Partitioning the biodiversity effects on productivity into density and size components.

Plant density and size - two factors that represent plant survival and growth - are key determinants of yield but have rarely been analysed explicitly in the context of biodiversity-productivity relationships. Here, we derive equations to partition the net, complementarity and selection effects of biodiversity into additive components that reflect diversity-induced changes in plant density and size. Applications of the new method to empirical datasets reveal contrasting ways in which plant density and size regulate yield in species mixtures. In an annual plant diversity experiment, overyielding is largely explained by selection effects associated with increased size of highly productive plant species. In a tree diversity experiment, the cause of overyielding shifts from enhanced growth in tree size to reduced mortality by complementary use of canopy space during stand development. These results highlight the capability of the new method to resolve crucial, yet understudied, demographic links between biodiversity and productivity.

How biotic, abiotic, and functional variables drive belowground soil carbon stocks along stress gradient in the Sundarbans Mangrove Forest?

Mangrove forests, some of the most carbon-dense ecosystems on Earth, play an important role in climate change mitigation through storing carbon in the soil. However, increasing anthropogenic pressures and sea level rise are likely to alter mangrove forest structure and functions, including the major source of carbon in mangrove ecosystems - below-ground soil carbon stocks (BSCS). Although estimating soil carbon stocks has been a popular practice in the mangroves, but poorly understood the (I) the linkage between BSCS and key ecosystem drivers (i.e., biotic, abiotic, and functional) and in (II) determining the pathways of how BSCS and multiple forest variables interact along stress gradients. This lack of understanding limits our ability to predict ecosystem carbon dynamics under future changes in climate. Here, we aimed to understand how abiotic factors (such as salinity, canopy gap fraction, nutrients, and soil pH), biotic factors (e.g., structural parameters, canopy packing, and leaf area index, LAI), and forest functional variables (e.g., growth and aboveground biomass stocks, AGB) affect BSCS (i.e., soil organic carbon, SOC, and root carbon, RC) using spatiotemporal data collected from the Sundarbans Mangrove Forest (SMF) in Bangladesh. We observed that BSCS decreased significantly with increasing salinity (e.g., from 70.6 Mg C ha-1 in the low-saline zone to 44.6 Mg C ha-1 in the high-saline zone). In contrast, the availability of several macronutrients (such as nitrogen, phosphorous, and potassium), LAI, species diversity, AGB, and growth showed a significant positive effect on SOC and RC. Stand properties, including tree height, basal area, density, canopy packing, and structural diversity, had a non-significant but positive impact on RC, while tree height and basal area significantly influenced SOC. Pathway analysis showed that salinity affects BSCS variability directly and indirectly by regulating stand structure and restricting nutrients and forest functions, although basal area, nutrients, and LAI directly enhance RC stocks. Our results indicate that an increase in nutrient content, canopy density, species diversity, and leaf area index can enhance BSCS, as they improve forest functions and contribute to a better understanding of the underlying mechanisms.

A high-resolution approach for the spatiotemporal analysis of forest canopy space using terrestrial laser scanning data.

Forest canopies and tree crown structures are of high ecological importance. Measuring canopies and crowns by direct inventory methods is time-consuming and of limited accuracy. High-resolution inventory tools, in particular terrestrial laser scanning (TLS), is able to overcome these limitations and obtain three-dimensional (3D) structural information about the canopy with a very high level of detail. The main objective of this study was to introduce a novel method to analyze spatiotemporal dynamics in canopy occupancy at the individual tree and local neighborhood level using high-resolution 3D TLS data. For the analyses, a voxel grid approach was applied. The tree crowns were modeled through the combination of two approaches: the encasement of all crown points with a 3D α-shape, which was then converted into a voxel grid, and the direct voxelization of the crown points. We show that canopy occupancy at individual tree level can be quantified as the crown volume occupied only by the respective tree or shared with neighboring trees. At the local neighborhood level, our method enables the precise determination of the extent of canopy space filling, the identification of tree-tree interactions, and the analysis of complementary space use. Using multitemporal TLS data recordings, this method allows the precise detection and quantification of changes in canopy occupancy through time. The method is applicable to a wide range of investigations in forest ecology research, including the study of tree diversity effects on forest productivity or growing space analyses for optimal tree growth. Due to the high accuracy of this novel method, it facilitates the precise analyses even of highly plastic individual tree crowns and, thus, the realistic representation of forest canopies. Moreover, our voxel grid framework is flexible enough to allow for the inclusion of further biotic and abiotic variables relevant to complex analyses of forest canopy dynamics.