Ruppeiner Geometry of RN Black Holes: Flat or Curved?

In some recent studies \cite{aman1, aman2, aman3}, Aman {\it et al.} used the Ruppeiner scalar as a measure of underlying interactions of Reissner-Nordstr\"{o}m black holes, indicating that it is a non-interacting statistical system for which classical thermodynamics could be used at any scale. Here, we show that if we use the complete set of thermodynamic variables, a non-flat state space will be produced. Furthermore, the Ruppeiner curvature diverges at extremal limits, as it would for other types of black holes.Comment: 9 page

A unified classification of alien species based on the magnitude of their environmental impacts

Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens) can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN) Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact-ranging from Minimal to Massive-with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions. © 2014 Blackburn et al

Impact scheme of the Global Invasive Species Database, implemented by the IUCN Species Survival Commission (SSC) Invasive Species Specialist Group.

<p>The GISD stores detailed information on more than 800 invasive alien species, including on the impacts they cause. The GISD has recently been redesigned, and all information has been re-classified in order to improve the searching functionalities of the database. The schema developed for the revised GISD has allowed all species stored in the database to be coded in respect of the direct mechanisms by which their impacts occur (e.g., predation), and by the outcomes of those impact mechanisms on the environment or on human activities. For example, the grass <i>Imperata cylindrica</i> (Poales: Poaceae) almost doubles litter biomass in invaded locations, which increases potential fuel for fires (impact mechanism coded as flammability, and impact outcome as modification of fire regime). The plant <i>Schinus terebinthifolius</i> (Sapindales: Anacardiaceae) is a bio-fouling agent, forming dense thickets in gullies and river bottoms, with the ultimate effect of changing the hydrology of river streams of invaded freshwater bodies (mechanism coded as bio-fouling, and impact outcome described as modification of hydrology). The insect <i>Adelges piceae</i> (Hemiptera: Adelgidae) releases a toxin causing stress to trees, which eventually die. The impact outcome of <i>A. piceae</i> is described in GISD as damage to forestry, with its mechanism of impact coded as poisoning/toxicity, but it can also be coded as having an environmental impact on plant/animal health, as it has been here. In the table, mechanisms and outcomes are reported in two separate columns, and the three examples of the connections between mechanisms and outcomes are shown. Impact outcomes in the GISD database can be environmental or socio-economic, but our categorisation scheme of species in terms of the magnitudes of their impacts (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001850#pbio-1001850-g002" target="_blank">Figure 2</a>; <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001850#pbio-1001850-t001" target="_blank">Table 1</a>) concerns only the former.</p

Impact criteria for assigning alien species to different categories in the classification scheme (Box 2).

<p>These categories are for species that have been evaluated, have alien populations (i.e., are known to have been introduced outside their native range), and for which there is adequate data to allow classification (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001850#pbio-1001850-g002" target="_blank">Figure 2</a>). Classification follows the general principle outlined in the first row. However, we specifically outlined the different mechanisms through which an alien species can cause impacts in order to help assessors to look at the different aspects and to identify potential research gaps. Numbers next to different impact classes reference the numbering of impacts in the classification of impact mechanisms in the GISD (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001850#pbio-1001850-g001" target="_blank">Figure 1</a>).</p

The different categories in the alien species impact scheme, and the relationship between them.

<p>Descriptions of the categories are provided in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001850#pbio-1001850-box002" target="_blank">Box 2</a>. The CG category is not represented in this diagram as CG taxa may be found in any category.</p