Heterogeneous Vegetation Research Articles

Spatial Scaling of Gross Primary Productivity Over Sixteen Mountainous Watersheds Using Vegetation Heterogeneity and Surface Topography

AbstractLand surface models intended for large‐scale applications are often executed at coarse resolutions, and the sub‐grid heterogeneity is usually ignored. Here, a spatial scaling algorithm that integrates the information of vegetation heterogeneity (land cover type and leaf area index) and surface topography (elevation, slope, relative azimuth (Raz) between the sun and the slope background, sky‐view factor, and topographic wetness index), was proposed to correct errors in gross primary productivity (GPP) estimates at a coarse spatial resolution. An eco‐hydrological model named BEPS‐TerrainLab was used to simulate GPP at 30 and 480 m resolutions for 16 mountainous watersheds selected globally. Results showed that an obvious improvement on GPP estimates at 480 m resolution was achieved after the correction in comparison with GPP modeled at 30 m resolution, with the determination coefficient increased by 0.38 and mean bias error reduced by 203gCm−2 yr−1. The combination of all the seven factors made the largest improvement for GPP estimation at 480 m resolution, suggesting that a larger improvement would be achieved when more factors of surface heterogeneity are considered. More specifically, our results indicated that five factors, including land cover type and leaf area index regarded as integrated outcomes of all the environmental conditions, Raz and sky‐view factor associated with radiation redistribution, and slope related to soil water redistribution, were especially important in the spatial scaling procedure. This study suggests that incorporating the information of surface heterogeneity into the spatial scaling algorithm is useful for improving coarse resolution GPP estimates over mountainous areas.

Assessment of snail communities in fragmented habitats

Forest fragmentation is an increasing commonality with the continued rise in disturbances from extractive industries and various anthropogenic activities. While research has observed negative effects of fragmentation such as ecotones, the impact on specific organisms is unknown. Sites were selected in three forests that have been fragmented by power lines, three forests fragmented by pipelines, and three primarily undisturbed forests to assess snail communities. Beginning at the edge of the disturbance, every 25, 50, 75, and 100m into the forest, two 1m2 quadrats were sampled on each side. Environmental data was collected along with snails visible to the naked eye; leaf litter was placed in bags and sieved for microsnails. Abundance and species richness were highest among the control sites, followed by power line rights-of-way. Since power lines have been around longer than pipelines, hypotheses conclude that snail communities need substantial time to repopulate fragmented forests. Species richness may never completely recover due to generalist and/or invasive species overtaking and outcompeting native species in these disturbed habitats. Surprisingly, environmental factors such as vegetation heterogeneity, soil temperature, and canopy cover showed no significant correlations with snail abundance or species richness. Besides site type, the driving force behind snail abundance and species richness appears to be distance from disturbance. Species richness significantly increased with distance from the disturbance. While abundance was not significant given distance from the disturbance, there was a clear observable trend. More sites should be sampled in the future as trends may likely display significance with more available data.

Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations

AbstractAccurate simulations of high‐latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Many such models represent high‐latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine Arctic‐specific PFTs. The newly developed PFTs include: (1) nonvascular mosses and lichens, (2) deciduous and evergreen shrubs of various height classes, including an alder PFT, (3) graminoids, and (4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario and constant PFT fractional areas showed alder‐dominated plant communities gaining more biomass and lichen‐dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.

A new record of Paramylodon harlani (Owen 1840) (Xenarthra, Pilosa, Mylodontidae) from the late Pleistocene of Valsequillo, Puebla, with comments on its paleobiogeography and paleoecology in Mexico

Paramylodon harlani was a large ground sloth recorded across North America, from Canada to Mexico. In Mexico, it is known from several late Pleistocene localities, but most of these records just mention the taxon in passing and few specimens have been described or illustrated. In this work, we describe a left tibia from the Valsequillo Basin, Puebla state. Its morphology and measurements allowed us to identify it as Paramylodon harlani, adding a new record for Mexico. In Mexico, P. harlani occurred mainly in the Trans-Mexican Volcanic Belt, central Mexico, with some records in the north and southeastern part of the country. Most localities are located between 1500 to 2000 m.a.s.l. Paleoenvironmental and paleoclimatic inference in some localities of Mexico where P. harlani occurred, showed heterogenous vegetation dominated by grasslands, and agree with the preferred habitat proposed for this species based on localities in the United States. This indicates that P. harlani could inhabit different environments, from grasslands to more wooded areas, and this adaptation allowed it to extend its range from the north to the southeast of Mexico.

