Principal Component Analysis Axes Research Articles

Twentieth century human and climate impacts on a large mountain lake in southwest China

Subfossil chironomid and sediment geochemistry data from Lugu Lake, a large high-elevation lake in southwest China, were used to assess the influences of climate warming and direct human impacts on the lake through time. A 95-year-long sediment record was recovered from the lake. Principal components analysis (PCA) and redundancy analysis of fossil chironomid data were performed to determine the controlling factors on the chironomid community. The four prominent environmental controls were summer air temperature, organic matter C:N ratio (Corg:N), dry mass accumulation rate (DMAR), and total nitrogen. Corg:N proved to be the most important controlling factor through time. However, Corg:N and summer air temperature were highly co-linear, possibly due to temperature directly impacting lake productivity (and thus C:N ratios) through increased stratification and a longer growing season. PCA Axis 1 scores were a strong predictor of summer temperatures even after DMAR was factored out to account for direct human influences. The strong temperature–chironomid relationship over the last 50 years could be due to the lake becoming more responsive to climate warming after cultural eutrophication of the 1950s, as lakes with higher nutrient loads are shown to be more responsive to the effects of climate warming.

Relationships between chironomids and water depth in Bosten Lake, Xinjiang, northwest China

A significant relationship between the distribution and abundance of chironomids and water depth has long been recognized. Few studies on this topic, however, have been carried out in arid regions where the chironomid community is usually controlled by water salinity. Bosten Lake, northwest China, the largest inland freshwater lake (~1,260 km2) in the country, provides a unique opportunity to investigate this relationship in an arid region. A total of 42 surface sediment samples from water depths of 0.9–17.0 m, and 12 chironomid taxa, were used in the analysis. The first principal component analysis (PCA) axis explained 59.3 % of the variance in the chironomid assemblage and there was a significant correlation between PCA axis 1 scores and water depth (R2 = 0.84, P < 0.001). The chironomid assemblages change significantly at 8.0 m water depth. This threshold corresponds to an abrupt change in the basin slope and the spatial distribution of aquatic vascular plants. Redundancy analysis showed that abundances of Chironomusplumosus-type, Microchironomus and Cryptochironomus are positively correlated with water depth, whereas abundances of Tanytarsus, Polypedilum nubifer-type, Cricotopus and Psectrocladius sordidellus-type are negatively correlated with water depth. These ecological relationships are supported by published data. Qualitative chironomid-inferred changes in lake level and diatom-inferred changes in salinity from sediment core BSTC001 were compared. Close agreement in trends for these two variables validates the use of chironomid assemblages to study palaeo-hydrological variability in this westerlies-dominated, arid region of central Asia.

The skin aging index: a new approach for documenting anti‐aging products or procedures

The overall appearance of an aged skin is characterized by a combination of several attributes such as wrinkles, brown spots and sagging. Our objective was to develop and validate a statistical framework to assess the overall anti-ageing benefits of products/procedures. Different skin attributes were evaluated by a clinical grader and combined using a Principal Component Analysis (PCA). The Skin Ageing Index was defined as the normalized projection of the clinical grading values on the first PCA axis. Several Skin Indexes were built by grouping specific parameters related to a skin condition such as overall ageing, wrinkles and sagging. The method was validated following two steps. Firstly, a clinical study was performed on 173 Caucasian women and the correlation between the Skin Indexes and the volunteers' real and perceived age was estimated. Secondly, a double-blinded placebo-controlled randomized study was performed on 87 Caucasian women to assess the efficacy of an anti-wrinkle cream containing retinol, hyaluronic acid and dihydroxymethylchromone. Facial wrinkles were clinically evaluated and a Wrinkle Index was built. All indexes were highly correlated with the real and the perceived age (0.57≤Pearson R≤0.92, P-value≤0.05). Finally, the Wrinkle Index provides documented evidence that the tested product significantly reduced the appearance of wrinkles versus the placebo and the baseline assessment (-23.53% after 4weeks, -27.83% after 8weeks). Skin ageing Indexes capture information relevant to the visual transformation of facial skin with age, while providing documented product benefits. These tools may enable a simpler and more consistent comparison of anti-ageing products/procedures.

