Lee A. Vierling

Putting the "landscape" in landscape genetics.

Landscape genetics has emerged as a new research area that integrates population genetics, landscape ecology and spatial statistics. Researchers in this field can combine the high resolution of genetic markers with spatial data and a variety of statistical methods to evaluate the role that landscape variables play in shaping genetic diversity and population structure. While interest in this research area is growing rapidly, our ability to fully utilize landscape data, test explicit hypotheses and truly integrate these diverse disciplines has lagged behind. Part of the current challenge in the development of the field of landscape genetics is bridging the communication and knowledge gap between these highly specific and technical disciplines. The goal of this review is to help bridge this gap by exposing geneticists to terminology, sampling methods and analysis techniques widely used in landscape ecology and spatial statistics but rarely addressed in the genetics literature. We offer a definition for the term ‘landscape genetics’, provide an overview of the landscape genetics literature, give guidelines for appropriate sampling design and useful analysis techniques, and discuss future directions in the field. We hope, this review will stimulate increased dialog and enhance interdisciplinary collaborations advancing this exciting new field.

Lidar: shedding new light on habitat characterization and modeling

Ecologists need data on animal–habitat associations in terrestrial and aquatic environments to design and implement effective conservation strategies. Habitat characteristics used in models typically incorporate (1) field data of limited spatial extent and/or (2) remote sensing data that do not characterize the vertical habitat structure. Remote sensing tools that directly characterize three-dimensional (3-D) habitat structure and that provide data relevant to organism–habitat interactions across a hierarchy of scales promise to improve our understanding of animal–habitat relationships. Laser altimetry, commonly called light detection and ranging (lidar), is a source of geospatial data that can provide fine-grained information about the 3-D structure of ecosystems across broad spatial extents. In this review, we present a brief overview of lidar technology, discuss recent applications of lidar data in investigations of animal–habitat relationships, and propose future applications of this technology to issues of broad species-management and conservation interest.

Isoprene emission estimates and uncertainties for the central African EXPRESSO study domain

A global three-dimensional (3-D) chemistry and transport model was used to demonstrate that a factor of 2 decrease in isoprene and monoterpene emissions results in significant (10–30%) changes in predicted concentration distributions of compounds such as OH, MPAN, NOx, H2O2, O3, and CO. Isoprene and monoterpenes were predicted to have a particularly strong impact on tropical regions, including central Africa. The 1996 Experiment for Regional Sources and Sinks of Oxidants (EXPRESSO) study included a number of experiments that improved our ability to predict isoprene and monoterpene emissions from central Africa. The results of these experiments have been incorporated into an isoprene emission model that predicts hourly emissions on a spatial scale of about 1 km2. The model uses procedures that are suitable for estimating global emissions but uses regional measurements to accurately parameterize the model. Comparisons with above-canopy aircraft and tower flux measurements demonstrate that the model can estimate emissions within a factor of 2 for regions where ground measurements of model inputs are available. The annual central African isoprene emission predicted by our revised model (35 Tg C) is only 14% less than that predicted by our earlier model, but there are considerable differences in estimates of individual model variables. The models differ by more than a factor of 5 for specific times and locations, which indicates that there are large uncertainties in emission estimates for at least some locations and seasons. The good agreement obtained for the EXPRESSO study field sites, however, suggests that the model can predict reasonable estimates if representative field measurements are used to parameterize the model.

Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data

We describe and evaluate a new analysis technique, spatial wavelet analysis (SWA), to automatically estimate the location, height, and crown diameter of individual trees within mixed conifer open canopy stands from light detection and ranging (lidar) data. Two-dimensional Mexican hat wavelets, over a range of likely tree crown diameters, were convolved with lidar canopy height models. Identification of local maxima within the resultant wavelet transformation image then allowed determination of the location, height, and crown diameters of individual trees. In this analysis, which focused solely on individual trees within open canopy forests, 30 trees incorporating seven dominant North American tree species were assessed. Two-dimensional (2D) wavelet-derived estimates were well correlated with field measures of tree height (r = 0.97) and crown diameter (r = 0.86). The 2D wavelet-derived estimates compared favorably with estimates derived using an established method that uses variable window filters (VWF) to estimate the same variables but relies on a priori knowledge of the tree height – crown diameter relationship. The 2D spatial wavelet analysis presented herein could potentially allow automated, large-scale, remote estimation of timber board feet, foliar biomass, canopy volume, and aboveground carbon, although further research testing the limitations of the method in a variety of forest types with increasing canopy closures is warranted.