High Spatial and Temporal Resolution Energy Flux Mapping of Different Land Covers Using an Off-the-Shelf Unmanned Aerial System

With the development of low-cost, lightweight, integrated thermal infrared-multispectral cameras, unmanned aerial systems (UAS) have recently become a flexible complement to eddy covariance (EC) station methods for mapping surface energy fluxes of vegetated areas. These sensors facilitate the measurement of several site characteristics in one flight (e.g., radiometric temperature, vegetation indices, vegetation structure), which can be used alongside in-situ meteorology data to provide spatially-distributed estimates of energy fluxes at very high resolution. Here we test one such system (MicaSense Altum) integrated into an off-the-shelf long-range vertical take-off and landing (VTOL) unmanned aerial vehicle, and apply and evaluate our method by comparing flux estimates with EC-derived data, with specific and novel focus on heterogeneous vegetation communities at three different sites in Germany. Firstly, we present an empirical method for calibrating airborne radiometric temperature in standard units (K) using the Altum multispectral and thermal infrared instrument. Then we provide detailed methods using the two-source energy balance model (TSEB) for mapping net radiation (Rn), sensible (H), latent (LE) and ground (G) heat fluxes at <0.82 m resolution, with root mean square errors (RMSE) less than 45, 37, 39, 52 W m−2 respectively. Converting to radiometric temperature using our empirical method resulted in a 19% reduction in RMSE across all fluxes compared to the standard conversion equation provided by the manufacturer. Our results show the potential of this UAS for mapping energy fluxes at high resolution over large areas in different conditions, but also highlight the need for further surveys of different vegetation types and land uses.

Assessment of spectral indexes for estimating soil water content in the Brazilian Pantanal

The Pantanal is the largest floodplain of the globe occupying 138,183 km2 in Brazil. The fundamental ecological factor of interaction between the Pantanal ecosystems is the flooding regime. Connected to properties of the soil-plant-atmosphere system, knowledge on the soil water content becomes increasingly necessary. The high temporal and spatial variability of water content in the soil caused by the vast heterogeneity of soil texture, vegetation, topography and climate makes it a difficult physical variable to be measured. However, its spatial and temporal variability can be determined by recent modern techniques of remote sensing based on data obtained by microwave or infrared sensors. Thus, the aim of this study was to evaluate the accuracy of vegetation and soil water indexes through satellite images from Landsat 5 in the northern Brazilian Pantanal. The study was conducted in a pasture, experimental site in the Northern Pantanal in Mato Grosso state. Soil moisture was measured using a TDR probe installed at 10 cm depth in the period from 2009 to 2011. For comparison, spectral indexes and the surface temperature provided by Geological Survey (USGS) were used, these indexes are derived from bands ratios of satellite reflectance products Landsat 5 TM. The data evaluation was performed using some indicators: accuracy - Willmott index, Root Mean Square Error and the Mean Absolute Error. This study demonstrated that the application of remote sensing in the management of water resources is very promising. The indexes correlated with soil moisture measurement. Among the soil water indexes the NBR-2 showed related to soil moisture measurement. For both types of soils EVI had the highest determination coefficient, lowest errors and highest Willmott’s index of agreement.

Applying a high-precision tracking system to distinguish the spatiotemporal patterns of animal movement in grassland ecology

Spatial heterogeneity in vegetation may derive from variation in animal movement patterns, but these patterns have been difficult to study at the fine spatial and temporal resolutions necessary to relate them to small-scale vegetation patterns. Here, we demonstrated the utility of Ultra-WideBand (UWB) technology to examine animal movement patterns. We evaluated UWB performance in a field setting and illustrated how these data could distinguish movement patterns of different types of livestock during day and night. The data were of high spatial resolution (within 9.7 cm ± 1.7 cm of actual locations) and high temporal resolution (every second). The positional data clearly demonstrated differential movement patterns between a cow and ewe and between daytime and nighttime. Furthermore, patterns were spatially heterogeneous: the cow spent up to 5% of the day in a single 1 m2 square and the ewe up to 7.6% of the day in a single square. Over the course of one day, the cow visited about two-thirds of the plot whereas the ewe visited about half of the plot. Our study suggests that UWB technology is a practical tool to describe animal movement at fine spatial and temporal scales. We note some limitations of this technology (battery life, receiver range, and cost) and end by identifying some opportunities for it to improve ecology and conservation, particularly when combined with other data or technologies such as high-resolution vegetation mapping.

Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment

The need for fine scale description of vegetation structure is increasing as Leaf Area Density (LAD, m2/m3) becomes a critical parameter to understand ecosystem functioning and energy and mass fluxes in heterogeneous ecosystems. Terrestrial Laser Scanning (TLS) has shown great potential for retrieving the foliage area at stand, plant or voxel scales. Several sources of measurement errors have been identified and corrected over the past years. However, measurements remain sensitive to several factors, including, 1) voxel size and vegetation structure within voxels, 2) heterogeneity in sampling from TLS instrument (occlusion and shooting pattern), the consequences of which have been seldom analyzed at the scale of forest plots. In the present paper, we aimed at disentangling biases and errors in plot-scale measurements of LAD with TLS in a simulated vegetation scene. Two negative biases were formerly attributed to (i) the unsampled voxels and to (ii) the subgrid vegetation heterogeneity (i.e. clumping effect), and then quantified, thanks to a the simulation experiment providing known LAD references at voxel scale, vegetation manipulations and unbiased point estimators. We used confidence intervals to evaluate voxel-scale measurement accuracy.We found that the unsampled voxel effect (i) led to underestimations with the “mean layer” method –commonly used to fill unsampled voxels- for small voxels (0.1–0.2 m) and/or low number of scans (<4). It was explained by the spatial correlations in vegetation, which induced that dense voxels were more often occluded by dense neighbors than light voxels. The distribution of the bias was heterogeneous in canopy, the bias being stronger at mid canopy where occlusion started, but smaller in highly-occluded upper layers. This somehow counterintuitive result was explained by a more random sampling of upper layers, but could highly depend on vegetation structure.The subgrid vegetation heterogeneity effect (ii) was confirmed to increase with voxel size, yet, the magnitude of this bias -quantified with vegetation manipulation- was found to be more homogeneously-distributed than the unsampled voxel effect.Overall, we found that no scenario was unbiased. However, an intermediate voxel size (0.5 m) was the best option, because the relatively homogeneous subgrid effect could be handled with a single correction factor and voxel-scale measurements errors were reasonable. On the contrary, smaller voxels led to poor voxel-scale measurements and variable biases in magnitude and spatial distribution with sampling design. However, more similar research in other context is required to adapt these conclusions to other forest plots.

Anthills as habitat islands in a sea of temperate pasture

Ants can shape vegetation as seed dispersers and ecosystem engineers. When anthills are long-lasting, they are known to change soil and vegetation characteristics. However, it is unclear whether plant species traits and species composition vary between ant guilds and between parts of individual anthills. We compared different aspects of soil and vegetation (composition, seedling abundance, and functional traits) between anthills and the surrounding mesophilous pasture in Czechia. This pasture hosts eight ant species, which belong to both seed dispersers and non-dispersers. Where feasible, we divided anthills into centres and margins for the analyses. Anthills (area 90.5–4051.7 cm2; 5–19 plant species) displayed different and more heterogeneous (less similar within anthill plot type) vegetation composition when compared to the surrounding area, with more seedlings and several species restricted to anthills. Further, anthills were more functionally diverse and exhibited several differences in traits, both at the community and intraspecific level. Anthill centres had higher surface temperatures in hot sunny days, higher levels of phosphorus and pH than margins, while margins had higher moisture and carbon content than surrounding vegetation. Further, anthill vegetation differed between ant guilds with more myrmecochorous species found at nests of seed dispersers. Overall heterogeneity in this mesophilous pasture was enhanced by the presence of anthills. Further, the anthills themselves are heterogeneous due to variable sizes, persistence, and differences between their centres and margins on long-lasting anthills. Anthills can thus enhance plant diversity by maintaining disturbed microsites and enhancing the growth of seedlings and less competitive plants.

