Assessing Potential Safety Zone Suitability Using a New Online Mapping Tool

Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.

Contrasts in Top Soil Infiltration Processes for Degraded vs. Restored Lands. A Case Study at the Perijá Range in Colombia

Governments are increasingly committing to significant ecological restoration. However, the impacts of forest restoration on local hydrological services are surprisingly poorly understood. Particularly, limited information is available about the impacts of tree planting on soil infiltration processes and runoff pathways. Thus, we investigated the saturated hydraulic conductivity (Ks) and preferential flow pathways in three land-cover types: (i) Active Restoration, (ii) Degraded Land, and (iii) Reference Forest, with contrasting differences in soil profile and land use history in the municipality of La Jagua de Ibirico, César department, Colombia. We conducted soil sampling, using the Beerkan method to determine Ks values. We also measured vegetation attributes (i.e., canopy cover, vegetation height, diameter at breast height, and total number of trees) and carried out three dye tracer experiments for each study site. The blue dye experiments revealed that near surface matrix infiltration was dominant for Degraded Land, while at the Active Restoration and Reference Forest, this only occurred at local surface depressions. The general infiltration pattern at the three land uses is indicated as being macropore flow with mixed interaction with the matrix and highly affected by the presence of rock fragments. The deeper infiltration patterns occur by preferential flow due to the presence of roots and rock fragments. The mean Ks for the Active Restoration (240 mm h−1) was much higher than the Ks at Degraded Land (40 mm h−1) but still considerably lower than the Reference Forest (324 mm h−1). These results indicate that top soil infiltration capacity and soil physical parameters not only directly regulate the amount of infiltration but also infiltration patterns and runoff processes, leading to lower infiltration and increased excess overland flow for Degraded Land than for other land uses.

Vegetation characteristics control local sediment and nutrient retention on but not underneath vegetation in floodplain meadows

Sediment and nutrient retention are essential ecosystem functions that floodplains provide and that improve river water quality. During floods, the floodplain vegetation retains sediment, which settles on plant surfaces and the soil underneath plants. Both sedimentation processes require that flow velocity is reduced, which may be caused by the topographic features and the vegetation structure of the floodplain. However, the relative importance of these two drivers and their key components have rarely been both quantified. In addition to topographic factors, we expect vegetation height and density, mean leaf size and pubescence, as well as species diversity of the floodplain vegetation to increase the floodplain’s capacity for sedimentation. To test this, we measured sediment and nutrients (carbon, nitrogen and phosphorus) both on the vegetation itself and on sediment traps underneath the vegetation after a flood at 24 sites along the River Mulde (Germany). Additionally, we measured biotic and topographic predictor variables. Sedimentation on the vegetation surface was positively driven by plant biomass and the height variation of the vegetation, and decreased with the hydrological distance (total R2 = 0.56). Sedimentation underneath the vegetation was not driven by any vegetation characteristics but decreased with hydrological distance (total R2 = 0.42). Carbon, nitrogen and phosphorus content in the sediment on the traps increased with the total amount of sediment (total R2 = 0.64, 0.62 and 0.84, respectively), while C, N and P on the vegetation additionally increased with hydrological distance (total R2 = 0.80, 0.79 and 0.92, respectively). This offers the potential to promote sediment and especially nutrient retention via vegetation management, such as adapted mowing. The pronounced signal of the hydrological distance to the river emphasises the importance of a laterally connected floodplain with abandoned meanders and morphological depressions. Our study improves our understanding of the locations where floodplain management has its most significant impact on sediment and nutrient retention to increase water purification processes.

Both landscape heterogeneity and configuration determine Woodlarks (Lullula arborea) breeding territories

Farmland birds have declined in the last decades mostly due to agriculture intensification. The Woodlark Lullula arborea, a farmland species of conservation concern and protected by the European Bird Directive, occurs in a variety of habitats across its geographic range. Although habitat heterogeneity has been recognized as a key feature, the preference or avoidance of particular habitat attributes might differ across its range because different localities may have distinct conditions. Such variation would challenge conservation efforts at the local level. Our aim was to assess habitat associations of Woodlarks and determine whether the habitat attributes identified as important in other locations across its range could be generalised and applied to Austrian populations. In addition, habitat associations can be influenced by land-use change. We examined changes in land use from 2007 to 2016 in 15 municipalities surrounding areas occupied by Woodlarks. We quantified the composition and configuration of the local landscape surrounding 18 singing males’ territories and 16 non-territory sites. We found that the probability of Woodlarks territories increased with landscape heterogeneity between 50% and 70%, increased with dispersed bare soil patches, decreased with overall patch density and were away from dirt roads. Contrary to our expectation, there was no indication of land-use change. In contrast to previous studies, vegetation height, the presence and proximity to woodland were not identified as important habitat characteristics. Thus, some conservation recommendations can be derived from other localities, for example, maintaining or enhancing landscape heterogeneity. However, others should be adapted to local conditions. In Austria, conservation efforts should focus on including dispersed patches of bare soil and limiting the development of dirt roads nearby Woodlark territories, in addition to promoting a heterogeneous landscape.

