Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade-off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be "poor" and 61% to show a degree of reliability split between "moderate" (30%), "good" (25%), and "excellent" (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold-out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd-sourcing further assessments by allowing web-based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.

Eriocaulaceae in the Brazilian Amazon and the use of Species Distribution Modelling in its conservation

Abstract Following a survey in herbaria in Brazil and abroad, complemented by a survey of the literature and searches of biodiversity data, 66 taxa of Eriocaulaceae have been identified in the Brazilian Amazon, as defined by the states of Acre, Amapá, Amazonas, Pará, Rondônia and Roraima. Six genera of Eriocaulaceae were found in the Amazon with the following taxon numbers: Comanthera (3 taxa), Eriocaulon (10), Paepalanthus (15), Rondonanthus (2), Syngonanthus (35) and Tonina (1). Of this total, 25 taxa present distributions in the states of the Amazon and other Brazilian states (considered as widely distributed) and the remaining 41 taxa are restricted to the Amazon Rainforest biome. The distribution data for 31 species were used for Species Distribution Modelling, due to the low number of occurrence points reported for the other taxa, 17 of those are known from a single location. The overlap of these models indicates areas from Amapá, Amazonas, Pará and Roraima where modelled species are most likely to occur. These data can further contribute to the location of new populations of species of Eriocaulaceae. New detection of Eriocaulaceae species can assist in filling the gaps on their geographic distribution and ecology, contributing to the protection or restoration of priority areas set aside for their conservation.

Using Qualitative and Quantitative Methods to Choose a Habitat Quality Metric for Air Pollution Policy Evaluation

Atmospheric nitrogen (N) deposition has had detrimental effects on species composition in a range of sensitive habitats, although N deposition can also increase agricultural productivity and carbon storage, and favours a few species considered of importance for conservation. Conservation targets are multiple, and increasingly incorporate services derived from nature as well as concepts of intrinsic value. Priorities vary. How then should changes in a set of species caused by drivers such as N deposition be assessed? We used a novel combination of qualitative semi-structured interviews and quantitative ranking to elucidate the views of conservation professionals specialising in grasslands, heathlands and mires. Although conservation management goals are varied, terrestrial habitat quality is mainly assessed by these specialists on the basis of plant species, since these are readily observed. The presence and abundance of plant species that are scarce, or have important functional roles, emerged as important criteria for judging overall habitat quality. However, species defined as 'positive indicator-species' (not particularly scarce, but distinctive for the habitat) were considered particularly important. Scarce species are by definition not always found, and the presence of functionally important species is not a sufficient indicator of site quality. Habitat quality as assessed by the key informants was rank-correlated with the number of positive indicator-species present at a site for seven of the nine habitat classes assessed. Other metrics such as species-richness or a metric of scarcity were inconsistently or not correlated with the specialists' assessments. We recommend that metrics of habitat quality used to assess N pollution impacts are based on the occurrence of, or habitat-suitability for, distinctive species. Metrics of this type are likely to be widely applicable for assessing habitat change in response to different drivers. The novel combined qualitative and quantitative approach taken to elucidate the priorities of conservation professionals could be usefully applied in other contexts.