A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.     

Rapid Assessment of Plant Diversity Patterns: A Methodology for Landscapes

We present a rapid, cost-efficient methodology to link plantdiversity surveys from plots to landscapes using: (1) unbiasedsite selection based on remotely sensed information; (2) multi-scale field techniques to assess plant diversity; (3)mathematical models (species-area curves) to estimate thenumber of species in larger areas corrected for within-typeheterogeneity; and (4) mathematical techniques to estimatetotal species richness and patterns of plant diversity in alandscape. We demonstrate the methodology in a 754 ha studyarea in Rocky Mountain National Park, Colorado, U.S.A.,using four 0.025 ha and twenty-one 0.1 ha multi-scalevegetation plots. We recorded 330 plant species (1/3 thenumber of plants recorded in the 1074 km² Park) in the2.2 ha area within the plots: this represents a samplingintensity of 0.29% of the 754 ha study site. We estimated 552plant species, about half the plant species recorded in the Park,in just 0.7% of the Parks area. We show how this rapid,cost-efficient methodology: (1) produces a rich informationbase on the patterns of native plant diversity and thedistribution of non-native plant species and keystoneecosystems; and (2) can be easily adapted for other nationaland state parks, national forests, wildlife refuges, and nature reserves.     

Assessing Landscape Condition Relative to Water Resources in the Western United States: A Strategic Approach

The Environmental Monitoring and Assessment Program (EMAP) is proposing an ambitious agenda to assess the status of streams and estuaries in a 12-State area of the western United States by the end of 2003. Additionally, EMAP is proposing to access landscape conditions as they relate to stream and estuary conditions across the west. The goal of this landscape project is to develop a landscape model that can be used to identify the relative risks of streams and estuaries to potential declines due to watershed-scale, landscape conditions across the west. To do so, requires an understanding of quantitative relationships between landscape composition and pattern metrics and parameters of stream and estuary conditions. This paper describes a strategic approach for evaluating the degree to which landscape composition and pattern influence stream and estuary condition, and the development and implementation of a spatially-distributed, landscape analysis approach.     

The Influence of Linear Elements on Plant Species Diversity of Mediterranean Rural Landscapes: Assessment of Different Indices and Statistical Approaches

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements -habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land- whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index.Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50×20 m² multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators.The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.     

A Multilevel Modeling Approach to Assessing Regional and Local Landscape Features for Lake Classification and Assessment of Fish Growth Rates

The ecoregion and watershed frameworks are landscape-based classifications that have been used to group waterbodies with respect to measures of community structure; however, they have yet to be evaluated for grouping lakes for demographic characteristics of fish populations. We used a multilevel modeling approach to determine if variability in mean fish length at age could be partitioned by ecoregions and watersheds. For the ecoregions analysis, we then examined if within-ecoregion variability could be explained by local water quality and lake morphometry characteristics. We used data from agency surveys conducted during 1974-1984 for age 2 and 3 fish of seven common warm and coolwater fish species. Variance in mean length at age between ecoregions for all species was not significant, and between-watershed variance estimates were only significant in 3 out of 14 analyses; however, the total amount of variation between watersheds was very small (ranging from 1.8% to 3.7% of the total variance), indicating that ecoregions and watersheds were ineffective in partitioning variability in mean length at age. Within ecoregions, water quality and lake morphometric characteristics accounted for 2%-23% of the variation in mean length at age. Measures of lake productivity were the most common significant covariates, with mean length at age increasing with increasing lake productivity. Much of the variability in mean length at age was not accounted for, suggesting that other local factors such as biotic interactions, fish density, and exploitation are important. The results indicate that the development of an effective regional framework for managing inland lakes will require a substantial effort to understand sources of demographic variability and that managers should not rely solely on ecoregions or watersheds for grouping lakes with similar growth rates.     

Development of a New Approach to Cumulative Effects Assessment: A Northern River Ecosystem Example

If sustainable development of Canadian waters is to be achieved, a realistic and manageable framework is required for assessing cumulative effects. The objective of this paper is to describe an approach for aquatic cumulative effects assessment that was developed under the Northern Rivers Ecosystem Initiative. The approach is based on a review of existing monitoring practices in Canada and the presence of existing thresholds for aquatic ecosystem health assessments. It suggests that a sustainable framework is possible for cumulative effects assessment of Canadian waters that would result in integration of national indicators of aquatic health, integration of national initiatives (e.g., water quality index, environmental effects monitoring), and provide an avenue where long-term monitoring programs could be integrated with baseline and follow-up monitoring conducted under the environmental assessment process.     

Distribution of Chlorinated Organic Pollutants in Harbor Sediments of Livorno (Italy): A Multivariate Approach to Evaluate Dredging Sediments

Dredging is a very important procedure for harbor management. InItaly the guidelines for the offshore dumping of dredged materials are issued by the Ministry of Environment. Theydescribed a few steps of dredging activities, such as thesampling strategy, but do not deal with limits or guide-valuesfor the chemical, physical and biological composition of theresulting sediments. The quality of dredged materials is mainlydependent on the presence of inorganic and organic pollutants.In particular, polychlorinated biphenyls (PCBs) and organo-chlorinated pesticides are seen as a high priority inmarine environment by international organizations because oftheir persistence, toxicity and bioaccumulation capacity.In this article the presence of some PCBs and organo-chlorinatedpesticides in sediment samples collected from the harbor ofLivorno (Northern Tyrrhenian Sea) was investigated. Theconcentration of HCHs, Aldrin, Chlordanes, DDEs, DDTs, and PCBsin 12 representative sites ranged between <1 g kg^–1and 95, 19, 32, 35, 107, and 111 g kg^–1, respectively.The application of univariate and multivariate statisticaltechniques, such as linear regression analysis and principalcomponent analysis, to the experimental data showed a differentdistribution of PCBs in the two sediment layers. On thecontrary, the vertical distribution of the other investigatedpollutants was more homogeneous and affected by randomvariability. The multivariate approach was an important tool to establish more rational criteria for the management of dredged materials.