Isoprene fluxes measured by enclosure, relaxed eddy accumulation, surface layer gradient, mixed layer gradient, and mixed layer mass balance techniques

Isoprene fluxes were estimated using eight different measurement techniques at a forested site near Oak Ridge, Tennessee, during July and August 1992. Fluxes from individual leaves and entire branches were estimated with four enclosure systems, including one system that controls leaf temperature and light. Variations in isoprene emission with changes in light, temperature, and canopy depth were investigated with leaf enclosure measurements. Representative emission rates for the dominant vegetation in the region were determined with branch enclosure measurements. Species from six tree genera had negligible isoprene emissions, while significant emissions were observed for Quercus, Liquidambar, and Nyssa species. Above-canopy isoprene fluxes were estimated with surface layer gradients and relaxed eddy accumulation measurements from a 44-m tower. Midday net emission fluxes from the canopy were typically 3 to 5 mg C m−2 h−1, although net isoprene deposition fluxes of −0.2 to −2 mg C m−2 h−1 were occasionally observed in early morning and late afternoon. Above-canopy CO2 fluxes estimated by eddy correlation using either an open path sensor or a closed path sensor agreed within ±5%. Relaxed eddy accumulation estimates of CO2 fluxes were within 15% of the eddy correlation estimates. Daytime isoprene mixing ratios in the mixed layer were investigated with a tethered balloon sampling system and ranged from 0.2 to 5 ppbv, averaging 0.8 ppbv. The isoprene mixing ratios in the mixed layer above the forested landscape were used to estimate isoprene fluxes of 2 to 8 mg C m−2 h−1 with mixed layer gradient and mixed layer mass balance techniques. Total foliar density and dominant tree species composition for an approximately 8100 km2 region were estimated using high-resolution (30 m) satellite data with classifications supervised by ground measurements. A biogenic isoprene emission model used to compare flux measurements, ranging from leaf scale (10 cm2) to landscape scale (102 km2), indicated agreement to within ±25%, the uncertainty associated with these measurement techniques. Existing biogenic emission models use isoprene emission rate capacities that range from 14.7 to 70 μg C g−1 h−1 (leaf temperature of 30°C and photosynthetically active radiation of 1000 μmol m−2 s−1) for oak foliage. An isoprene emission rate capacity of 100 μg C g−1 h−1 for oaks in this region is more realistic and is recommended, based on these measurements.

Biogenic volatile organic compound emissions (BVOCs). I. Identifications from three continental sites in the U.S.

Vegetation composition and biomass were surveyed for three specific sites in Atlanta, GA; near Rhinelander, WI; and near Hayden, CO. At each research site emissions of biogenic volatile organic compounds (BVOCs) from the dominant vegetation species were sampled by enclosing branches in bag enclosure systems and sampling the equilibrium head space onto multi-stage solid adsorbent cartridges. Analysis was performed using a thermal desorption technique with gas chromatography (GC) separation and mass spectrometry (MS) detection. Identification of BVOCs covering the GC retention index range (stationary phase DB-1) from approximately 400 to 1400 was achieved (volatilities C4-C14).

Volatile organic compound emission rates from mixed deciduous and coniferous forests in Northern Wisconsin, USA

Biogenic emissions of volatile organic compounds {VOC) from forests play an important role in regulating the atmospheric trace gas composition including global tropospheric ozone concentrations. However, more information is needed on VOC emission rates from different forest regions of the world to understand regional and global impacts and to implement possible mitigation strategies. The mixed deciduous and coniferous forests of northern Wisconsin, USA were predicted to have significant VOC emission rates because they are comprised of many genera (i.e. Picea, Populus, Quercus, Salix) known to be high VOC emitters. In July 1993, a study was conducted on the Chequamegon National Forest near Rhinelander, WI to identify and quantify VOC emitted from major trees, shrubs, and understory herbs in the mixed northern forests of this region. Emission rates were measured at various scales -at the leaf level with cuvettes, the branch level with branch enclosures, the canopy level with a tower based system, and the landscape level with a tethered balloon air sampling system. Area-average emission rates were estimated by scaling, using biomass densities and species composition along transects representative of the study site. Isoprene (C5H8) was the primary VOC emitted, although significant quantities of monoterpenes (C10H16) were also emitted. The highest emission rates of isoprene (at 30C and photosynthetically active radiation of 1000 umolm-2s-1) were from northern red oak (Quercus rubra. > 110 ug(C)g-1h-1): aspen (Populus tremuloides. > 77): willow (Salix spp.. > 54): and black spruce (Picea mariamz. > 101. Emission rates of hybrid poplar clones ranged from 40 to 90 ug(C)g-1h-1 at 25C: those of Picea provenances were generally

