Land degradation and desertification monitoring using a multivariate statistical approach

Land degradation and desertification (LDD) are causing the loss of fertile soils all over the world, depriving more and more people of arable land. In a European context, the most affected areas are found in the Mediterranean zone. The aim of the present study is to develop a monitoring system to identify the dynamic nature of environmental sensitivity of the 73 municipalities of the island of Lesvos (Greece) to LDD. We employ a modification of the widely applied Environmentally Sensitive Area Index (ESAI) with additional case-specific biophysical and socio-economic indices estimated using satellite imagery, field and census data in a Geographical Information System (GIS). The most frequently applied indicator-based system for assessing LDD in the Mediterranean region is the Environmentally Sensitive Area (ESA) framework, mainly due to its simplicity in model building as well as its flexibility in the use of relevant variables as indicators. However, the ESAI model weights all indicators equally, possibly underestimating the importance of some factors and inflating the importance of others. Here, we used multiway data analysis (MDA) to explicitly measure the variance in LDD between 1990 and 2000 for each of the 21 LDD indicators to inform a modified ESAI for the Lesvos dataset. Our results show that the majority of the island is in a critically sensitive environmental state. While LDD in the western part of the island improves in the second period of study, a finding which is consistent with other land degradation studies in the area, at a local scale this region is most sensitive to LDD. On the contrary, other parts of the island perform worse in the year 2000, perhaps due to economic activity in the eastern coastal areas as a result of urban growth, tourism and irrigation (i.e. littoralisation). While a significant correlation between our results and the ESAI was observed for both epochs, it is concluded that our approach may more accurately identify the causative factors influencing LDD by overcoming the methodological constraints of the ESAI procedure. The suggested methodology can be used for identifying sensitive areas where mitigation measures are required and thus provide a management tool for the prioritisation of such measures

Metrics of student dissatisfaction and disagreement: longitudinal explorations of a national survey instrument

This study explores dissatisfaction and neutrality metrics from 12 years of a national-level undergraduate student survey. The notion of dissatisfaction is much less prevalent in the narratives surrounding student survey outcomes, and the underpinning metrics are seldom considered. This is despite an increasingly vociferous debate about ‘value for money’ of higher education and the positioning of students as consumers in a marketised sector. We used machine learning methods to explore over 2.7 million national survey outcomes from 154 institutions to describe year-on-year stability in the survey items that best predicted dissatisfaction and neutrality, together with their similarity to known metric predictors of satisfaction. The widely publicised annual increases in student ‘satisfaction’ are shown to be the result of complex reductions in the proportions of disagreement and neutrality across different survey dimensions. Due to the widespread use of survey metrics in university league tables, we create an anonymised, illustrative table to demonstrate how UK institutional rankings would have differed if dissatisfaction metrics had been the preferred focus for reporting. We conclude by debating the tensions of balancing the provision of valuable information about dissatisfaction, with perpetuating negative impacts that derive from this important subset of the survey population

Using integrated population modelling in conservation monitoring: A case study in the common dormouse (Muscardinus avellanarius)

© 2014, Czech Academy of Sciences. All rights reserved. Integrated Population Modelling (IPMs) is a computational method for estimating population and demographic parameters that can improve precision relative to traditional methods. Here we compare the precision of IPM to traditional mark-recapture analysis to estimate population parameters in the common dormouse (Muscardinus avellanarius). This species is relatively rare across its European range and field estimation of demographic parameters can be challenging, as several parts of the life history are difficult to observe in the field. We develop an IPM model incorporating dormouse nest counts and offspring counts, which is data often recorded as a standard part of dormouse nest box monitoring. We found a significant improvement in precision in the estimation of demographic parameters using IPM compared to standard mark-recapture estimation. We discuss our results in the context of common dormouse conservation monitoring

Spatial and seasonal variation in abundance within an insular grey parrot population