Allocating CSR plant functional types: the use of leaf economics and size traits to classify woody and herbaceous vascular plants

Summary Three main directions of adaptive specialization are evident in the world flora, reflecting fundamental trade‐offs between economics (conservative vs. acquisitive investment of resources) and size. The current method of ordinating plants according to these trade‐offs, CSR classification, cannot be applied to the woody species that dominate many terrestrial ecosystems. We aimed to produce a novel CSR classification method applicable to vascular plants in general. Principal components analysis (PCA) of variation in a range of plant traits for 678 angiosperm, gymnosperm and pteridophyte species was used to determine the limits to multivariate space occupied by functionally diverse species. From this calibration, correlations between PCA axes and values of leaf dry matter content (LDMC; as an index of conservatism in life history), specific leaf area (SLA; indicative of acquisitive economics) and leaf area (LA; photosynthetic organ size) were used to produce predictor regressions from which target species could be compared against the multivariate space. A spreadsheet was developed that returned ternary coordinates and tertiary CSR strategies for target subjects based on LA, LDMC and SLA values. The method allowed classification of target species within a triangular space corresponding to Grime's theoretical CSR triangle and was sufficiently precise to distinguish strategies between species within genera and within populations of species. It was also largely in agreement with previous methods of CSR classification for herbaceous species. Rapid CSR classification of woody and herbaceous vascular plants is now possible, potentially allowing primary plant functional types and ecosystem processes to be investigated over landscape scales.

Head-and-face shape variations of U.S. civilian workers

The objective of this study was to quantify head-and-face shape variations of U.S. civilian workers using modern methods of shape analysis. The purpose of this study was based on previously highlighted changes in U.S. civilian worker head-and-face shape over the last few decades – touting the need for new and better fitting respirators – as well as the study's usefulness in designing more effective personal protective equipment (PPE) – specifically in the field of respirator design. The raw scan three-dimensional (3D) data for 1169 subjects were parameterized using geometry processing techniques. This process allowed the individual scans to be put in correspondence with each other in such a way that statistical shape analysis could be performed on a dense set of 3D points. This process also cleaned up the original scan data such that the noise was reduced and holes were filled in. The next step, statistical analysis of the variability of the head-and-face shape in the 3D database, was conducted using Principal Component Analysis (PCA) techniques. Through these analyses, it was shown that the space of the head-and-face shape was spanned by a small number of basis vectors. Less than 50 components explained more than 90% of the variability. Furthermore, the main mode of variations could be visualized through animating the shape changes along the PCA axes with computer software in executable form for Windows XP. The results from this study in turn could feed back into respirator design to achieve safer, more efficient product style and sizing. Future study is needed to determine the overall utility of the point cloud-based approach for the quantification of facial morphology variation and its relationship to respirator performance.

Fragment size, vegetation structure and physical environment control grassland functioning: a test based on artificial neural networks

