Vegetation Structure Properties Research Articles

Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands

Semi-natural grasslands with grazing management are characterized by high fine-scale species richness and have a high conservation value. The fact that fine-scale surveys of grassland plant communities are time-consuming may limit the spatial extent of ground-based diversity surveys. Remote sensing tools have the potential to support field-based sampling and, if remote sensing data are able to identify grassland sites that are likely to support relatively higher or lower levels of species diversity, then field sampling efforts could be directed towards sites that are of potential conservation interest. In the present study, we examined whether aerial hyperspectral (414–2501 nm) remote sensing can be used to predict fine-scale plant species diversity (characterized as species richness and Simpson’s diversity) in dry grazed grasslands. Vascular plant species were recorded within 104 (4 m × 4 m) plots on the island of Öland (Sweden) and each plot was characterized by a 245-waveband hyperspectral data set. We used two different modeling approaches to evaluate the ability of the airborne spectral measurements to predict within-plot species diversity: (1) a spectral response approach, based on reflectance information from (i) all wavebands, and (ii) a subset of wavebands, analyzed with a partial least squares regression model, and (2) a spectral heterogeneity approach, based on the mean distance to the spectral centroid in an ordinary least squares regression model. Species diversity was successfully predicted by the spectral response approach (with an error of ca. 20%) but not by the spectral heterogeneity approach. When using the spectral response approach, iterative selection of important wavebands for the prediction of the diversity measures simplified the model but did not improve its predictive quality (prediction error). Wavebands sensitive to plant pigment content (400–700 nm) and to vegetation structural properties, such as above-ground biomass (700–1300 nm), were identified as being the most important predictors of plant species diversity. We conclude that hyperspectral remote sensing technology is able to identify fine-scale variation in grassland diversity and has a potential use as a tool in surveys of grassland plant diversity.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Potential impacts of aridity on structural and functional status of a southern Mediterranean Stipa tenacissima steppe

Over the last decades, there has been a growing interest in evaluating the predicted potential impacts of future climatic conditions on ecosystem functioning. Ecological indicators developed to assess ecosystem functioning strongly rely on soil and vegetation variables.In the current investigation, we evaluated the structural and functional status of a southern Mediterranean Stipa tenacissima steppe along an increasing aridity gradient. We estimated also the predicted effects of aridity on their functioning.The wide variation of LFA indices, vegetation structural attributes and soil properties among the different study sites revealed structural and functional heterogeneity in S. tenacissima steppes with the increasing aridity. Correlations obtained between LFA indices and most patch attributes showed the importance of vegetation structural attributes on the functioning of S. tenacissima steppes. On the other hand, correlations found between LFA indices and most measured soil variables verified the significance of LFA indices in monitoring soil functioning in southern Mediterranean S. tenacissima steppes.The strong negative relationships observed between aridity and stability, nutrient cycling indices demonstrated that increasing aridity can reinforce erosive processes and deteriorate nutrient cycling (i.e. aridity decreased soil carbon, nitrogen and enzymatic activities).Similarly, aridity was negatively related to vegetation structural attributes including patch cover and landscape organization index. This finding suggests that any increase in aridity can promote the loss of perennial vegetation cover.The current investigation highlighted that predicted increasing aridity will dramatically affect the functioning of southern Mediterranean S. tenacissima steppes, especially in the more arid areas.

The Uncertainty of Plot-Scale Forest Height Estimates from Complementary Spaceborne Observations in the Taiga-Tundra Ecotone

Satellite-based estimates of vegetation structure capture broad-scale vegetation characteristics as well as differences in vegetation structure at plot-scales. Active remote sensing from laser altimetry and radar systems is regularly used to measure vegetation height and infer vegetation structural attributes, however, the current uncertainty of their spaceborne measurements is likely to mask actual plot-scale differences in vertical structures in sparse forests. In the taiga (boreal forest)—tundra ecotone (TTE) the accumulated effect of subtle plot-scale differences in vegetation height across broad-scales may be significant. This paper examines the uncertainty of plot-scale forest canopy height measurements in northern Siberia Larix stands by combining complementary canopy surface elevations derived from satellite photogrammetry and ground elevations derived from the Geosciences Laser Altimeter System (GLAS) from the ICESat-1 satellite. With a linear model, spaceborne-derived canopy height measurements at the plot-scale predicted TTE stand height ~5 m–~10 m tall (R2 = 0.55, bootstrapped 95% confidence interval of R2 = 0.36–0.74) with an uncertainty ranging from ±0.86 m–1.37 m. A larger sample may mitigate the broad uncertainty of the model fit, however, the methodology provides a means for capturing plot-scale canopy height and its uncertainty from spaceborne data at GLAS footprints in sparse TTE forests and may serve as a basis for scaling up plot-level TTE vegetation height measurements to forest patches.

