Developing and enhancing biodiversity monitoring programmes: a collaborative assessment of priorities

1.Biodiversity is changing at unprecedented rates, and it is increasingly important that these changes are quantified through monitoring programmes. Previous recommendations for developing or enhancing these programmes focus either on the end goals, that is the intended use of the data, or on how these goals are achieved, for example through volunteer involvement in citizen science, but not both. These recommendations are rarely prioritized. 2.We used a collaborative approach, involving 52 experts in biodiversity monitoring in the UK, to develop a list of attributes of relevance to any biodiversity monitoring programme and to order these attributes by their priority. We also ranked the attributes according to their importance in monitoring biodiversity in the UK. Experts involved included data users, funders, programme organizers and participants in data collection. They covered expertise in a wide range of taxa. 3.We developed a final list of 25 attributes of biodiversity monitoring schemes, ordered from the most elemental (those essential for monitoring schemes; e.g. articulate the objectives and gain sufficient participants) to the most aspirational (e.g. electronic data capture in the field, reporting change annually). This ordered list is a practical framework which can be used to support the development of monitoring programmes. 4.People's ranking of attributes revealed a difference between those who considered attributes with benefits to end users to be most important (e.g. people from governmental organizations) and those who considered attributes with greatest benefit to participants to be most important (e.g. people involved with volunteer biological recording schemes). This reveals a distinction between focussing on aims and the pragmatism in achieving those aims. 5.Synthesis and applications. The ordered list of attributes developed in this study will assist in prioritizing resources to develop biodiversity monitoring programmes (including citizen science). The potential conflict between end users of data and participants in data collection that we discovered should be addressed by involving the diversity of stakeholders at all stages of programme development. This will maximize the chance of successfully achieving the goals of biodiversity monitoring programmes

Evolution of the velocity-dispersion function of luminous red galaxies: a hierarchical Bayesian measurement

We present a hierarchical Bayesian determination of the velocity-dispersion function of approximately 430,000 massive luminous red galaxies observed at relatively low spectroscopic signal-to-noise ratio (S/N ~ 3–5 per 69 km s−1) by the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. We marginalize over spectroscopic redshift errors, and use the full velocity-dispersion likelihood function for each galaxy to make a self-consistent determination of the velocity-dispersion distribution parameters as a function of absolute magnitude and redshift, correcting as well for the effects of broadband magnitude errors on our binning. Parameterizing the distribution at each point in the luminosity–redshift plane with a log-normal form, we detect significant evolution in the width of the distribution toward higher intrinsic scatter at higher redshifts. Using a subset of deep re-observations of BOSS galaxies, we demonstrate that our distribution-parameter estimates are unbiased regardless of spectroscopic S/N. We also show through simulation that our method introduces no systematic parameter bias with redshift. We highlight the advantage of the hierarchical Bayesian method over frequentist “stacking” of spectra, and illustrate how our measured distribution parameters can be adopted as informative priors for velocity-dispersion measurements from individual noisy spectra

The UV-Optical Color Dependence of Galaxy Clustering in the Local Universe

We measure the UV-optical color dependence of galaxy clustering in the local universe. Using the clean separation of the red and blue sequences made possible by the NUV - r color-magnitude diagram, we segregate the galaxies into red, blue and intermediate "green" classes. We explore the clustering as a function of this segregation by removing the dependence on luminosity and by excluding edge-on galaxies as a means of a non-model dependent veto of highly extincted galaxies. We find that \xi (r_p, \pi) for both red and green galaxies shows strong redshift space distortion on small scales -- the "finger-of-God" effect, with green galaxies having a lower amplitude than is seen for the red sequence, and the blue sequence showing almost no distortion. On large scales, \xi (r_p, \pi) for all three samples show the effect of large-scale streaming from coherent infall. On scales 1 Mpc/h < r_p < 10 Mpc/h, the projected auto-correlation function w_p(r_p) for red and green galaxies fits a power-law with slope \gamma ~ 1.93 and amplitude r_0 ~ 7.5 and 5.3, compared with \gamma ~ 1.75 and r_0 ~ 3.9 Mpc/h for blue sequence galaxies. Compared to the clustering of a fiducial L* galaxy, the red, green, and blue have a relative bias of 1.5, 1.1, and 0.9 respectively. The w_p(r_p) for blue galaxies display an increase in convexity at ~ 1 Mpc/h, with an excess of large scale clustering. Our results suggest that the majority of blue galaxies are likely central galaxies in less massive halos, while red and green galaxies have larger satellite fractions, and preferentially reside in virialized structures. If blue sequence galaxies migrate to the red sequence via processes like mergers or quenching that take them through the green valley, such a transformation may be accompanied by a change in environment in addition to any change in luminosity and color.Comment: accepted by MNRA

