Vegetation maps based on remote sensing are informative predictors of habitat selection of grassland birds across a wetness gradient

Vegetation is a major environmental factor influencing habitat selection in bird species. High resolution mapping of vegetation cover is essential to model the distribution of populations and improve the management of breeding habitats. However, the task is challenging for grassland birds because microhabitat variations relevant at the territory scale cannot be measured continuously over large areas to delineate areas of higher suitability. Remote sensing may help to circumvent this problem. We addressed this issue by using SPOT 5 imagery and phytosociological data. We mapped grassland vegetation in a floodplain using two methods. We (i) mapped the continuous Ellenberg index of moisture and (ii) identified 5 vegetation classes distributed across the wetness gradient. These two methods produced consistent output maps, but they also provided complementary results. Ellenberg index is a valuable proxy for soil moisture while the class approach provided more information about vegetation structure, and possibly trophic resources. In spite of the apparent uniformity of meadows, our data show that birds do not settle randomly along the moisture and vegetation gradients. Overall birds tend to avoid the driest vegetation classes, i.e. the highest grounds. Thus, vegetation maps based on remote sensing could be valuable tools to study habitat selection and niche partition in grassland bird communities. It is also a valuable tool for conservation and habitat management.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Plant functional types and climatic change: Introduction

Abstract. Plant functional types are a necessary device for reducing the complex and often uncharted characteristics of species diversity in function and structure when attempting to project the nature and function of species assemblages into future environments. A workshop was held to review the current methods commonly used for defining plant functional types, either globally or for particular biomes, and to compare them with the field experiences of specialists for specific biomes of the world. The methods fall into either an objective and inductive approach or a subjective and deductive approach. When the different methods were tested, it was generally found that the classification for one site or environment was not wholly applicable to a different site or environment. However, the degree of change which is necessary for adjustment between environments may not prove to be a major limitation in the use of functional types.     

Latitudinal comparison of altitudinal changes in forest structure,leaf-type,and species richness in humid monsoon Asia

A new template for mountain vegetation zonation along latitudinal gradients is proposed for examining geographical pattern of various forest attributes in humid monsoon Asia. The contrasting temperature regime in tropical and temperate mountains, i.e., the former is a non-seasonal, temperature-sum controlled environment, and the latter is a seasonal, low temperature limiting environment, leads to different altitudinal patterns of tree height distribution and species richness. In the tropical mountains, both tree height and species richness decrease steeply, and the tree height often stepwise. The decline of tree height and species diversity in the temperate mountains is far less pronounced except near the forest limit. Both trends are explained by their temperature regime.     

Functional classifications of coastal barrier island vegetation

Abstract. Due to the complexity of coastal barrier vegetation, it is useful to apply a functional-type approach to assess the response of barrier island vegetation to climate change. In this paper, a simple clustering analysis is applied to a group of 19 plant associations, based on six plant attributes and six environmental constraints. This analysis results in the suggestion that the main division of the vegetation types at Virginia Coast Reserve is between herbaceous and woody types, which differs from the existing classification which recognizes three groups: xeric-mesic herbaceous, woody and hydric-halophytic herbaceous. Considerations about grouping plant functional types are also addressed in this paper. At a global scale, inclusion of barrier plant functional types may not be so important for the climate-change response of vegetation, but it may be necessary to consider these important systems for spatially explicit modelling of landscape responses.     

EMAP-Wetlands: A sampling design with global application

The U.S. Environmental Protection Agency (EPA) initiated the Environmental Monitoring and Assessment Program (EMAP) in 1988. The wetland component (EMAP-Wetlands) is designed to provide quantitative assessments of the current status and long-term trends in the ecological condition of wetland resources. EMAP-Wetlands will develop a wetland monitoring network and will identify and evaluate indicators that describe and quantify wetland condition. The EMAP-Wetlands network will represent a probability sample of the total wetland resource. The EMAP sample is based on a triangular grid of approximately 12,600 sample points in the conterminous U.S. The triangular grid adequately samples wetland resources that are common and uniformly distributed in a region, such as the prairie pothole wetlands of the Midwest. However, the design is flexible and allows the base grid density to be increased to adequately sample wetland resources, such as the coastal wetlands of the Gulf of Mexico, which are distributed linearly along the coast. The Gulf sample network required a 49-fold increase in base grid density. EMAP-Wetlands aggregates the 56 U.S. Fish and Wildlife Service's (FWS) National Wetland Inventory (NWI) categories (Cowardin et al. 1979) into 12 functionally similar groups (Leibowitz et al. 1991). Both the EMAP sample design and aggregated wetland classes are suitable for global inventory and assessment of wetlands.The research described in this report has been funded by the U.S. Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, OR, through contract No. 68-C8-0006 to Man Tech Environmental Technology, Inc. This paper has been subjected to the Agency's peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

In and out: Effects of shoot- vs. rooted-presence sampling methods on plant diversity measures in mountain grasslands