AbstractQuestionsHow do fragment‐level characteristics affect remnant grassland functioning in a highly transformed landscape? Are artificial neural networks (ANNs) a better statistical tool to model variations in grassland functioning compared to linear regression models (LRMs)?LocationTandilia Range, Southern Pampa, Buenos Aires Province, Argentina.MethodsWe characterized the dynamics of the vegetation functioning in 60 remnant grasslands using enhanced vegetation index (EVI) data provided by MODIS/Terra images from July 2000 to June 2005. First, we performed a principal components analysis (PCA) on the fragment mean monthly values of EVI in order to obtain synthetic measures (i.e. the PCA axes) of grassland functioning. Grassland fragments were also characterized by size, vegetation structure (abundance of the tall‐tussock grass Paspalum quadrifarium) and physical environment (soil type – abundance of litholitic soils – elevation, aspect and slope). The relationship between grassland functioning and these explanatory variables was explored using linear regression models (LRMs) and artificial neural networks (ANNs).ResultsThe first and second PCA axes were related to the annual integral of EVI (EVI‐I) and EVI seasonality (EVI‐S), respectively; these explained jointly ca. 80% of total variability in mean EVI values. ANNs captured better than regression models the relationships among the proposed controls and the spatial variability of grassland functioning in Southern Pampa. Results showed that EVI‐I variability was related to all independent variables except aspect. While fragment size, litholitic soils and slope were negatively related to EVI‐I, the abundance of P. quadrifarium had a positive effect on the spectral index. Grasslands with high seasonality were large and had high slope and aspect, low abundance of P. quadrifarium and increased abundance of litholitic soils.ConclusionsOur results showed that grassland functioning in Southern Pampa, as estimated by EVI, depends on fragment size, vegetation structure and physical factors (soil type, aspect and slope). Paspalum quadrifarium may have an important functional role in this grassland system.

Water Balance and Spatial Distribution of an Anuran Community from Brazil

Abstract: Terrestrial amphibians may dehydrate when exposed to low humidity, representing an important factor affecting spatial distribution and community composition. In this study we investigated whether rates of dehydration and rehydration are able to explain the spatial distribution of an anuran community in a Restinga environment at the northern coast of the State of Bahia, Brazil, represented by 11 species distributed in 27 sample units. The environmental data set containing 20 variables was reduced to a few synthetic axes by principal component analysis (PCA). Physiological variables measured were rates of dehydration, rehydration from water, and rehydration from a neutral substrate. Multiple regression analyses were used to test the null hypothesis of no association between the environmental data set (synthetic axes of PCA) and each axis representative of a physiological variable, which was rejected (P < 0.001). Of 15 possible partial regressions only rehydration rate from neutral substrate vs. PC...

Agro-morphological markers and organo-sulphur compounds to assess diversity in Tunisian garlic landraces

This work is aimed at studying diversity of 31 garlic landraces from Tunisia and structuring this diversity. It helped at establishing correlations between content of organo-sulphur compounds and agro-morphological characteristics. For this purpose the quantitative variability of five organo-sulphur compounds, namely: alliin, isoalliin, glutamyl allyl cysteine (GluAlCs), isoglutamyl allyl cysteine (isoGluAlCs) and allicin is studied. The diversity of the accessions for number of leaves per plant, the pseudostem length, dry weight of bulb, weight of one clove, weight of one bulb, bulb diameter, number of cloves in one bulb, the yield and number of days to dormancy release, is assessed. Particular correlations related to the yield and to the organo-sulphur compounds were demonstrated. Genetic diversity was assessed between and within accessions using statistical analyses including coefficients of variation, one way analysis of variance, hierarchical cluster analysis (HCA) and principal component analysis (PCA).Significant agro-morphological traits and organo-sulphur contents variations were found between accessions, except for the number of days for dormancy release (DDR). There is no correlation between total measured organo-sulphur compounds and any of the agro-morphological characteristics. The yield is highly influenced by the following characteristics: weight of the clove, the weight and the diameter of the bulb, the number of leaves per plant and the stem length. Total variance was well described by the first three PCA axes which represent 80.57% of the variance. The PCA and HCA distinguished two major groups of garlic. Clustering does not correspond to the geographical origin but it distinguishes clearly between coloured and light coloured accessions.