Estimating Ground Elevation and Vegetation Characteristics in Coastal Salt Marshes Using UAV-Based LiDAR and Digital Aerial Photogrammetry

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured on a Spartina alterniflora-dominated salt marsh in Little Sapelo Island, USA. The method produces high-resolution (ground sampling distance = 0.40 m) maps of ground elevation and vegetation characteristics and captures the large gradients in the proximity of tidal creeks. Our results show that LiDAR-based techniques provide more accurate reconstructions of marsh vegetation (height: MAEVH = 12.6 cm and RMSEVH = 17.5 cm; density: MAEVD = 6.9 stems m−2 and RMSEVD = 9.4 stems m−2) and morphology (MAEM = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAEVH = 31.1 cm; RMSEVH = 38.1 cm; MAEVD = 12.7 stems m−2; RMSEVD = 16.6 stems m−2; MAEM = 11.3 cm; RMSEM = 17.2 cm). The accuracy of the classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters together with the LiDAR-UAV point cloud (MAEVH = 6.9 cm; RMSEVH = 9.4 cm; MAEVD = 10.0 stems m−2; RMSEVD = 14.0 stems m−2). However, it improves when used together with the DAP-UAV point cloud (MAEVH = 21.7 cm; RMSEVH = 25.8 cm; MAEVD = 15.2 stems m−2; RMSEVD = 18.7 stems m−2). Thus, we discourage using DAP-UAV-derived point clouds for high-resolution vegetation mapping of coastal areas, if not coupled with other data sources.

Experimental evidence for opposing effects of high deer density on tick-borne pathogen prevalence and hazard

Background Identifying the mechanisms driving disease risk is challenging for multi-host pathogens, such as Borrelia burgdorferi sensu lato (s.l.), the tick-borne bacteria causing Lyme disease. Deer are tick reproduction hosts but do not transmit B. burgdorferi s.l., whereas rodents and birds are competent transmission hosts. Here, we use a long-term deer exclosure experiment to test three mechanisms for how high deer density might shape B. burgdorferi s.l. prevalence in ticks: increased prevalence due to higher larval tick densities facilitating high transmission on rodents (M1); alternatively, reduced B. burgdorferi s.l. prevalence because more larval ticks feed on deer rather than transmission-competent rodents (dilution effect) (M2), potentially due to ecological cascades, whereby higher deer grazing pressure shortens vegetation which decreases rodent abundance thus reducing transmission (M3). Methods In a large enclosure where red deer stags were kept at high density (35.5 deer km−2), we used an experimental design consisting of eight plots of 0.23 ha, four of which were fenced to simulate the absence of deer and four that were accessible to deer. In each plot we measured the density of questing nymphs and nymphal infection prevalence in spring, summer and autumn, and quantified vegetation height and density, and small mammal abundance. Results Prevalence tended to be lower, though not conclusively so, in high deer density plots compared to exclosures (predicted prevalence of 1.0% vs 2.2%), suggesting that the dilution and cascade mechanisms might outweigh the increased opportunities for transmission mechanism. Presence of deer at high density led to shorter vegetation and fewer rodents, consistent with an ecological cascade. However, Lyme disease hazard (density of infected I. ricinus nymphs) was five times higher in high deer density plots due to tick density being 18 times higher. Conclusions High densities of tick reproduction hosts such as deer can drive up vector-borne disease hazard, despite the potential to simultaneously reduce pathogen prevalence. This has implications for environmental pathogen management and for deer management, although the impact of intermediate deer densities now needs testing. Graphical abstract

Forest restoration after alluvial gold mining can recover vegetation structure. A case study in Colombia

Technical reclamation and spontaneous succession (passive restoration) are the two main approaches for restoring post-mining sites worldwide. Despite substantial differences between both approaches, little is known regarding how they differ in terms of ecological outcomes. We assessed and compared the vegetation structure and composition in one spontaneous succession forest that is 29 years old, two technically reclaimed forests that are 2 and 10 years old after alluvial gold mining, and one old-growth reference forest in northeastern Antioquia, Colombia. We sampled trees and saplings establishing three Modified-Whittaker Plots in each site. We measured tree basal area, canopy cover, vegetation height, tree density, and species richness. Vegetation structure and composition differed considerably among restoration approaches. Species richness was significantly greater in the spontaneous succession forest than at the other sites. Similarly, technical reclamation significantly increased the vegetation attributes after 10 years, reaching values similar to the reference forest. We underscore the importance of fast-growth planted species (Acacia mangium, Samanea saman, and Schizolobium parahyba) to revegetate mining degraded lands.

The three major axes of terrestrial ecosystem function

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Quantifying the Spatial Variability of Annual and Seasonal Changes in Riverscape Vegetation Using Drone Laser Scanning

Riverscapes are complex ecosystems consisting of dynamic processes influenced by spatially heterogeneous physical features. A critical component of riverscapes is vegetation in the stream channel and floodplain, which influences flooding and provides habitat. Riverscape vegetation can be highly variable in size and structure, including wetland plants, grasses, shrubs, and trees. This vegetation variability is difficult to precisely measure over large extents with traditional surveying tools. Drone laser scanning (DLS), or UAV-based lidar, has shown potential for measuring topography and vegetation over large extents at a high resolution but has yet to be used to quantify both the temporal and spatial variability of riverscape vegetation. Scans were performed on a reach of Stroubles Creek in Blacksburg, VA, USA six times between 2017 and 2019. Change was calculated both annually and seasonally over the two-year period. Metrics were derived from the lidar scans to represent different aspects of riverscape vegetation: height, roughness, and density. Vegetation was classified as scrub or tree based on the height above ground and 604 trees were manually identified in the riverscape, which grew on average by 0.74 m annually. Trees had greater annual growth and scrub had greater seasonal variability. Height and roughness were better measures of annual growth and density was a better measure of seasonal variability. The results demonstrate the advantage of repeat surveys with high-resolution DLS for detecting seasonal variability in the riverscape environment, including the growth and decay of floodplain vegetation, which is critical information for various hydraulic and ecological applications.