Publications

Datafile accompanying the publication Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests. (https://doi.org/10.1016/j.foreco.2023.121414) This datafile entails the raw seedlings data which were used to calculate tree diversity and forest structure parameters presented in the above-named publication and in the following repository: https://doi.org/10.5281/zenodo.8041128 Use of these data require citation of this dataset and the associated publication (Keller et al. submitted). We also require that you inform us of the use of the data would also appreciate the opportunity to be involved in work making use of this data. The required citations are follows: Marfil, Tobias, Keller, Nadine, Bin Abd Karim, Bin Jelling, Steven, Zenden, & Philipson, Christopher D. (2023). 'Danum Revised' seedling data for twenty-seven 4 m2 field plots, measured in 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8063292 Keller, Nadine, Pascal A Niklaus, Jaboury Ghazoul, Tobias Marfil, Elia Godoong, and Christopher D Philipson. 2023. "Biodiversity Consequences of Long-Term Active Forest Restoration in Selectively-Logged Tropical Rainforests." Forest Ecology and Management 549: 4. https://doi.org/10.1016/j.foreco.2023.121414.

The role of conspecific density dependence (CDD) in the maintenance of species richness is a central focus of tropical forest ecology. However, tests of CDD often ignore the integrated effects of CDD over multiple life stages and their long-term impacts on population demography. We combined a 10-year time series of seed production, seedling recruitment and sapling and tree demography of three dominant Southeast Asian tree species that adopt a mast-fruiting phenology. We used these data to construct individual-based models that examine the effects of CDD on population growth rates ( λ ) across life-history stages. Recruitment was driven by positive CDD for all species, supporting the predator satiation hypothesis, while negative CDD affected seedling and sapling growth of two species, significantly reducing λ . This negative CDD on juvenile growth overshadowed the positive CDD of recruitment, suggesting the cumulative effects of CDD during seedling and sapling development has greater importance than the positive CDD during infrequent masting events. Overall, CDD varied among positive, neutral and negative effects across life-history stages for all species, suggesting that assessments of CDD on transitions between just two stages (e.g. seeds seedlings or juveniles mature trees) probably misrepresent the importance of CDD on population growth and stability.

During the 2005–2007 June–September ablation seasons, meteorological conditions were recorded on the lower and upper parts of the debris‐covered ablation zone of Miage Glacier, Italy. In 2005, debris temperature and subdebris ice melt were also monitored at 25 points with debris thickness of 0.04–0.55 m, spread over 5 km 2 of the glacier. The radiative fluxes were directly measured, and near‐closure of the surface energy balance is achieved, providing support for the bulk aerodynamic calculation of the turbulent fluxes. Surface‐layer meteorology and energy fluxes are dominated by the pattern of incoming solar radiation which heats the debris, driving strong convection. Mean measured subdebris ice melt rates are 6–33 mm d −1 , and mean debris thermal conductivity is 0.96 W m −1 K −1 , displaying a weak positive relationship with debris thickness. Mean seasonal values of the net shortwave, net longwave, and debris heat fluxes show little variation between years, despite contrasting meteorological conditions, while the turbulent latent (evaporative) heat flux was more than twice as large in the wet summer of 2007 compared with 2005. The increase in energy output from the debris surface in response to increasing surface temperature means that subdebris ice melt rates are fairly insensitive to atmospheric temperature variations in contrast to debris‐free glaciers. Improved knowledge of spatial patterns of debris thickness distribution and 2 m air temperature, and the controls on evaporation of rainwater from the surface, are needed for distributed physically based melt modeling of debris‐covered glaciers.

. Borneo contains some of the world’s most biodiverse and carbon dense tropical forest, but this 750 000-km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognising the ecosystem services they provide, including their ability to store and sequester carbon. Airborne Laser Scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into state-wide assessment of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen, new regional models, need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rain forests of Sabah, on the island of Borneo, we develop a simple-yet-general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbons stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions, and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalised and effective approach for mapping forest carbon stocks in Borneo, and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.