Composition, species diversity, and biomass of the herbaceous community in dry tropical forest of northern India in relation to soil moisture and light intensity

Herb layer contributes substantially to the species diversity of forests and responds relatively quickly to changes in the environment. The objectives of the present study were to understand the relationships among tree canopy cover, soil moisture, light intensity, herbaceous diversity and biomass in a dry tropical forest of India. For this, 20 locations equally distributed in four sites were selected. Four quadrats, each 1 9 1 m in size, were ran- domly placed for sampling at each location. For each quadrat, tree canopy cover, incident light, soil moisture, herbaceous diversity, and biomass were determined. Results indicated that the selected locations differed in terms of tree canopy cover, soil moisture, light intensity, herbaceous diversity, and biomass. Principal component analysis (PCA), using importance value indices of the component species yielded four groups corresponding to the four communities. PCA axes were related to the tree canopy cover, light intensity, and soil moisture and sug- gested that these variables had a profound effect on the organization and determination of herbaceous floristic composition and diversity. Positive relationships of tree canopy cover with soil moisture, herbaceous diversity and biomass, and those of soil moisture with herbaceous diversity and biomass suggested that the tree canopies facilitated the herbaceous communities by modifying environmental conditions that ultimately improved the diversity and production. Further, the study showed a linear relationship of herbaceous diversity with biomass, indi- cating the importance of species diversity for generating primary production in forest herbs.

Leaf nitrogen and phosphorus stoichiometry of Quercus species across China

Leaf stoichiometry patterns and their controlling factors at different scales, such as the global flora or single species/genus, are still poorly understood. Here, we analyzed a national-level dataset of leaf nitrogen (N) and phosphorus (P) concentrations and their stoichiometry for 13 Quercus species from 41 study sites in China, aiming to document the patterns of leaf N and P concentrations and N:P ratio to investigate how these patterns vary with geographic and climatic variables. The averages of leaf N and P concentrations and N:P ratio were 17.27mgg−1, 1.54mgg−1 and 13.96, respectively, across all Quercus species studied. Significant differences in leaf N and P concentrations were detected, while no significant difference in leaf N:P ratio was found among species. Leaf N and P concentrations and N:P ratio showed single-peak curves or linear patterns along the geographic and climatic gradients. Principal component analysis (PCA) revealed that the first PCA axis, which reflected the temperature and evaporation variations along the altitude and longitude, had good relationships with leaf N and P concentrations and N:P ratio. The second PCA axis, which reflected temperature and moisture variations along the latitude, only showed a significantly correlation with leaf N concentration. Leaf N:P ratio was well constrained to a relatively stable range for Quercus species and was less influenced by environmental variables. Leaf N and P concentrations were mainly driven by heat and water distribution induced through geographic variations. Leaf stoichiometry-geography relationships are more complicated than stoichiometry-climate relationships.

Disentangling the role of edaphic variability, flooding regime and topography of Amazonian white‐sand vegetation

AbstractQuestionHow much variation in plant community structure and composition can be predicted using soil, flooding and topography in white‐sand vegetation of northern Amazonia?LocationBrazil, northern Amazon, Roraima State, Viruá National Park (01°46′34″ N, 61°02′06″ W).MethodsData from 17, 1‐ha permanent plots distributed across a 25 km2 landscape within the Viruá National Park, northern Amazonia, was used to assess the soil, flooding and topography effects on tree species composition, diversity and structure. Our analyses were based on 16 599 trees (DBH ≥ 1 cm) belonging to 303 species. Principal components analysis (PCA) was used to reduce the dimensionality of soil variables, whereas dimensionality of floristic composition assemblage was reduced using non‐metric multidimensional scaling (NMDS). Multiple regression analysis was used to test combined effects of soil, flooding and topography on floristic composition, diversity, basal area and tree density.ResultsDepending on the diameter class or the type of data (qualitative or quantitative), NMDS axis 1 explained 45–84% of total variation in species composition among plots. The first and second axes from PCA explained, respectively, 54.8% and 15.1% of the variation related to soil gradients. Soil texture and fertility (PCA axis 1) were the most important predictors of the variation in tree composition, diversity and structure for the three different size classes analysed (DBH ≥ 1 cm, 1 cm ≤ DBH ≤ 9.9 cm and DBH ≥ 10 cm). Overall, plots on more fertile clayey soils showed higher tree diversity and basal area than those on well‐drained sandy soils. Although flooding had little effect on the tree community, the water level was higher in high‐stature forests established on more clayey and fertile soils.ConclusionsEven though soils in the study area are predominantly sandy and oligotrophic, our findings highlight the importance of soil in structuring plant communities of seasonally flooded white‐sand vegetation at mesoscales in the Amazon Basin.

