Genetic differentiation amongst fragrant orchids (Gymnadenia conopsea s.l.) in the British Isles

Genetic variation was examined in five microsatellite loci to seek evidence of genetic differentiation and restricted gene flow that would support the taxonomic division of Gymnadenia into three species ( G. borealis , G. conopsea , and G. densiflora ). A total of 107 alleles was detected in 17 populations from England, Scotland, and Ireland. The mean expected heterozygosities ranged from 0.48 to 0.81. The differentiation in allele frequencies amongst populations that had been assigned to each taxon on the basis of morphology was sufficiently large to support the taxa as distinct species. Phylogenetic trees based on microsatellite allele frequencies, as well as assignment tests, supported the existence of three distinct groups with at least partial restriction of gene flow between them. There was substantial homozygote excess, leading to high F _IS estimates, for most loci in most populations. This is unlikely to have been a result of widespread null alleles, and more probably reflects a high level of inbreeding in G. conopsea . This inference requires further investigation. The implications of the results of this and other taxonomic studies for the conservation of Gymnadenia in Britain are discussed.  © 2007 The Linnean Society of London, Botanical Journal of the Linnean Society , 2007, 155 , 349–360.     

Using species accumulation curves to estimate trapping effort in fauna surveys and species richness

Abstract The shape of species accumulation curves is influenced by the relative abundance and diversity of the fauna being sampled, and the order in which individuals are caught. We use resampling to show the variation in species accumulation curves caused by the order of trapping periods. Averaged species accumulation curves calculated by randomly assigning the order of trapping periods are smooth curves that are a better estimate of species richness and a more useful tool for determining the trapping effort required to adequately survey a site. We extend this concept of randomly resampling the trapping period to show that randomizing the number of individuals caught for each species over the number of collection periods (e.g. days) can provide an accurate estimate of the averaged species accumulation curve. This is particularly useful as it enables an accurate estimation of the proportion of the total number of species caught in an area during a survey from information on the number of individuals caught for each species and the number of trapping periods, and is not dependent on having knowledge of the trapping period in which each individual was caught. This calculation also enables an assessment to be made of the adequacy of fauna surveys to report a species inventory in environmental impact assessments when only a species list and relative abundance data are provided.     

Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

In this study we examined ecosystem respiration (R_ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R_ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R_ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R_ECO. The maximum seasonal leaf area index (LAI_MAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T_ref=15 °C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r²=0.52, P<0.001, n=104) even within each PFT. Besides LAI_MAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N_depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI_MAX) which performed well in predicting the spatio‐temporal variability of R_ECO, explaining >70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.     

Relationships between phenology,radiation and precipitation in the Amazon region

In tropical areas, Dynamic Global Vegetation Models (DGVMs) still have deficiencies in simulating the timing of vegetation phenology. To start addressing this problem, standard Fourier‐based methods are applied to aerosol screened monthly remotely sensed phenology time series (Enhanced Vegetation Index, EVI) and two major driving factors of phenology: solar radiation and precipitation (for March 2000 through December 2006 over northern South America). At 1 × 1 km scale using, power (or variance) spectra on good quality aerosol screened time series, annual cycles in EVI are detected across 58.24% of the study area, the strongest (largest amplitude) occurring in the savanna. Terra Firme forest have weak but significant annual cycles in comparison with savannas because of the heterogeneity of vegetation and nonsynchronous phenological events within 1 × 1 km scale pixels. Significant annual cycles for radiation and precipitation account for 86% and 90% of the region, respectively, with different spatial patterns to phenology. Cross‐spectral analysis was used to compare separately radiation with phenology/EVI, precipitation with phenology/EVI and radiation with precipitation. Overall the majority of the Terra Firme forest appears to have radiation as the driver of phenology (either radiation is in phase or leading phenology/EVI at the annual scale). These results are in agreement with previous research, although in Acre, central and eastern Peru and northern Bolivia there is a coexistence of ‘in phase’ precipitation over Terra Firme forest. In contrast in most areas of savanna precipitation appears to be a driver and savanna areas experiencing an inverse (antiphase) relationship between radiation and phenology is consistent with inhibited grassland growth due to soil moisture limitation. The resulting maps provide a better spatial understanding of phenology–driver relationships offering a bench mark to parameterize ecological models.