 (Supplementary Methods), capturing not only the main ecological processes, but also the spatial differentiated degradation of forest (for example, due to fragmentation), and the subsequent regrowth on that patch, too.…”

Section: Discussionmentioning

confidence: 99%

“…FORMIND models tree growth, seed dispersal, recruitment, mortality, competition for light and space and disturbances by grouping trees into functional types 32,33 . FORMIND is an individual-and process-based forest model, which has already been applied and tested in many different regions of the tropics 32,33 (Supplementary Methods), capturing not only the main ecological processes, but also the spatial differentiated degradation of forest (for example, due to fragmentation), and the subsequent regrowth on that patch, too. We parameterized the model such that it yielded on average an above-ground-stored carbon in live trees of 125 Mg C ha À 1 , as estimated empirically for non-fragmented forests of the Brazilian Atlantic Forest 32,33,48,49 , and for the Amazon Forest we applied 170 Mg C ha À 1 for undisturbed forests 13 .…”

Section: Discussionmentioning

confidence: 99%

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Long-term carbon loss in fragmented Neotropical forests

et al. 2014

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Section: Discussionmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Long-term carbon loss in fragmented Neotropical forests

et al. 2014

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“…The model has been proven suitable to simulate a wide range of forest sites on Borneo (Sabah) , Venezuela (Kammesheidt et al, 2001), French Guiana (Köhler et al, 2003), Mexico (Rüger et al, 2008), Brazil (Groeneveld et al, 2009) and Ecuador (Dislich et al, 2009). The site-specific model adaptation and parametrisation to a dipterocarp tropical rain forest in Borneo (Sabah) as used here were published elsewhere (Huth et al, , 2005Köhler and Huth, 2004).…”

Section: Description Of the Modelmentioning

confidence: 99%

Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

Köhler

Huth

2010

Biogeosciences

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Abstract. The canopy height h of forests is a key variable which can be obtained using air-or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a ·h b ) with an r 2 ∼ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r 2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r 2 ∼ 60%) between AGB and the area fraction ofCorrespondence to: P. Köhler (peter.koehler@awi.de) gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques such as LIDAR and radar interferometry have the potential to quantify the carbon contained in the vegetation, although this calculation contains due to the heterogeneity of the forest landscape structural uncertainties which restrict future applications to spatial averages of about one hectare in size. The uncertainties in AGB for a given canopy height are here 20−40% (95% confidence level) corresponding to a standard deviation of less than ± 10%. This uncertainty on the 1 ha-scale is much smaller than in the analysis of 0.04 ha-scale data. At this small scale (0.04 ha) AGB can only be calculated out of canopy height with an uncertainty which is at least of the magnitude of the signal itself due to the natural spatial heterogeneity of these forests.

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