Invertebrates associated to Eichhornea azurea Kunth in a lagoon of the Upper Paraná River: composition, community attributes and influence of abiotic factors

AIM: We evaluated the composition and community attributes of invertebrates associated to Eichhornia azurea at Cascalho Lagoon, Upper Paraná River, Mato Grosso do Sul State, Brazil, over a hydrological cycle, as well the possible influence of abiotic factors upon these attributes. METHODS: The samplings were conducted during 2010 in the rainy and dry periods at stands of E. azurea. The attributes evaluated were abundance, richness, diversity, evenness and dominance. The abiotic factors, temperature, dissolved oxygen, pH and turbidity were summarized by a Principal Component Analysis (PCA). In order to verify possible differences between the mean values of the community attributes and the scores of the PCA axis in different periods, we employed null models analysis of variance. The influence of abiotic factors on each attribute was evaluated through Pearson correlations. RESULTS: We captured 3,052 individuals, distributed into 32 taxa, belonging to the phyllum Mollusca, Annelida, Nematoda and Arthropoda. Among the assessed attributes, only abundance and richness varied significantly between periods, with higher values during the rainy period. Chironomidade was dominant in both periods, whereas Notonectidae and Cyclopoida were rare in the rainy, and Bivalve, Decapoda, Haliplidae, Trichoptera and Pyralidae, in the dry period. A temporal distinction was evident only for the PCA axis 1, which represented gradients in temperature, dissolved oxygen and pH. Among the community attributes, only abundance was significant and negatively correlated with this axis. CONCLUSION: We attested that: i) the rainy period should add favorable conditions for invertebrates' higher richness and abundance in this macrophyte; ii) only the later attribute was influenced by limnological gradients.

Habitat selection by small mammals in Brazilian Pampas biome

The use of microhabitats by small mammals was investigated in an area of Pampas in southern Brazil. We used 10 transect lines with 12 live-traps during six fieldwork sessions between June 2009 and April 2010. Sixteen environmental variables measured were summarized by a principal component analysis (PCA). Richness, total abundance and abundance of each species captured were correlated with the first two PCA axes. The environmental variables were also correlated with the small-mammal abundance through a canonical correspondence analysis (CCA). The first axis was related to variables that characterize forest environments, such as canopy cover and number of trees, and the second axis (with which the species richness and abundance were associated) was related to water, arthropods and herbaceous vegetation. The CCA and PCA showed a significant effect of microhabitat variables on species occurrence. In view of the great variability of environments in the study area and the correlation of the species with the environment variables measured, the degree of heterogeneity seemed to be an important factor associated with the small-mammal variation among microhabitats.

Geomorphic Determinants of Species Composition of Alpine Tundra, Glacier National Park, U.S.A.

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

Adaptation of interval PCA to symbolic histogram variables

This paper is an adaptation of symbolic interval Principal Component Analysis (PCA) to histogram data. We proposed two methodologies. The first one involved three steps: the coding of bins of histogram, the ordinary PCA of means of variables and the representation of dispersion of symbolic observations we call concepts. For the representation of dispersion of these concepts we proposed the transformation of histograms into intervals. Then, we suggest the projection of the hypercubes or the interval lengths associated to each concept on the principal axes of the ordinary PCA of means. In the second methodology, we proposed the use of the three previous steps with the angular transformation.