Relationships between Soil and Vegetation Structural Properties of Secondary Forest Regenerating in Degraded Rubber Plantation in the Niger Delta Area of Nigeria

The effects of soil on vegetation structural attributes (tree density, tree height, tree diameter, basal area and estimated aboveground biomass) of a secondary forest following the abandonment of a degraded rubber plantation in Orogun area of Delta state Nigeria was studied using the multiple linear regression model. Four secondary forests of different age categories (1-year, 5-year, 10-year old secondary forests and a mature secondary forest of about 80 years old) were studied. Vegetation parameters were measured by quadrat method. Forty quadrats (30m x 30m), ten in each secondary forest categories were delineated for soil sampling and for the measurement of vegetation structural properties. Twenty composite soil samples were collected in each secondary forest category and analyzed for organic matter, pH, available phosphorus, total porosity, ECEC (effective cation exchange capacity) and water holding capacity. Vegetation structural properties for each of the quadrats were measured using appropriate field measurement techniques. Multiple linear regression was used to investigate the relationship between the vegetation structural properties and soil properties. The result of multiple linear regression showed that soil organic matter, total porosity, water holding capacity, available phosphorus and ECEC were the most outstanding soil factors influencing the regenerative capacity of the vegetation structural properties in secondary forests. Relationship between Soil and vegetation Structural Properties of Secondary Forest regenerating... Key words : Tree height, Tree density, Basal area, multiple regression, ECEC, Water holding capacity.

Modeling canopy height in a savanna ecosystem using spaceborne lidar waveforms

Although savanna ecosystems cover about 20% of the terrestrial land surface and can have productivity equal to some closed forests, their role in the global carbon cycle is poorly understood. As a result, these ecosystems are globally more important than generally appreciated in the earth observation and modeling communities. Remote sensing has been proposed as an efficient tool in assessing the physical structure of an ecosystem which in turn is closely related to its ecological functionality such as carbon storage. Studies using Light Detection and Ranging (lidar) have demonstrated the technology's ability to measure canopy height and the strong relationship between canopy height and structural attributes such as aboveground biomass, but most of this work has focused on closed canopy forests. This study explored the applicability of spaceborne lidar to estimate canopy height as a pre-requisite for aboveground biomass and carbon storage assessment in savannas. The research used a case study of the Oak Savannas of Santa Clara in California, USA. Discrete return airborne lidar data was used to extract height metrics in plots coincident with waveform data from the Ice Cloud and land Elevation Satellite (ICESat)'s Geoscience Laser Altimeter System (GLAS). Detailed analysis of GLAS waveforms was followed by non-parametric regression modeling to estimate maximum canopy height and 80th and 90th percentile vegetation heights. Existing methods were adapted with the inclusion of NDVI (as a canopy cover proxy) and interaction terms to increase utility in savanna ecosystems. Our main findings were that merely adopting the methods derived for forests would not produce adequate results. Maximum canopy height was estimated with better accuracy compared to percentile height metrics. The inclusion of NDVI and interaction terms improved maximum canopy height modeling much more than it did for the 80th and 90th percentile height modeling. Taller stands on flat terrain had the best results while shorter stands on steep terrain had the worst. Our work has demonstrated the capability of waveform lidar to assess vegetation structural attributes in savannas. The challenge in canopy height modeling using this technique in such ecosystems not only is limited to terrain slope but also includes the interacting influence of low canopy cover and short height. As such, we need special models for savanna areas in an effort to do global assessments of terrestrial vegetation structure using lidar. For future studies we recommend a closer look at the non-significant influence of canopy cover on the percentile canopy height models especially its implication on the subsequent biomass modeling.