Greater Sage-Grouse nest bowls buffer microclimate in a post-megafire landscape although effects on nest survival are marginal

AbstractTemperature at fine spatial scales is an important driver of nest site selection for many avian species during the breeding season and can influence nest success. Sagebrush (Artemisia spp.) communities have areas with high levels of vegetation heterogeneity and high thermal variation; however, fire removes vegetation that provides protection from predators and extreme environmental conditions. To examine the influence of microclimates on Greater Sage-Grouse (Centrocercus urophasianus) nest site selection and nest success in a fire-affected landscape, we measured black bulb temperature (Tbb) and vegetation attributes (e.g., visual obstruction) at 3 spatial scales (i.e. nest bowl, microsite, and landscape) in unburned and burned areas. Nest bowls exhibited greater buffering of Tbb than both nearby microsites and the broader landscape. Notably, nest bowls were warmer in cold temperatures, and cooler in hot temperatures, than nearby microsites and the broader landscape, regardless of burn stage. Nest survival (NS) was higher for nests in unburned areas compared to nests in burned areas (unburned NS = 0.43, 95% confidence interval [CI]: 0.33–0.54; burned NS = 0.24, 95% CI: 0.10–0.46). The amount of bare ground was negatively associated with NS, but effects diminished as the amount of bare ground reached low levels. Shrub height and visual obstruction were positively associated with NS during the entire study period, whereas minimum Tbb had a weaker effect. Our findings demonstrate that thermoregulatory selection by Greater Sage-Grouse at nest sites had marginal effects on their NS. However, given that increases in vegetation structure (e.g., shrub height) provide thermal refuge and increase NS, vegetation remnants or regeneration in a post-fire landscape could be critical to Greater Sage-Grouse nesting ecology.

Comparing the browsing behavior of inexperienced kids versus adult goats on heterogeneous vegetation

The present study compared the feeding behavior of inexperienced kids on heterogeneous vegetation with that of adult goats with browsing experience. Twelve non-pregnant, non-lactating adult Criollo goats (35 ± 5 kg live weight (LW)) with >3 years of browsing experience and ten weaned kids (19 ± 3 kg LW) without previous browsing experience were used. The two groups of animals browsed simultaneously on 10.2 ha of tropical heterogeneous vegetation (4 h daily) in the rainy season. Mouth dimensions (width and length) were determined from contemporary animals in the same herd (14 kids and 79 adult goats). The proportion of dry matter intake (DMI) was estimated for the following categories: (i) life forms: shrubs, dicot-herbaceous plants, vines and grasses; (ii) height of strata: low (<25 cm), medium (25−50 cm) and high (>50 cm of height); and (iii) bite size: small (<5 cm) and large (>6 cm). The proportions of materials consumed in each category were compared between kids and adult goats via Chi-squared tests. Kids consumed fewer plant species than adult goats, but total DMI was similar between kids and adult goats (52.5 ± 5.1 and 51 ± 5 g DM/Kg LW0.75; P > 0.05). The proportion of the DMI obtained from different life forms was also similar between kids and adult goats (35.3 % and 40.4 % from shrubs, 1.6 % and 2.1 % from dicot-herbaceous plants, 0.3 %, and 0.6 % from vines, and 62.8 % and 57.0 % from grasses, respectively). However, kids had less DMI from high strata than adult goats (14.6 % and 58.0 %) and more DMI from low strata (66.8 % and 24.5 %, P < 0.05), possibly due to their smaller height. Although inexperienced kids consumed fewer plant species than adult goats, the two groups of animals consumed similar proportions of shrubs and grass in their diets. In addition, kids consumed a smaller proportion of large bites than adult goats, most likely due to the smaller size of their mouths (P < 0.0001). Overall, the differences in feeding behavior between kids and adult goats seem related to zoometric differences, but the browsing experience of adult goats should also be considered.

Short-Term Dynamics of Vegetation Diversity and Aboveground Biomass of Picea abies (L.) H. Karst. Forests after Heavy Windstorm Disturbance