The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data

Individual tree detection algorithms can provide accurate measurements of individual tree locations, crown diameters (from aerial photography and light detection and ranging (lidar) data), and tree heights (from lidar data). However, to be useful for forest management goals relating to timber harvest, carbon accounting, and ecological processes, there is a need to assess the performance of these image-based tree detection algorithms across a full range of canopy structure conditions. We evaluated the performance of two fundamentally different automated tree detection and measurement algorithms (spatial wavelet analysis (SWA) and variable window filters (VWF)) across a full range of canopy conditions in a mixed-species, structurally diverse conifer forest in northern Idaho, USA. Each algorithm performed well in low canopy cover conditions (<50% canopy cover), detecting over 80% of all trees with measurements, and producing tree height and crown diameter estimates that are well correlated with field measurements. However, increasing tree canopy cover significantly decreased the accuracy of both SWA and VWF tree measurements. Neither SWA or VWF produced tree measurements within 25% of field-based measurements in high canopy cover (i.e., canopy cover >50%) conditions. The results presented herein suggest that future algorithm development is required to improve individual tree detection in structurally complex forests. Furthermore, tree detection algorithms such as SWA and VWF may produce more accurate results when used in conjunction with higher density lidar data.

Use of a ground-based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis)

Ground‐based laser scanners represent a relatively new technology that promises to enhance the ability to remotely sense biophysical properties of vegetation. In this study, we utilized a commercially available discrete‐return ground‐based laser scanning system to sample properties of western larch (Larix occidentalis) in a northern Idaho forest. Three young trees <5 m in height were scanned before and after leaf abscission in the autumn of 2004. Leaf areas represented by the number of laser returns were estimated by subtracting leaf‐off laser returns from leaf‐on returns. Leaf areas represented by number of laser returns were significantly correlated with manual‐based estimates of leaf area (r 2 = 0.822). Ratios of woody‐to‐total tree area were estimated based on number of laser returns from woody material. Ratios of woody‐to‐total area ranged from 0.24 to 0.58 for nine one‐metre sections of tree for which estimates were made. Ratios of woody‐to‐total area were also estimated using intensity of laser returns and fell near the range of estimates made using the number of laser returns. Improved estimation of leaf area, woody‐to‐total area ratios, and other biophysical parameters using ground‐based laser scanning technology may be possible with a careful consideration of instrument specifications and sampling design.

Biogenic hydrocarbon emissions and landcover/climate change in a subtropical savanna

Abstract Biogenic non-methane hydrocarbon (NMHC) emissions strongly influence the chemical composition of the troposphere. Thus, variations in emissions of these compounds are expected to cause changes in concentrations of important atmospheric trace gases. Here, we assess the relative magnitude of potential changes in NMHC (e.g., isoprene and monoterpene) emissions using field flux measurements from a subtropical savanna parkland/thorn woodland site in conjunction with model predictions of climate and landcover change. NMHC emissions of about 40 plant species were characterized. Grasses, as a group, had low emission rates. Several common woody species had high emission rates. However, there was little evidence of emissions being consistently related to woody plant taxonomy, growthform or functional groups. Above-canopy measurements were used to validate modeled isoprene flux predictions of about 2 mg C m−2 h−1 for savanna parkland/thorn woodland and ca. 0.7 mg C m−2 h−1 for the regional landscape, which is a mixture of savanna parkland/thorn woodland and cropland. Linkage of the biogenic emissions model with a plant succession model indicated that landcover change since the early 1800s has elicited a 3-fold increase in total NMHC emissions. This increase reflected changes in vegetation species composition (from domination by grasses which were typically ‘low emitters’, to shrubs and trees, many of which were ‘high emitters’) and increases in foliar density. Field measurements on two common shrub species indicated that isoprene emission increased exponentially with increases in leaf temperature from 20 to 40° C and were not suppressed by drought stress. Accordingly, our model predicted that projected increases in ambient temperature (3 to 6°C) emissions could produce a 2-fold increase in biogenic NMHC emissions. Cloud cover, precipitation, relative humidity, and winds also exerted some control over NMHC emissions, but their influence was highly variable and difficult to estimate. Although our results are specific to southern Texas USA, they indicate the magnitude of change in NMHC emissions that could occur at other locations when climate and vegetation composition are altered.