Retrieval of Savanna Vegetation Canopy Height from ICESat-GLAS Spaceborne LiDAR With Terrain Correction

Light detection and ranging (LiDAR) remote sensing enables accurate estimation and monitoring of vegetation structural properties. Airborne and spaceborne LiDAR is known to provide reliable information on terrain elevation and forest canopy height over closed forests. However, it has rarely been used to characterize savannas, which have a complex structure of trees coexisting with grasses. This letter presents the first validation of spaceborne Ice Cloud and land Elevation Satellite Geoscience Laser Altimeter System (GLAS) full-waveform data to retrieve savanna vegetation canopy height that uses field data specifically collected within the GLAS footprints. Two methods were explored in the Kruger National Park, South Africa: one based on the Level 2 Global Land Surface Altimetry Data product and the other using Level 1A Global Altimetry Data (GLA01) with terrain correction. Both methods use Gaussian decomposition of the full waveform. Airborne LiDAR (AL) was also used to quantify terrain variability (slope) and canopy height within the GLAS footprints. The canopy height retrievals were validated with field observations in 23 GLAS footprints and show that the direct method works well over flat areas (Pearson correlation coefficient r = 0.70, , and n = 8 for GLA01) and moderate slopes (r = 0.68, , and n = 9 for GLA01). Over steep slopes in the footprint, however, the retrievals showed no significant correlation and required a statistical correction method to remove the effect of terrain variability on the waveform extent. This method improved the estimation accuracy of maximum vegetation height with correlations (R2 = 0.93, , and n = 6 using the terrain index (g) generated from AL data and R2 = 0.91,, and n = 6 using the GLAS returned waveform width parameter). The results suggest that GLAS can provide savanna canopy height estimations in complex tree/grass plant communities.

The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs

Abstract. Terrestrial biosphere models typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical plant functional types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) as a new approach to terrestrial biosphere modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly generated plant growth strategies, each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a strategy is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other strategies. The biogeochemical fluxes and land surface properties of the individual strategies are aggregated to the grid-cell scale using a mass-based weighting scheme. We evaluate the simulated global biogeochemical patterns against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favourably with other state-of-the-art global vegetation models. We also evaluate the simulated patterns of functional diversity and the sensitivity of the JeDi-DGVM modelling approach to the number of sampled strategies. Altogether, the results demonstrate the parsimonious and flexible nature of a functional trade-off approach to global vegetation modelling, i.e. it can provide more types of testable outputs than standard PFT-based approaches and with fewer inputs. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.

Timberline meadows along a 1000-km transect in NW North America: species diversity and community patterns

Question The mountains of NW North America are home to natural meadows that cover large areas at the timberline. The vegetation of these meadows has been the topic of few local studies, and little is known of species composition turnover across mountain ranges and along the latitudinal gradient. We sampled and analyzed community composition along a 1000-km gradient to answer the following questions: (1) what are the main community types in timberline meadows; (2) what are the most important abiotic gradients underlying their composition; and (3) how is species diversity related to environmental factors and how does it change along the latitudinal gradient? Location SE and central British Columbia (Canada), NW Montana (USA). Methods We recorded data on cover and presence/absence of vascular plant, bryophyte and lichen species, as well as structure and environmental properties in 4 m × 4 m plots (n = 112). Using the OptimClass approach, we classified plots into distinct community types. We used NMDS and multiple regressions to analyse the relationship between composition, species richness and environmental and geographic gradients. Results Despite drawing from a large geographic area, our classification revealed only four meadow communities. Mesic meadows were the most frequent and had a pronounced species turnover along latitude, resulting in two distinct community types. In addition, a three-dimensional ordination showed that vegetation structural properties, macroclimate and geographic predictors were important underlying gradients for species composition. Vascular species richness increased with soil pH, and exhibited a quadratic relationship with litter cover and latitude. Furthermore, in the latter case, it increased towards the southern and northern ends of our gradient. Conclusions Detection of only four meadow communities along the 1000-km sampling gradient suggests a relatively recently established flora and a lack of regional differentiation consistent with the low level of endemism in the region. Higher vascular species diversity at the northern and southern edges of our gradient may reflect the geographic proximity to areas unglaciated during the Pleistocene, and suggests that areas farthest from the unglaciated edge may be experiencing colonization debt.