Although forest disturbances have become more frequent and severe due to ongoing climate change, our understanding of post-disturbance development of vegetation and tree–herb layer interactions remains limited. An extreme windstorm, which occurred on 19 November 2004, destroyed Picea abies (L.) H. Karst dominated forests in the High Tatra Mts. Here, we studied short-term changes in diversity, species composition, and aboveground biomass of trees and herb layer vegetation, including mutual relationships that elucidate tree–herb interactions during post-disturbance succession. Assessment of species composition and tree biomass measurements were performed at 50 sample plots (4 × 4 m) along two transects 12, 14, and 16 years after the forest destruction. Heights and stem base diameters of about 730 trees were measured and subsequently used for the calculation of aboveground tree biomass using species-specific allometric relationships. Aboveground biomass of herb layer was quantified at 300 subplots (20 × 20 cm) by destructive sampling. Species richness and spatial vegetation heterogeneity did not significantly change, and species composition exhibited small changes in accordance with expected successional trajectories. While aboveground tree biomass increased by about 190%, biomass of annual herb shoots decreased by about 68% and biomass of perennial herb shoots was stable during the studied period. The contribution of trees to total aboveground biomass increased from 83% to 97%. After 16 years of forest stands recovery, tree biomass represented approximately 13% of forest biomass before the disturbance. Herb layer biomass, particularly the biomass of annual herb shoots, was more closely related to tree cover than to tree biomass and its decline could be assigned to gradual tree growth. Our study provides clear evidence that short-term successional processes in post-disturbance vegetation are much better detectable by biomass than by diversity or compositional measures and emphasized the importance of light conditions in tree–herb competitive interactions.

Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices

Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha−1) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha−1 (mean biomass 10.6 Mg ha−1). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small.

Seasonal and inter-annual drivers of yellow fever transmission in South America.

In the last 20 years yellow fever (YF) has seen dramatic changes to its incidence and geographic extent, with the largest outbreaks in South America since 1940 occurring in the previously unaffected South-East Atlantic coast of Brazil in 2016–2019. While habitat fragmentation and land-cover have previously been implicated in zoonotic disease, their role in YF has not yet been examined. We examined the extent to which vegetation, land-cover, climate and host population predicted the numbers of months a location reported YF per year and by each month over the time-period. Two sets of models were assessed, one looking at interannual differences over the study period (2003–2016), and a seasonal model looking at intra-annual differences by month, averaging over the years of the study period. Each was fit using hierarchical negative-binomial regression in an exhaustive model fitting process. Within each set, the best performing models, as measured by the Akaike Information Criterion (AIC), were combined to create ensemble models to describe interannual and seasonal variation in YF. The models reproduced the spatiotemporal heterogeneities in YF transmission with coefficient of determination (R2) values of 0.43 (95% CI 0.41–0.45) for the interannual model and 0.66 (95% CI 0.64–0.67) for the seasonal model. For the interannual model, EVI, land-cover and vegetation heterogeneity were the primary contributors to the variance explained by the model, and for the seasonal model, EVI, day temperature and rainfall amplitude. Our models explain much of the spatiotemporal variation in YF in South America, both seasonally and across the period 2003–2016. Vegetation type (EVI), heterogeneity in vegetation (perhaps a proxy for habitat fragmentation) and land cover explain much of the trends in YF transmission seen. These findings may help understand the recent expansions of the YF endemic zone, as well as to the highly seasonal nature of YF.

The role of spatial heterogeneity in diversity of squamate reptiles in the Atlantic Forest highlands of southeastern Brazil.

Spatial heterogeneity of vegetation is considered to be one of the most important factors that can influence species richness in a region and, therefore, an important driver for species diversity. Here, we investigate how squamate diversity varies throughout a heterogeneous area in southeastern Atlantic Forest. Our sampling site corresponded to a mosaic of forest and open fields in Curucutu nucleus, Serra do Mar State Park, São Paulo State, Southeastern Brazil. Species diversity varied throughout the mosaic in terms of species composition and relative abundance, with some species being clearly associated with a particular physiognomy. However, a decrease is observed in species richness in forest, after the rarefaction method is applied, showing that when the abundance effect is excluded, only species composition differed between physiognomies. On the other hand, both space and environmental heterogeneity were associated with diversity and distribution of squamates. Our results emphasize the importance of environmental heterogeneity, as well as the influence of the spatial location of the sample units, in structuring squamate diversity in a highland assemblage from the Atlantic Forest.