Data file accompanying the publication Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests. (https://doi.org/10.1016/j.foreco.2023.121414) This data file entails the calculated tree diversity and forest structure parameters presented in the above-named publication. The raw data on the adult tree data per plot can be accessed in the following repository: https://doi.org/10.5281/zenodo.8042468 , and the raw data on the seedling data per plot can be accessed in the following repository: https://zenodo.org/record/8063292 Use of these data require citation of this dataset, the raw data on adult trees, the raw data on seedlings, the associated publication (Keller et al. submitted), as well as the 2017 dataset (which describes the full set up process). We also require that you inform us of the use of the data would also appreciate the opportunity to be involved in work making use of this data. The required citations are follows: Keller, Nadine, Niklaus, Pascal A., Ghazoul, Jaboury, Marfil, Tobias, Godoong, Elia, & Philipson, Christopher D. (2023). TreeDiversity_ForestStructure [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8041128 Keller, Nadine, Karolus, Alexander, Murus, Remmy, O'Brien, Michael, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Philipson, Christopher D. (2023). 'Danum Revised' forest field plot data for thirty-five 0.28 hectare field plots, measured in 2020 (0.9) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042468 Marfil, Tobias, Keller, Nadine, Bin Abd Karim, Bin Jelling, Steven, Zenden, & Philipson, Christopher D. (2023). 'Danum Revised' seedling data for twenty-seven 4 m2 field plots, measured in 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8063292 Keller, Nadine, Pascal A Niklaus, Jaboury Ghazoul, Tobias Marfil, Elia Godoong, and Christopher D Philipson. 2023. "Biodiversity Consequences of Long-Term Active Forest Restoration in Selectively-Logged Tropical Rainforests." Forest Ecology and Management 549: 4. https://doi.org/10.1016/j.foreco.2023.121414. Philipson, Christopher D., Brodrick, Philip G., Milne, Sol, Murus, Remmy, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Asner, Gregory P. (2023). 'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017 (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042050

No abstract is provided for this article.

1. Soil infiltration capacity determines the partitioning of precipitation into infiltration and overland flow and is therefore an important soil hydrological characteristic. Water infiltration through soil is facilitated by macropores created by roots and soil macrofauna. In clay‐rich soils, such as those of the tropical forests of Sabah, Malaysian Borneo, most infiltration occurs via these preferential flow pathways. 2. We evaluated the effects of dung beetle tunnelling on infiltration and macropore creation (depth and width of the flow pathways) in tropical forest soils in Sabah. Using mesocosms, we applied three treatments (i) soil‐only, (ii) dung‐only, (iii) dung + dung beetles, and measured saturated hydraulic conductivity (i.e., the steady‐state infiltration rate) after 0, 5 and 10 days, and assessed depth and width of infiltration pathways by applying a blue dye tracer. 3. The steady‐state infiltration rate increased in the presence of dung beetles, though differences among treatments were only statistically significant after 10 days. After 5 days of dung beetle presence, infiltrated water had reached a greater depth than the control mesocosms without beetles. However, there were no differences in the width of infiltration pathways among treatments. 4. These results reveal the important, but under studied roles of dung beetles on soil hydrological functioning, that may have consequences for nutrient cycling and plant productivity. Further, our findings indicate that the novel application of an established hydrological method—blue dye tracer—can provide interesting and reliable results for macrofauna–soil interaction studies.

No abstract is provided for this article.

Mudflats are critical interfaces between the marine and terrestrial environment of muddy coasts. Mapping mudflat surface sediment types and analyzing their dynamic changes are helpful to understand the variations of sedimentary environments and their responses to tidal current movements. To obtain the surface sediment types of the mudflats, this study first took the chlorophyll-a content as an environmental variable and combined it with satellite spectral reflectance data processed by fractional-order derivative (FOD) to establish a machine learning model for retrieving sediment component content (SCC) of the sand, silt, and clay. Then, the three SCCs were linear equilibrium corrected and inputted into Folk's ternary classification model, and the spatial distribution map of the sediment types was accurately obtained. The results showed that the use of the FODs for satellite image enhancement could provide richer spectral information and improve the accuracy of the chlorophyll-a content and SCCs inversed by the grid search-support vector machine (GS-SVM) model. When compared to direct spectral modeling, considering the effect of the chlorophyll-a content as the key input factor, the coefficients of determination (R 2) for the sand, silt, and clay contents inversion were increased by 15.1, 9.2, and 38.2%, and the root mean square error (RMSE) were reduced by 9.7, 5.5, and 2.5%, respectively. Surface sediment type maps obtained from the three SCCs showed that the main sediments in the mudflats on the central coast of Jiangsu Province, China were silty sand and sandy silt. Between 2019 and 2021, the sediment types in 84.46% of the total area were unchanged. For the changing area, the sediment transitioned toward finer-grained types near the seawall of the coastal region. Whereas in the offshore area, especially along the edge of the huge tidal channels, the sediments tended to be coarser because of strong hydrodynamic screening. The findings will be helpful for improving the ability of mudflat sedimentation environmental monitoring and spatial resource management via remote sensing.