Characterizing vegetation structural and topographic characteristics sampled by eddy covariance within two mature aspen stands using lidar and a flux footprint model: Scaling to MODIS

[1] In this study, a Boolean classification was applied using novel methods to 3-D vegetation structural and topographic attributes found within flux footprint source/sink areas measured by eddy covariance instrumentation. The purpose was to determine if the spatial frequency of 3-D attributes, such as canopy height, effective leaf area index, etc., found within 1 km resolution Moderate Resolution Imaging Spectroradiometer (MODIS) pixels were significantly different from or similar to attributes sampled by flux footprints originating from prevailing wind directions. A Kolmogorov-Smirnov test was used for the first time to apply confidence limits to individual MODIS pixels based on (1) the spatial distribution of cumulative frequencies of attributes representative of those sampled by eddy covariance and (2) temporal representation of MODIS pixels related to area sampling frequency by eddy covariance based on wind direction. Structural and topographic attributes at homogeneous Southern Old Aspen and heterogeneous Upland Aspen sites are representative of 56% and 69% of a 1 km radius area surrounding the tower and 21% and 47% of a 4 × 4 km area. Attributes found within the MODIS “tower” pixel compare well with attributes most frequently sampled by eddy covariance instruments at both sites. By classifying pixels using the Boolean approach, correspondence between MODIS pixels and eddy covariance estimates of gross primary production (GPP) explain up to 13% more variance than using pixels proximal to the tower. This study, therefore, provides a method for choosing MODIS pixels that have similar attributes to those found within footprints most frequently sampled by eddy covariance.

Contemporary fire regimes in a fragmented and an unfragmented landscape: implications for vegetation structure and persistence of the fire-sensitive malleefowl

Habitat fragmentation alters fire regimes by changing the spatial and temporal context in which fire operates, potentially altering ecosystem state and threatening taxa. In the fragmented wheatbelt of Western Australia, spatial patterns of contemporary fire and their effects on biodiversity conservation are poorly understood. We addressed this by: (1) determining if fire regimes differed between vegetation remnants of differing sizes and uncleared vegetation, using analysis of satellite imagery; (2) determining vegetation structural responses to time since fire in three habitats: mallee-shrub, Acacia shrublands and mallee-heath; and (3) exploring the consequences of these differences, using the fire-sensitive malleefowl (Leipoa ocellata) as a case study. Fire was infrequent in small remnants, more frequent in large remnants, and most frequent in uncleared areas. Key vegetation structural attributes for malleefowl, such as canopy and litter cover, increased beyond 45 years post-fire in mallee-shrub, reached a plateau in mallee-heath after 30–40 years, and declined in Acacia shrublands after 25–40 years. Senescence in long-unburnt vegetation, combined with rare contemporary fires, suggest progressive decline in habitat quality of Acacia shrublands for malleefowl in the wheatbelt. In the adjacent, continuously vegetated landscapes, more frequent (and extensive) fires in structurally developing mallee-shrub communities are of concern for malleefowl conservation.

Above ground woody community attributes, biomass and carbon stocks along a rainfall gradient in the savannas of the central lowveld, South Africa

Enumeration of carbon stocks at benchmark sites is a necessary activity in assessing the potential carbon sequestration and possible generation of credits through restoration of intensively impacted sites. However, there is a lack of empirical studies throughout much of the savannas of sub-Saharan Africa, including South Africa. We report an estimation of species specific and site biomass and carbon stocks, and general vegetation structural attributes from three protected areas along a rainfall gradient in the central lowveld, South Africa. Estimates of biomass and carbon stocks were effected through destructive sampling to establish locally derived allometric equations. There was a gradient of increasing woody density, height of the canopy, number of species, density of regenerative stems and a greater proportion of stems in small size classes from the arid locality to the mesic locality, with the semi-arid locality being intermediate. The proportion of spinescent species decreased with increasing rainfall. The mesic locality was significantly more woody than either the arid or semi-arid sites, having double the biomass, four times the density and 40% higher basal area. Above ground carbon pools were also higher; carbon stocks were approximately 9 t/ha for the arid and semi-arid sites and 18 t/ha for the mesic site.