Leaf element concentrations of terrestrial plants across China are influenced by taxonomy and the environment

ABSTRACTAim The productivity, functioning and biogeochemical cycles of terrestrial ecosystems are strongly affected by leaf element concentrations. Understanding the biological and ecological factors affecting leaf element concentrations is therefore important for modelling the productivity and nutrient fluxes of ecosystems and their responses to global change. The present study aimed to determine how leaf element concentrations are linked to taxonomy and the environment.Location China.Methods The concentrations of 10 leaf elements of 702 terrestrial plant species from different biomes were extracted from publications. The links between environmental variables, taxonomy and leaf elements were analyzed using phylogenetically comparative methods and partial Mantel tests.Results Taxonomy had stronger effects on leaf S and SiO2 than latitude, explaining 40.2–43.9% of total variation, whereas latitude had stronger effects on leaf N, P, K, Fe, Al, Mn, Na and Ca concentrations, explaining 19.5–52.1% of total variation. Leaf N, S, Al, Fe and Na concentrations were correlated with mean annual precipitation (MAP), while leaf N, P and Fe concentrations were correlated with mean annual temperature (MAT). Latitude, MAP and MAT were significantly correlated with the first axis of a principal components analysis (PCA). This first axis was associated with leaf elements involved in protein synthesis and photosynthesis. The other PCA axes, which were not correlated with MAT, latitude and MAP, were associated with leaf elements responsible for cell structure and enzymes.Main conclusions Leaf element concentrations of terrestrial plants in China were correlated with climate, latitude and taxonomy. With the exception of S and SiO2, the environmental factors were more important in explaining leaf element variation than taxonomy. Therefore, changes in temperature and precipitation will directly affect the spatial patterns of leaf elements and thus the associated nutrient fluxes and ecosystem functioning.

ANALYSIS OF PIG PROFILES ON SMALL-SCALE PIG FARMERS IN MANOKWARI-WEST PAPUA

This study was aimed to determine the profiles of pig farming systems. Participatory situationanalysis was employed to gain data relating to pig profiles in the urban and rural areas of Manokwari.Due to the interests of combining many correlated data, multivariate analysis using Principal ComponentAnalysis (PCA) was performed. Cluster Analysis using Agglomerative Hierarchical Clustering wasapplied for analysis of merge samples based on similarity in components’ composition across sites.There were various twelve classes of pig profiles in Manokwari. In principal component of the first axiscorrelation of several components shows strong positive relation e.g. in piglets, sows, and total herd size.Status of region in the first axis of PCA (P1) through which pigs were raised had negative correlation,including grower, household member and pig production. In the second axis (P2), negative correlationswere shown in piglets, grower, boars, total herd size and the Pig Production Potential (PPP). Status ofregion has underpinned profiles of pigs. Several farmers were able to manage their farm continuity in asteady composition. Selling pigs was the main aim and few farmers play a role as pure breeder.

Diversity and distribution of chironomids (Diptera, Chironomidae) in pristine Alpine and pre-Alpine springs (Northern Italy)

The diversity and distribution of chironomids (Diptera, Chironomidae) were studied in relation to environmental factors in 81 springs under pristine conditions in the Italian Prealps and Alps (Trentino and Veneto, NE-Italy, 46°N, 10-11°E). Each spring was surveyed once, between May and November, in 2005 or in 2007-2008, within 50 m of the spring's source (eucrenal). A total of 173 macroinvertebrate samples were collected, in which 26,871 chironomids (including larvae, pupae, pupal exuviae and adults) were counted. Five subfamilies (Tanypodinae, Diamesinae, Prodiamesinae, Orthocladiinae and Chironominae), 54 genera and 104 species/groups of species were identified. As expected, Orthocladiinae accounted for a large part of specimens (82%), followed by Diamesinae (10%), Chironominae Tanytarsini (6%) and Tanypodinae (2%). Together the Chironominae Chironomini and Prodiamesinae contributed less than 0.05% of the fauna. Larvae represented 97.5% of specimens, mostly juveniles (62.6%). Maximum richness and diversity occurred at intermediate altitudes (ca 900-2100 m a.s.l.). Most taxa were found in a small proportion of sites, and frequencies declined gradually for more widely distributed species. A high number (67%) of rare (= present in less than 10% of sites) taxa were found. Three to 27 taxa were identified per spring. The rheocrene/rheo-helocrene springs were richest in taxa (generally &gt;15 taxa), the mineral spring was poorest, with only three taxa. Most taxa were crenophilous, including lentic, rheobiontic and bryophilous taxa. A Principal Component Analysis (PCA) was performed including 98 taxa. Axes were interpreted calculating the correlation coefficients between site scores and 24 environmental factors. The species with the highest scores were Pseudokiefferiella parva, Corynoneura sp. A, Metriocnemus eurynotus gr., Paratrichocladius skirwithensis and Tvetenia calvescens. Five clusters of sites were identified with K-means analysis on the basis of the first and second PCA axes and a Discriminant Analysis was used to detect environmental factors discriminating the clusters: altitude, canopy cover, hydrological regime, pH, and granulometry as percentage of cobbles and stones. The highly individual nature of springs was highlighted; within the same river basin, between springs and within a single spring. These results suggest that prudent and conservative land management should assume that all springs sheltering such unique faunal assemblages need protection.

