Aboveground plant community and species-specific vegetation cover from the Jena Experiment (Main Experiment, year 2004)

This data set contains information on vegetation cover, i.e. the proportion of soil surface area that is covered by different categories of plants per estimated plot area. Data was collected on the plant community level (sown plant community, weed plant community, dead plant material, and bare ground) and on the level of individual plant species in case of the sown species. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2004, vegetation cover was estimated twice in May and August just prior to mowing (during peak standing biomass) on all experimental plots of the Main Experiment. Cover was visually estimated in a central area of each plot 3 by 3 m in size (approximately 9 m²) using a decimal scale (Londo). Cover estimates for the individual species (and for target species + weeds + bare ground) can add up to more than 100% because the estimated categories represented a structure with potentially overlapping multiple layers. In 2004, cover on the community level was only estimated for the sown plant community, weed plant community and bare soil. In contrast to later years, cover of dead plant material was not estimated.

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

The relationship between vegetation and modern pollen assemblages on Mount Paggeo (NE Greece)

In this study, we investigated the relationship between vegetation and modern-pollen rain along the elevational gradient of Mount Paggeo. We apply multivariate data analysis to assess the relationship between vegetation and modern-pollen rain and quantify the representativeness of forest zones. This study represents the first statistical analysis of pollen-vegetation relationship along an elevational gradient in Greece. Hence, this paper improves confidence in interpretation of palynological records from north-eastern Greece and may refine past climate reconstructions for a more accurate comparison of data and modelling. Numerical classification and ordination were performed on pollen data to assess differences among plant communities that beech (Fagus sylvatica) dominates or co-dominates. The results show a strong relationship between altitude, arboreal cover, human impact and variations in pollen and nonpollen palynomorph taxa percentages.

Spectral Properties of Vegetation

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

Vegetation Indices

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

Normalised Difference Vegetation Index

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

Enhanced Vegetation Index

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

Sugarcane leaf area estimate obtained from the corrected normalized difference vegetation index (NDVI)

v. 46, n. 2, p. 140-148, apr./jun. 2016.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

Evaluation of vegetation recovery after fire: a case study in Calde, central region of Portugal

Remote Sensing has been used for decades, and more and more applications are added to its repertoire. With this study we aim to show the use of Remote Sensing in the field of vegetation recovery monitoring in burned areas and the added value of data with a high spatial resolution. This was done by analysing both Landsat 7 and 8 scenes, after the forest fire of summer 2012 in the parish of Calde, in the central region of Portugal, as well as an orthophoto produced with images acquired by an unmanned aerial vehicle.

DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

Conversion of sub-tropical native vegetation to introduced conifer forest: Impacts on below-ground and above-ground carbon pools

Land-use change can have a major influence on soil organic carbon (SOC) and above-ground C pools. We assessed a change from native vegetation to introduced Pinus species plantations on C pools using eight paired sites. At each site we determined the impacts on 0–50 cm below-ground (SOC, charcoal C, organic matter C, particulate organic C, humic organic C, resistant organic C) and above-ground (litter, coarse woody debris, standing trees and woody understorey plants) C pools. In an analysis across the different study sites there was no significant difference (P > 0.05) in SOC or above-ground tree C stocks between paired native vegetation and pine plantations, although significant differences did exist at specific sites. SOC (calculated based on an equivalent soil mass basis) was higher in the pine plantations at two sites, higher in the native vegetation at two sites and did not differ for the other four sites. The site to site variation in SOC across the landscape was far greater than the variation observed with a change from native vegetation to introduced Pinus plantation. Differences between sites were not explained by soil type, although tree basal area was positively correlated with 0–50 cm SOC. In fact, in the native vegetation there was a significant linear relationship between above-ground biomass and SOC that explained 88.8% of the variation in the data. Fine litter C (0–25 mm diameter) tended to be higher in the pine forest than in the adjacent native vegetation and was significantly higher in the pine forest at five of the eight paired sites. Total litter C (0–100 mm diameter) increased significantly with plantation age (R2 = 0.64). Carbon stored in understorey woody plants (2.5–10 cm DBH) was higher in the native vegetation than in the adjacent pine forest. Total site C varied greatly across the study area from 58.8 Mg ha−1 at a native heathland site to 497.8 Mg ha−1 at a native eucalypt forest site. Our findings suggest that the effects of change from native vegetation to introduced Pinus sp. forest are highly site-specific and may be positive, negative, or have no influence on various C pools, depending on local site characteristics (e.g. plantation age and type of native vegetation).

Protein feeding of Queensland fruit fly Bactrocera tryoni and cucumber fly Zeugodacus cucumis (Diptera: Tephritidae) on non-host vegetation: effect of plant species and bait height

Perimeter-baiting of non-crop vegetation using toxic protein baits was developed overseas as a technique for control of melon fly, Zeugodacus (Zeugodacus) cucurbitae (Coquillett) (formerly Bactrocera (Zeugodacus) cucurbitae), and evidence suggests that this technique may also be effective in Australia for control of local fruit fly species in vegetable crops. Using field cage trials and laboratory reared flies, primary data were generated to support this approach by testing fruit flies' feeding response to protein when applied to eight plant species (forage sorghum, grain sorghum, sweet corn, sugarcane, eggplant, cassava, lilly pilly and orange jessamine) and applied at three heights (1, 1.5 and 2 m). When compared across the plants, Queensland fruit fly, Bactrocera tryoni (Froggatt), most commonly fed on protein bait applied to sugarcane and cassava, whereas more cucumber fly, Zeugodacus (Austrodacus) cucumis (French) (formerly Bactrocera (Austrodacus) cucumis), fed on bait applied to sweet corn and forage sorghum. When protein bait was applied at different heights, B. tryoni responded most to bait placed in the upper part of the plants (2 m), whereas Z. cucumis preferred bait placed lower on the plants (1 and 1.5 m). These results have implications for optimal placement of protein bait for best practice control of fruit flies in vegetable crops and suggest that the two species exhibit different foraging behaviours.

DIFFERENTIATION OF ARBOREAL VEGETATION IN THREE SECTORS OF A FOREST FRAGMENT RELATED TO ITS HISTORICAL DISTURBANCES

Forest fragmentation is one of the main causes of biodiversity loss, directly affecting the ecological processes. This study aimed to evaluate tree diversity, structure, and composition parameters in three sectors of a forest fragment with distinct disturbance records. The arboreal vegetation was evaluated in twenty-four 10 × 10 m plots, sampling a total of 1,228 living individuals. We calculated Shanon’s diversity index, Pielou’s equability, and jackknife estimators of first and second orders. The sampled individuals were distributed in diameter classes and the importance value (VI) was calculated for each species. It was made a Detrended Correspondence Analysis (DCA) to verify whether there were significant distinctions between the sectors. It was noticed that the sector where there was clear cutting and vegetation burning in a recent past had higher abundance and richness but also the worst equability. That corresponds to the effects of perturbation as confirmed by the tree diameters and the presence of species of greater importance value. The sector that had no record of disturbance, situated in a location with greater variety of microenvironments, presented diversity, structure, and composition consistent with a no disturbance scenario. The other sector, which did not have clear cutting, was subjected to cattle trampling presented ecological parameters consistent with the absence of major disturbances. On the other hand, this third sector had the smallest environmental diversity, which puts this last sector in an intermediate situation.