Plant diversity measures (e.g., alpha- and beta-diversity) provide the basis for a number of ecological indication and monitoring methods. These measures are based on species counts in sampling units (plots or quadrats). However, there are two alternative conventions for defining a vascular plant species as “present” in a plot, i.e. “shoot presence” (a species is recorded if the vertical projection of any above-ground part falls within the plot) and “rooted presence” (a species is recorded only when an individual is rooted inside the plot). Very few studies addressed the effects of the two sampling conventions on species richness and diversity indices. We sampled mountain dry grasslands in Italy across different plot sizes and vegetation types to assess how large is the difference in alpha- and beta-diversity values and in sample-based rarefaction curves between the two methods. We found that the difference is greatly dependent on plot size, being more relevant, both in absolute and percentage values, at smaller grain; it is also dependent on habitat type, being larger in shallow-soil communities, as they have a sparser vegetation structure and host life-form types with a larger lateral spread. At fine spatial scales (<1 m²) the difference is large enough to bias statistical inference, and we conclude that at such scales one should not attempt to compare plant diversity indices if they were not obtained with the same sampling convention.     

Analysis of Profiles Based on Ordinal Classification Functions and Rank Tests

In this article a test for the comparison of K groups of independent profiles is suggested. It is based on rank tests, in which the criterion is obtained by using a suitably chosen ordinal classification function. This function represents a specific view on the profiles. The test, which is easy to use, can be regarded as a generalisation of other well known tests and can be applied within a variety of situations. The relationships to other procedures for the analysis of profiles are described. Some properties are discussed.     

The influence of environmental factors on the spatial distribution of saxicolous lichens in a Norwegian coastal community

Abstract. The effects of vegetation cover, radiation, micro‐habitat variables and maritime influence on the floristic composition of a saxicolous community in Vingen, western Norway were studied. Particular emphasis is put on the local distribution of Fuscidea cyathoides, Ochrolechia tartarea, Ophioparma ventosa and Pertusaria corallina. Very little of the variation in the lichen community composition is directly related to measured micro‐environmental variables but variance partitioning shows that vegetation cover explains more of the floristic variation than radiation, maritime influence and microhabitat variables. Logistic regression analyses nevertheless indicate that the micro‐environment influences the spatial distribution of the four species. The high fraction of unexplained floristic variation, 91%, is suggested to result from (1) lack of fit of data to the response model; (2) some influential environmental variables that have not been recorded; (3) local historical factors that affect present day distribution and/or (4) apparent randomness in colonization. The results also agree with the view that the four lichen species in this study are able to co‐exist in the long‐term because of different spatial distributions resulting from different strategies with respect to ecology, dispersion and interaction.     

Novel summary metrics for insular biotic assemblages based on taxonomy and phylogeny: Biogeographical,palaeogeographical and possible conservational applications

Using the land‐bound vertebrates on the marine islands as model organisms, two metrics are presented that permit quantitative and succinct synopses of the ‘evolutionary maturity’ of the hosted faunal assemblages. In turn, these reflect the geo‐physical settings and geological developments of the substrates. The assemblage lineage‐taxonomy spectrum (ALTS) is based on the constituent lineages’ taxonomic distinctiveness and diversity. Individual lineages within assemblages can in most cases be assigned to one of six categories, LT1?LT6: LT1 is a non‐endemic taxon, whereas LT6 comprises multiple endemic genera from a family that arose elsewhere. If required, the scheme can be expanded: LT9 is an endemic order. The data can then be combined to provide an assemblage spectrum, for example, 00:08:38:30:08:15[ 13 ]. Here, the first six values denote the number of lineages assigned to each category expressed as percentages of the overall total, with the sum of the processed lineages listed as the seventh (in brackets and bold). The ALTS metric highlights efficiently the key features of a marine island's biological assemblage. Notably, the contrast between spectra for suites on geologically and geo‐physically varied island types can be striking, for instance the squamate suite on the young, proximate orogenic margin island of Taiwan is coded 78:16:05:00:00:00[ 37 ] whereas the one on the distantly located, Late Eocene composite terrane island of New Caledonia is 00:11:00:11:33:44[ 9 ]. To overcome the subjectivity that is inherent in assigning supraspecific ranks, an alternative assemblage lineage‐age spectrum (ALAS) is also introduced that makes use of the binary logarithm values of the colonization times of the island lineages (0–2, 2–4, … , 32–64, >64 Ma). It is represented using a seven‐plus‐two‐number code, for instance Madagascar's squamates are 00:06:00:00:19:62:12[ 19 ( 16 )]; most colonizations took place in the Palaeogene (66–23 Ma); there are 19 lineages, but only 16 are presently age‐dated. In addition to marine‐island biogeography studies, the ALTS–ALAS spectrum approach is potentially useful for encapsulating biotas in other sorts of insular setting (e.g. lakes, mountain tops), and for evaluating palaeogeographical models. Furthermore, it may help emphasize the conservation value of an island's faunal assemblage.