Modeling the hemispherical scanning, below-canopy lidar and vegetation structure characteristics with a geometric-optical and radiative-transfer model

This study applied a hybrid canopy geometric optical and radiative transfer (GORT) model to study the vegetation structure characteristics and lidar signals from a terrestrial below-canopy lidar instrument, Echidna Validation Instrument (EVI), developed by CSIRO Australia. Off-nadir scans from the below-canopy lidar show strong laser energy returns from both leaves and tree trunks. The GORT model was modified to include the effect of both leaves and trunks on below-canopy lidar energy returns by treating the trunks as simple uniform cylinders extending to the middle of each tree crown. GORT was also extended to allow multiple canopy layers by convolution of the canopy gap probability profiles for individual canopy layers. The extended leaf-and-trunk GORT model was evaluated by comparing the modeled and EVI-derived gap probability profiles in a single-layer pine plantation and a two-layer eucalypt forest at the Tumbarumba flux tower site in southeastern New South Wales, Australia. Results show that the new leaf-and-trunk GORT model improves estimates of EVI-derived gap probability profiles. This study demonstrates the potential use of terrestrial upward-scanning hemispherical lidar to retrieve forest canopy structural information. A future goal is to link these terrestrial hemispherical lidar measurements to downward-looking airborne lidar, such as the Laser Vegetation Imaging Sensor (LVIS), and spaceborne lidar, such as the Geoscience Laser Altimeter System (GLAS) on ICESat, through a common model to provide large-area mapping of vegetation structural properties and biomass.

The use of airborne lidar to assess avian species diversity, density, and occurrence in a pine/aspen forest

Vegetation structure is an important factor that influences wildlife-habitat selection, reproduction, and survival. However, field-based measurements of vegetation structure can be time consuming, costly, and difficult to undertake in areas that are remote and/or contain rough terrain. Light detection and ranging (lidar) is an active remote sensing technology that can quantify three-dimensional vegetation structure over large areas and thus holds promise for examining wildlife-habitat relationships. We used discrete-return airborne lidar data acquired over the Black Hills Experimental Forest in South Dakota, USA in combination with field-collected vegetation and bird data to assess the utility of lidar data in quantifying vegetation structural characteristics that relate to avian diversity, density, and occurrence. Indices of foliage height diversity calculated from lidar data were positively and significantly correlated with indices of bird species diversity, with the highest correlations observed when foliage height diversity categories contained proportionally more foliage layers near the forest floor (<5 m). In addition, lidar-derived indices of vegetation volume were significantly correlated with bird density. Using lidar-derived vegetation height data in combination with multispectral IKONOS data, we delineated five general habitat types within the study area according to the presence of prominent vegetation layers at lower levels of the forest and predominant tree type (deciduous or conifer). Habitat type delineations were tested by examining the occurrence and relative density of two bird species common to the study area that prefer lower level vegetation for foraging and nesting. Dark-eyed Juncos were significantly associated with the 0.5–2.0 m high vegetation layer in pine-dominated stands, and Warbling Vireos were significantly associated with this same layer in aspen-dominated stands. These results demonstrate that discrete-return lidar can be an effective tool to remotely quantify vegetation structural attributes important to birds, and may be enhanced when used in combination with spectral data.

Plant Spatial Pattern Predicts Hillslope Runoff and Erosion in a Semiarid Mediterranean Landscape

The importance of the spatial pattern of vegetation for hydrological behavior in semiarid environments is widely acknowledged. However, there is little empirical work testing the hypothetical covariation between vegetation spatial structure and hillslope water and sediment fluxes. We evaluated the relationships between vegetation structural attributes (spatial pattern, functional diversity), soil surface properties (crust, stone, plant, and ground cover, and particle size distribution) and hillslope hydrologic functioning in a semiarid Mediterranean landscape; in particular, we tested whether decreasing patch density or coarsening plant spatial pattern would increase runoff and sediment yield at the hillslope scale. Runoff and sediment yield were measured over a 45-month period on nine 8 × 2-m plots that varied in vegetation type and spatial pattern. We grouped vegetation into functional types and derived plant spatial pattern attributes from field plot maps processed through a GIS system. We found that there was an inverse relationship between patch density and runoff, and that both runoff and sediment yields increased as the spatial pattern of vegetation coarsened. Vegetation pattern attributes and plant functional diversity were better related to runoff and sediment yield than soil surface properties. However, a significant relationship was found between physical crust cover and plant spatial pattern. Our results present empirical evidence for the direct relationship between the hydrologic functioning of semiarid lands and both the spatial pattern and the functional diversity of perennial vegetation, and suggest that plant spatial pattern, physical crust cover, and functional diversity may be linked through feedback mechanisms.