Joint Estimation of Leaf Area Density and Leaf Angle Distribution Using TLS Point Cloud for Forest Stands

The foliage density $(u_l)$ and the leaf angle distribution (LAD) are important properties that impact radiation transmission, interception, absorption and, therefore, photosynthesis. Their estimation in a forested scene is a challenging task due to their interdependence in addition to the large variability in the forest structure and the heterogeneity of the vegetation. In this work, we propose to jointly estimate both of them using terrestrial laser scanner (TLS) point cloud for different forest stands. Our approach is based on direct/inverse radiative transfer modeling. The direct model was developed to simulate TLS shots within a vegetation scene having known foliage properties (i.e., $u_l$ and LAD) resulting in a 3-D point cloud of the observed scene. Then, the inverse model was developed to jointly estimate $u_l$ and LAD decomposing the 3-D point cloud into voxels. The problem turns out to a high-dimensional cost function to optimize. To do it, the shuffled complex evolution method has been adopted. Our approach is validated with results derived from several simulated homogeneous and heterogeneous vegetation canopies as well as from actual TLS point cloud acquired from Estonian Birch, Pine, and Spruce stands. Our findings revealed that our estimates were considerably close to the actual $u_l$ and leaf inclination distribution function (LIDF) values with ( $\text{Biais}_{u_l} \in [0.001 \; 0.006]$ , $\text{RMSE}_{u_l} \in [0.019 \; 0.045]$ , $\text{RMSE}_{\text{LIDF}} \in [ 0.019 \; 0.038]$ ) for homogeneous dataset and ( $\text{Biais}_{u_l} \in [0.001 \; 0.045]$ , $\text{RMSE}_{u_l} \in [0.023 \; 0.078]$ , $\text{RMSE}_{\text{LIDF}} \in [ 0.011 \; 0.018]$ ) for heterogeneous dataset with different tree crown geometries (i.e., conical and elliptical). In the actual case (Birch, Pine, and Spruce stands), our approach with the traditional and novel techniques, $\text{RMSE}_{\text{LAI}}$ are 0.526 and 0.105, respectively. The results outperform those of the baseline technique (i.e., assuming spherical LAD) with $\text{RMSE}_{\text{LAI}}=2.651$ .

Soil moisture retrieval over a site of intensive agricultural production using airborne radiometer data

This study investigates soil moisture retrievals using airborne passive microwave data at two different resolutions collected during the Soil Moisture Active Passive Validation Experiments in 2012 and 2016 (SMAPVEX12 and SMAPVEX16-MB). Based on the fine-resolution passive data (500 m), we integrate the surface roughness parameters which are traditionally used in the radar backscatter models into the passive emission models. To parameterize the effective roughness Hr in L-band Microwave Emission of the Biosphere (L-MEB) model, we analyze two different functions which include only surface Root Mean Square height (s), as well as both s and the autocorrelation length l (zs = s2/l). For each of the two roughness functions, the b vegetation parameters are optimized for canola, soybean and wheat. The transferability of the b parameters between 2012 and 2016 is also evaluated by comparing the L-MEB model simulated and the measured brightness temperature. Then, the calibrated L-MEB model is applied to the subpixels of the coarse-resolution passive data (1500 m) given the vegetation heterogeneity, to map the soil moisture over the SMAPVEX entire experimental site. The results indicated the Hr model with the zs parameter outperformed that with the s parameter. This suggests that the inclusion of the roughness autocorrelation length in the L-MEB model improved the accuracy of modeling the brightness temperature. The vegetation attenuation on the brightness temperature at V-polarization was stronger than that at H-polarization, due to the dominant vertical structure of the crop canopy. Since the airborne passive observations exhibited remarkable consistency between the 2012 and 2016 measurements, the b parameters obtained in 2012 can be transferred to the 2016. Based on the obtained Hr and b parameters, the soil moisture maps were retrieved using the calibrated L-MEB model applied to the sub-pixel of the coarse-resolution passive data, implying a Root Mean Square Errors (RMSEs) of 0.049–0.058 m3/m3 and correlation coefficients of 0.82–0.87. This paper suggests that the physical roughness zs in the radar domain can be coupled into the L-MEB model to refine the soil moisture retrievals from passive brightness temperature.

