Physical structure and biological composition of canopies in tropical secondary and old-growth forests

The area of tropical secondary forests is increasing rapidly, but data on the physical and biological structure of the canopies of these forests are limited. To obtain such data and to measure the ontogeny of canopy structure during tropical rainforest succession, we studied patch-scale (5 m2) canopy structure in three areas of 18–36 year-old secondary forest in Costa Rica, and compared the results to data from old-growth forest at the same site. All stands were sampled with a stratified random design with complete harvest from ground level to the top of the canopy from a modular portable tower. All canopies were organized into distinct high- and low-leaf-density layers (strata), and multiple strata developed quickly with increasing patch height. The relation of total Leaf Area Index (LAI, leaf area per area of ground) to patch canopy height, the existence of distinct high and low leaf- density layers (strata and free air spaces), the depth and LAI of the canopy strata and free air spaces, and the relation of the number of strata to patch canopy height were remarkably constant across the entire successional gradient. Trees were the most important contributor to LAI at all stages, while contribution of palm LAI increased through succession. We hypothesize that canopy physical structure at the patch scale is driven by light competition and discuss how this hypothesis could be tested. That canopy physical structure was relatively independent of the identity of the species present suggests that canopy physical structure may be conserved even as canopy floristics shift due to changing climate.

Estimating Floodplain Vegetative Roughness Using Drone-Based Laser Scanning and Structure from Motion Photogrammetry

Vegetation heights derived from drone laser scanning (DLS), and structure from motion (SfM) photogrammetry at the Virginia Tech StREAM Lab were utilized to determine hydraulic roughness (Manning’s roughness coefficients). We determined hydraulic roughness at three spatial scales: reach, patch, and pixel. For the reach scale, one roughness value was set for the channel, and one value for the entire floodplain. For the patch scale, vegetation heights were used to classify the floodplain into grass, scrub, and small and large trees, with a single roughness value for each. The roughness values for the reach and patch methods were calibrated using a two-dimensional (2D) hydrodynamic model (HEC-RAS) and data from in situ velocity sensors. For the pixel method, we applied empirical equations that directly estimated roughness from vegetation height for each pixel of the raster (no calibration necessary). Model simulations incorporating these roughness datasets in 2D HEC-RAS were validated against water surface elevations (WSE) from seventeen groundwater wells for seven high-flow events during the Fall of 2018 and 2019, and compared to marked flood extents. The reach method tended to overestimate while the pixel method tended to underestimate the flood extent. There were no visual differences between DLS and SfM within the pixel and patch methods when comparing flood extents. All model simulations were not significantly different with respect to the well WSEs (p > 0.05). The pixel methods had the lowest WSE RMSEs (SfM: 0.136 m, DLS: 0.124 m). The other methods had RMSE values 0.01–0.02 m larger than the DLS pixel method. Models with DLS data also had lower WSE RMSEs by 0.01 m when compared to models utilizing SfM. This difference might not justify the increased cost of a DLS setup over SfM (~150,000 vs. ~2000 USD for this study), though our use of the DLS DEM to determine SfM vegetation heights might explain this minimal difference. We expect a poorer performance of the SfM-derived vegetation heights/roughness values if we were using a SfM DEM, although further work is needed. These results will help improve hydrodynamic modeling efforts, which are becoming increasingly important for management and planning in response to climate change, specifically in regions were high flow events are increasing.

Quantification of N2O fluxes and EF values in a pasture using chamber and eddy-covariance technique

<p>In grassland ecosystems nitrogen (N) inputs are mainly attributed to fertilizer applications for increasing  herbage productivity and to excreta of grazing animals. Cattle, for instance, excrete 75-95 % of the N intake. Accordingly, dung and urine patches of grazing animals form hotspots of nitrate leaching and gaseous N emissions as ammonia (NH<sub>3</sub>) or the important greenhouse gas nitrous oxide (N<sub>2</sub>O). Global default emission factor (EF) values for N<sub>2</sub>O, 2.0 % for grazing based nitrogen inputs (EF3) and 1.0 % for nitrogen inputs via fertilizer applications (EF1) have been suggested by IPCC. However, some countries like New Zealand, Canada or the Netherlands have established country-specific EFs showing considerable regional differences.</p><p>In the present research study, we examine N<sub>2</sub>O emissions of a pasture field in Switzerland in relation to possible drivers. Field scale emissions by eddy covariance are measured in parallel to patch-scale N<sub>2</sub>O fluxes from controlled applications of urine, dung and fertilizer. The patch-scale fluxes are measured by a manually operated chamber ('fast-box') connected to an online gas analyzer. Besides estimating EF values on annual and seasonal basis, relevant factors that might control N<sub>2</sub>O fluxes like environmental conditions (weather parameters, soil moisture, soil temperature), vegetation characteristics (height, composition, nitrogen and carbon content) and pasture management (patch age, grazing, fertilization, cut events, interactive effects) are analyzed. </p><p>We present and discuss results of the first measurement year 2020. Three artificial urine applications during summer and autumn were performed. They show peak N<sub>2</sub>O fluxes of 279-1718 μg m<sup>-2</sup> h<sup>-1</sup> directly after application that decrease to near-background fluxes within 19-43 days. Using a simple linear interpolation of measured N<sub>2</sub>O fluxes, EF values of artificial urine patches vary between 0.57 and 2.44 % indicating a seasonal variability of N<sub>2</sub>O fluxes.</p>

Disturbance, patches and mosaics

This chapter introduces the range of biological and physical processes that disturb soft sediment. It introduces the concept of disturbance regimes that connect the extent, frequency and magnitude of disturbance. Post-disturbance recovery processes are described in terms of processes that occur within the disturbed patch and processes that influence recovery from outside the patch. Moving on from the patch scale, the chapter introduces the concept of patch dynamics and the concept of the seafloor as a mosaic of patches at different stages of recovery from disturbance. Connectivity between patches is a critical factor linking local recovery processes to landscape-scale processes. This mosaic perspective leads to the introduction of metacommunity dynamics and the potential for heterogeneous landscapes to fragment and eventually homogenise seafloor communities as a consequence of the loss of large habitat-defining species.

Rusty Blackbirds select areas of greater habitat complexity during stopover

The Rusty Blackbird (Euphagus carolinus) is a widespread, uncommon migrant that has experienced heavy population declines over the last century. This species can spend over a quarter of their annual cycle on migration, so it is important to determine their habitat requirements during stopover events to inform effective conservation planning. We assessed their habitat selection at an important stopover site in northern Ohio during both fall and spring migration. Since stopover habitat selection is scale-dependent, we investigated both patch-scale (between patches) and fine-scale (within a patch) selection using radio telemetry to locate foraging and roosting flocks, and compared habitat variables between used and available points across the study site. At the patch scale, we found that birds preferred dogwood–willow swamp, low-lying forest patches, and areas of greater habitat complexity for foraging in both seasons. At the fine scale, spring migrants foraged closer to habitat edges than random, and preferred areas with more wet leaf litter and shallow water, and less grass cover. Fall migrants also preferred shallow water and leaf litter cover, and avoided areas with dense grass, forbs, and herbaceous shrub cover. By contrast, birds consistently roosted in dense stands of emergent Phragmites or Typha marsh, suggesting that the best stopover or staging sites are those with a matrix of different wetland habitats. Although the migratory range of Rusty Blackbirds is currently dominated by agricultural development, our results suggest that fragmented landscapes can still provide adequate habitat for migrants if the available land is managed for a variety of wet habitat types.