Using multi‐directional high‐resolution imagery from POLDER sensor to retrieve leaf area index

Multi‐directional satellite optical imagery collected at high spatial resolution potentially allows improving the accuracy of biophysical variable retrieval. The improvements result from the inclusion of the directional anisotropy of the target, which provides additional information related to vegetation structural properties. The research presented here analyses airborne imagery and ground reference data in order to quantify the accuracy of the retrieval methods for LAI (leaf area index). Both variables are estimated through processing of airborne POLDER (POLarization and Directionality of Earth Reflectances) sensor images from an agricultural area. In a first step, the BRDF (Bi‐directional Reflectance Distribution Function) of the surface is estimated using a simple parametric model, whose parameters where derived from fitting POLDER BRF (Bi‐directional Reflectance Factor) measurements. LAI estimation was performed using two different approaches, both based on an artificial neural network designed to invert a 1D soil‐vegetation radiative transfer model. The difference between the two methods is that one of them uses only the isotropic component of the BRDF parametric model and the other the full BRDF information, i.e. adding the anisotropic components. The algorithm using isotropic information shows a clear improvement when compared to semi‐empirical approaches. Root mean square error between estimated and ground measured LAI values is 0.87. However, the method using the full BRDF information yielded poorer estimates, pointing out the difficulty of fully exploiting the multi-directional information. The performance decrease is partially explained by the incoherence between real and modelled BRDF measurements.

Fauna-habitat relationships: a basis for identifying key stand structural attributes in temperate Australian eucalypt forests and woodlands

We review a representative sample of the literature concerning fauna-habitat relationships in temperate Australian eucalypt forests and woodlands as a basis for identifying some key stand structural attributes in these ecosystems. Our review identifies 56 studies in south-east and south-west Australia in which the presence or abundance of different fauna were significantly associated with vegetation structural attributes at the scale of a stand. The majority of these studies concern bird, arboreal mammal, and ground mammal habitat requirements, with relatively few studies addressing the habitat requirements of reptiles, invertebrates, bats or amphibians. We identify 34 key structural attributes from these 56 studies, by grouping similar attributes, and then representing each group with a single generic attribute. Relatively few of these attributes are incorporated into indices used to quantify fauna habitat. We highlight the need for a quantitative method for selecting which key attributes should form the basis for an index of structural complexity or other surrogate measure of faunal diversity.

Vegetation height estimation from Shuttle Radar Topography Mission and National Elevation Datasets

A study was conducted to determine the feasibility of obtaining estimates of vegetation canopy height from digital elevation data collected during the 2000 Shuttle Radar Topography Mission (SRTM). The SRTM sensor mapped 80% of the Earth's land mass with a C-band Interferometric Synthetic Aperture Radar (InSAR) instrument, producing the most complete digital surface map of Earth. Due to the relatively short wavelength (5.6 cm) of the SRTM instrument, the majority of incoming electromagnetic energy is reflected by scatterers located within the vegetation canopy at heights well above the “bald-Earth” surface. Interferometric SAR theory provides a basis for properly identifying and accounting for the dependence of this scattering phase center height on both instrument and target characteristics, including relative and absolute vertical error and vegetation structural attributes. An investigation to quantify the magnitude of the vertical error component was conducted using SRTM data from two vegetation-free areas in Iowa and North Dakota, revealing absolute errors of −4.0 and −1.1 m, respectively. It was also shown that the relative vertical error due to phase noise can be reduced significantly through sample averaging. The relative error range for the Iowa site was reduced from 13 to 4 m and for the North Dakota site from 7 to 3 m after averaging of 50 samples. Following error reduction, it was demonstrated that the SRTM elevation data can be successfully correlated via linear regression models with ground-measured canopy heights acquired during the general mission timeframe from test sites located in Georgia and California. Prior to outlier removal and phase noise reduction, initial adjusted r 2 values for the Georgia and California sites were 0.15 and 0.20, respectively. Following outlier analysis and averaging of at least 20 SRTM pixels per observation, adjusted r 2 values for the Georgia and California sites improved to 0.79 (rmse=1.1 m) and 0.75 (rmse=4.5 m), respectively. An independent validation of a novel bin-based modeling strategy designed for reducing phase noise in sample plot data confirmed both the robustness of the California model (adjusted r 2=0.74) as well as the capacity of the binning strategy to produce stable models suitable for inversion (validated rmse=4.1 m). The results suggest that a minimum mapping unit of approximately 1.8 ha is appropriate for SRTM-based vegetation canopy height mapping.