The Ks-band Tully-Fisher Relation - A Determination of the Hubble Parameter from 218 ScI Galaxies and 16 Galaxy Clusters

The value of the Hubble Parameter (H0) is determined using the morphologically type dependent Ks-band Tully-Fisher Relation (K-TFR). The slope and zero point are determined using 36 calibrator galaxies with ScI morphology. Calibration distances are adopted from direct Cepheid distances, and group or companion distances derived with the Surface Brightness Fluctuation Method or Type Ia Supernova. Distances are determined to 16 galaxy clusters and 218 ScI galaxies with minimum distances of 40.0 Mpc. From the 16 galaxy clusters a weighted mean Hubble Parameter of H0=84.2 +/-6 km s-1 Mpc-1 is found. From the 218 ScI galaxies a Hubble Parameter of H0=83.4 +/-8 km s-1 Mpc-1 is found. When the zero point of the K-TFR is corrected to account for recent results that find a Large Magellanic Cloud distance modulus of 18.39 +/-0.05 a Hubble Parameter of 88.0 +/-6 km s-1 Mpc-1 is found. A comparison with the results of the Hubble Key Project (Freedman et al 2001) is made and discrepancies between the K-TFR distances and the HKP I-TFR distances are discussed. Implications for Lamda-CDM cosmology are considered with H0=84 km s-1 Mpc-1. (Abridged)Comment: 37 pages including 12 tables and 7 figures. Final version accepted for publication in the Journal of Astrophysics & Astronom

Controls on primary production in Lake Naivasha, a shallow tropical freshwater

This study uses Lake Naivasha, Kenya as an example of a shallow tropical freshwater lake. In common with many tropical lakes it experiences fluctuating water-levels which influence its area and productivity, and is currently considered moderately eutrophic.;The light regime experienced by phytoplankton in Lake Naivasha dominates other controls as it determines the potential level of primary production. Photoinhibition reduces productivity by 25% at the surface with maximum productivity at a depth of approximately 0.5m. Light attenuation reduces productivity by 50% at 1m depth with zero productivity at 5m depth. Self-shading causes a 17% loss of productivity under conditions of below average productivity, but a 46% loss when productivity is above average. Hydrological factors form a primary control as the mixing regime determines the light regime. Lake Naivasha is generally well mixed, but where temporary stratification occurs there is nutrient resupply due to sediment anoxia. Without mixing, there is a 75% loss of productivity by cell sedimentation. Low sinking rates, tropical conditions and high nutrient availability favour low Surface Area:Volume species such as Aulacoseira which is the dominant genus. Changing conditions such as increased water-column stability could favour cyanobacteria.;Bottom-up controls were the most important in Lake Naivasha, reducing potential productivity by 50%. Nitrogen was found to be more limiting than phosphorus with an algal preference for ammonium over nitrate. Minor nutrients were not limiting. The main source of allochthonous nutrients was from river inflow with underflow and circulations around the lake. Top-down control by grazing imposes a 15% reduction in productivity with zooplankton preferring large 'production' cells over small 'standing-stock' cells