Comunidades de sírfidos (Diptera) asociadas a coberturas influenciadas por actividades antrópicas en los cerros orientales de Bogotá, Colombia

La diversidad taxonómica y funcional de los sírfidos los hace fundamentales en los ecosistemas. Además, su sensibilidad a la fragmentación del hábitat por factores antrópicos los hace buenos indicadores ecológicos de la conservación ecosistémica. Establecimos si las comunidades de sírfidos están relacionadas con coberturas vegetales en un gradiente de intervención antrópica en un área boscoso-montañosa de la ciudad de Bogotá. Las coberturas vegetales se identificaron con la metodología de coberturas de uso de la tierra y el sistema Corine Land Cover. Los insectos se recolectaron activamente durante los picos de máxima actividad diaria en un periodo de transición seco-húmedo. Las comunidades de sírfidos y su relación con las coberturas se evaluaron estimando el número efectivo de especies y un análisis de componentes principales (ACP). Se identificaron tres coberturas: Vegetación Secundaria Alta, Tejido Urbano Discontinuo y Bosque Ripario. Los 381 individuos recolectados pertenecen a 24 especies agrupadas en dos subfamilias. Las comunidades de sírfidos en la Vegetación Secundaria Alta y el Bosque Ripario presentaron números efectivos de especies superiores a los hallados en el Tejido Urbano Discontinuo. El ACP sugirió una estrecha asociación entre las especies Lejops mexicanus y Toxomerus watsoni con el Tejido Urbano Discontinuo y la Vegetación Secundaria Alta, mientras Palpada florea, Syrphus shorae, Orphnabaccha golbachi y Allograpta exotica lo son con el Bosque Ripario. La abundancia de sírfidos fue más alta en las coberturas con espacios abiertos y su diversidad fue influenciada por la heterogeneidad y antropización de las coberturas, patrón registrado por primera vez en el Neotrópico.

Environmental heterogeneity and population density affect the functional diversity of personality traits in small mammal populations.

Understanding factors affecting the functional diversity of ecological communities is an important goal for ecologists and conservationists. Previous work has largely been conducted at the community level; however, recent studies have highlighted the critical importance of considering intraspecific functional diversity (i.e. the functional diversity of phenotypic traits among conspecifics). Further, a major limitation of existing literature on this topic is the lack of empirical studies examining functional diversity of behavioural phenotypes-including animal personalities. This is a major shortcoming because personality traits can affect the fitness of individuals, and the composition of personalities in a population can have important ecological consequences. Our study aims to contribute to filling this knowledge gap by investigating factors affecting the functional diversity of personality traits in wild animal populations. Specifically, we predicted that the richness, divergence and evenness associated with personality traits would be impacted by key components of forest structure and would vary between contrasting forest types. To achieve our objective we conducted a fully replicated large-scale field experiment over a 4 year period using small mammal populations as a model system. We found that greater heterogeneity in the cover of shrubs, coarse woody debris and canopy cover was associated with a greater richness, lower divergence and lower evenness in personality traits. Greater population density was associated with greater functional richness and lower functional divergence and evenness of personality traits. To maintain a behaviourally diverse population and its associated functions, managers may promote heterogeneity in vegetation and increased population density, which we found to be the most important determinants driving functional diversity of personality traits.

Simulation-Based Evaluation of the Estimation Methods of Far-Red Solar-Induced Chlorophyll Fluorescence Escape Probability in Discontinuous Forest Canopies

The escape probability of Solar-induced chlorophyll fluorescence (SIF) can be remotely estimated using reflectance measurements based on spectral invariants theory. This can then be used to correct the effects of canopy structure on canopy-leaving SIF. However, the feasibility of these estimation methods is untested in heterogeneous vegetation such as the discontinuous forest canopy layer under evaluation here. In this study, the Discrete Anisotropic Radiative Transfer (DART) model is used to simulate canopy-leaving SIF, canopy total emitted SIF, canopy interceptance, and the fraction of absorbed photosynthetically active radiation (fAPAR) in order to evaluate the estimation methods of SIF escape probability in discontinuous forest canopies. Our simulation results show that the normalized difference vegetation index (NDVI) can be used to partly eliminate the effects of background reflectance on the estimation of SIF escape probability in most cases, but fails to produce accurate estimations if the background is partly or totally covered by vegetation. We also found that SIF escape probabilities estimated at a high solar zenith angle have better estimation accuracy than those estimated at a lower solar zenith angle. Our results show that additional errors will be introduced to the estimation of SIF escape probability with the use of satellite products, especially when the product of leaf area index (LAI) and clumping index (CI) was underestimated. In other results, fAPAR has comparable estimation accuracy of SIF escape probability when compared to canopy interceptance. Additionally, fAPAR for the entire canopy has better estimation accuracy of SIF escape probability than fPAR for leaf only in sparse forest canopies. These results help us to better understand the current estimation results of SIF escape probability based on spectral invariants theory, and to improve its estimation accuracy in discontinuous forest canopies.