Rain forest invasion of eucalypt‐dominated woodland savanna, Iron Range, north‐eastern Australia: I. Successional processes

AbstractAim To explore successional processes associated with rain forest expansion in Eucalyptus‐dominated woodland savanna vegetation in north‐eastern Australia.Location Iron Range National Park and environs, northeast Queensland, Australia. This remote region supports probably the largest extent of lowland (&lt; 300 m) rainforest remnant in Australia. Rainfall (c. 1700 mm p.a.) occurs mostly between November and June, with some rain typically occurring even in the driest months July–October.Methods (1) Sampling of rain forest seedling distributions, and other vegetation structural attributes, in fifteen 10 × 10 m quadrats distributed equi‐distantly between mature rain forest margins (range: 70–840 m), at each of 10 sites which were open‐canopied vegetation in 1943. (2) Assessment of relationships between rain forest seedling densities and structural characteristics, including distance‐to‐rain forest‐margin, canopy height, stem density. (3) Assessment of lifeform and dispersal spectra for defined vegetation structural types.Results Rates of rain forest invasion were found to be substrate‐mediated. Transects established on hematite schist, diorite, riverine alluvium, and granite developed closed canopies (termed phase III sites) by 1991. The remainder (four transects on poorly drained colluvial/alluvial sediments; one on dune sands) continued to occur either as grassy woodland (phase I), or with developing rain forest understoreys (phase II). Rain forest seedlings were observed at maximum sampled distances from mature rain forest margins at all sites. Lifeform and dispersal spectra data illustrated that: (1) the proportions of woodland trees, shrubs and graminoids declined with successional phase, with concomitant increases in rain forest primary trees and all other lifeform categories save rain forest trees; (2) the proportions of major dispersal syndromes did not vary between successional phases, neither for rain forest nor woodland taxa.Main conclusions Rain forest seedling distribution data for phases I and II sites illustrate three successional processes: margin extension – seedling density significantly negatively correlated with distance from mature rain forest margins at two sites; nucleation – seedling densities significantly positively correlated with tall trees at two sites; and irruption – seedling densities at two sites neither correlated with distance from mature rain forest margins, nor with measured vegetation structural features. The observation of irruptive rain forest regeneration at these sites, combined with decadal‐scale rain forest canopy development at the five remaining sites, illustrates that under conditions conducive to growth (moisture, substrate), low fire disturbance, and maintenance of diverse dispersal processes (high frugivore richness), rain forest can rapidly invade regional landscapes.

Explaining bird species composition and richness in eucalypt‐dominated remnants in subhumid Tasmania

AbstractAim To determine the factors influencing the distribution of birds in remnants in a fragmented agricultural landscape.Location Forty‐seven eucalypt remnants and six sites in continuous forest in the subhumid Midlands region of Tasmania, Australia.Methods Sites were censused over a two‐year period, and environmental data were collected for remnants. The avifauna of the sites was classified and ordinated. The abundances of bird species, and bird species composition, richness, abundance and diversity were related to environmental variables, using simple correlation and modelling.Results There were two distinct groups of sample sites, which sharply differed in species composition, richness, diversity and bird abundance, separated on the presence/absence of noisy miner (Manorina melanocephala Latham) colonies, remnant size, vegetation structural attributes and variables that reflected disturbance history. The approximate remnant size threshold for the change from one group to another was 20–30 ha. Remnant species richness and diversity were most strongly explained by remnant area and noisy miner abundance, with contributions from structural and isolation attributes in the second case. Segment richness was explained by precipitation, logging history and noisy miner abundance. Bird abundance was positively related to precipitation and negatively related to tree dieback. The 28 individual bird species models were highly individualistic, with vegetation structural variables, noisy miner abundance, climatic variables, variables related to isolation, area, variables related to floristics, disturbance variables, the nature of the matrix and remnant shape all being components in declining order of incidence. Age of the remnant did not relate to any of the dependent variables.Main conclusions Degraded and small remnants may have become more distinct in their avifaunal characteristics than might otherwise be the case, as a result of the establishment of colonies of an aggressive native bird, the noisy miner. The area, isolation and shape of remnants directly relate to the abundance of relatively few species, compared to vegetation attributes, climate and the abundance of the noisy miner. The nature of the matrix is important in the response of some species to fragmentation.