© 2017 John Wiley & Sons Ltd. Populations of Psittacidae are endangered by habitat loss and the international pet market. The grey parrot (Psittacus erithacus) is among the most traded species, yet little is known about densities and their variability in time and space. The population of grey parrots on the island of Príncipe (Gulf of Guinea) was estimated with distance sampling, in both pre- and postbreeding seasons. Abundance was related to a range of habitat features using generalized additive models. Densities averaged 48 ± 3 (SE) individuals km-2 in the prebreeding and 59 ± 4 in the postbreeding season, both extremely high compared to elsewhere in Africa and to other parrot species. Despite a population of 6000-8000 individuals over only 139 km2, parrots were patchily distributed, being unrecorded in ~25% of surveyed areas. Abundance varied seasonally, with densities being significantly higher in secondary compared to primary forest in the post- but not in the prebreeding season. Abundance was most tied to the presence of nest-tree species prior to breeding and to feeding-tree species and lightly sloping ground after breeding. These results highlight the need to preserve a matrix of habitat types to provide resources for parrots across seasons and ensure that surveys recognize seasonality in habitat use as a potential bias

Trapping method and quota observance are pivotal to population stability in a harvested parrot

Wildlife trade is currently regulated mainly in terms of ‘volume’, i.e. the number of individuals taken from the wild or numbers appearing on the market in a given year. To explore the possible effects of other factors such as capture methods, variability in annual harvest, and habitat, we built and validated a demographic model for a closed population of Grey Parrots Psittacus erithacus on Príncipe, and ran 50-year simulations for the population under different harvest scenarios. There was a fine line between capture volumes being robustly sustainable (11% harvested) and dramatically unsustainable (15%). Population trajectories were highly sensitive to changes in adult survivorship, such that the inclusion of even a small number of adults among the harvest had a far greater impact than a similar number of juveniles. High annual variation in capture rate (reflecting poor national management of trade) could make the difference between sustainability and non-sustainability if quotas were set around critical harvest volumes. While these patterns may be common to large traded parrots generally, sufficient habitat and secure nest sites exist on Príncipe to render the effects of habitat loss on the island less important than in most other situations. If trade in parrots is to continue sustainably it will require reliable demographic and harvest data and must eliminate instability in quota observance (exceeded quotas are not compensated by shortfalls in other years) and, especially, the indiscriminate capture of adults

The Hubble Constant from Observations of the Brightest Red Giant Stars in a Virgo-Cluster Galaxy

The Virgo and Fornax clusters of galaxies play central roles in determining the Hubble constant H_0. A powerful and direct way of establishing distances for elliptical galaxies is to use the luminosities of the brightest red-giant stars (the TRGB luminosity, at M_I = -4.2). Here we report the direct observation of the TRGB stars in a dwarf elliptical galaxy in the Virgo cluster. We find its distance to be 15.7 +- 1.5 Megaparsecs, from which we estimate a Hubble constant of H_0 = 77 +- 8 km/s/Mpc. Under the assumption of a low-density Universe with the simplest cosmology, the age of the Universe is no more than 12-13 billion years.Comment: 12 pages, LaTeX, with 2 postscript figures; in press for Nature, July 199

Benchmarking factor selection and sensitivity: a case study with nursing courses

There is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking is widely used for this purpose, but methodological approaches to the creation of benchmark metrics vary greatly. Approaches require selection of factors for inclusion and subsequent calculation of benchmarks for comparison. We describe an approach using machine learning to select input factors based on their value to predict completion rates of nursing courses. Data from over 36,000 students, from nine institutions over three years were included and weighted averages provided a dynamic baseline for year on year and within year comparisons between institutions. Anonymised outcomes highlight the variation in benchmarked performances between institutions and we demonstrate the value of accompanying sensitivity analyses. Our methods are appropriate worldwide, for many forms of data and at multiple scales of enquiry. We discuss our results in the context of HE management, highlighting the value of scrutinising benchmark calculations