Profitability of dairy farming in relation to the type of feeding system

Profitability of dairy farming in relation to the type of feeding systemWe investigated the profitability of dairy farms in relation to the type of feeding system (seasonal pasture vs. permanent housing). An economic analysis was carried out of data on the structure and financial health of 50 farms in 2007 using questionnaires filled in by the farmers. The Principal Component Analysis (PCA) was applied to reveal causal relationships between a number of characteristics of the farms. The two axis of PCA explained 40.48% and 16.13% of the variability among the selected farm characteristics. Profitability related more to the number of subsidies, the area of arable land, the number of livestock and to the milk and plant production than to the area of meadows and pastures. Although a better cow performance was achieved on farms with confined herds, the profit per agricultural area and profit rate did not differ significantly between the two feeding strategies (P&gt;0.05). The profit was 3,259 and 3,655 CZK/ha on average and the profit rate 7.9% and 5.6% on average on farms with pastured herds and on farms with confined herds, respectively. A lowering of input costs and a more effective utilisation of grasslands may further enhance profitability.

Modern and pre-Industrial Age distributions of Cladocera in Italian and Swiss Alpine lakes

We compared contemporary and pre-Industrial Age (before 1850 AD) fossil assemblages of Cladocera in sediment cores from 25 lakes in the Italian and Swiss Alps to investigate the impact of mounting anthropogenic stresses over the last 150 years on community composition. In addition, we sought relationships between specific species and their environments by measuring nutrients, major ions, pH, alkalinity, conductivity, chlorophyll, and lake and catchment morphological features at the time of core collection for comparison with surface sediment fossil assemblages. The modern (surface sediment) communities of the study lakes consisted mainly of benthic chydorids, primarily Alona affinis, A. quadrangularis, Acroperus harpae, and Chydorus sphaericus-type, with Daphnia as the sole planktonic genus. Principal component analysis (PCA), relating the modern Cladocera assemblages to environmental variables at the time of sampling, indicated that A. affinis and A. quadrangularis are influenced by altitude and dissolved inorganic nitrogen (PCA axis 1) whereas Acroperus harpae and C. sphaericus-type are more influenced by potassium (PCA axis 2). Redundancy analysis, however, identified lake water pH and potassium as the measured variables most impacting modern cladoceran assemblages, and especially the distribution of C. sphaericus-type and A. harpae. Pre-Industrial Age samples contained more Daphnia (longispina-type primarily) than modern samples, and some harbored Eurycercus lamellatus, which has since been extirpated from these lakes. The directional shifts in Cladocera assemblages from the pre-industrial period to the present, illustrated as changes in the sample scores along the PCA axes 1 and 2, were associated with the secondary PCA gradient in almost all lakes, and thus were probably the indirect responses to a cascade of limnological alterations, perhaps initiated by large anthropogenic forcing factors such as atmospheric pollution or fish introductions.