Although it is generally recognized that global biodiversity is declining, few studies have examined long-term changes in multiple biodiversity dimensions simultaneously. In this study, we quantified and compared temporal changes in the abundance, taxonomic diversity, functional diversity, and phylogenetic diversity of bird assemblages, using roadside monitoring data of the North American Breeding Bird Survey from 1971 to 2010. We calculated 12 abundance and diversity metrics based on 5-year average abundances of 519 species for each of 768 monitoring routes. We did this for all bird species together as well as for four subgroups based on breeding habitat affinity (grassland, woodland, wetland, and shrubland breeders). The majority of the biodiversity metrics increased or remained constant over the study period, whereas the overall abundance of birds showed a pronounced decrease, primarily driven by declines of the most abundant species. These results highlight how stable or even increasing metrics of taxonomic, functional, or phylogenetic diversity may occur in parallel with substantial losses of individuals. We further found that patterns of change differed among the species subgroups, with both abundance and diversity increasing for woodland birds and decreasing for grassland breeders. The contrasting changes between abundance and diversity and among the breeding habitat groups underscore the relevance of a multifaceted approach to measuring biodiversity change. Our findings further stress the importance of monitoring the overall abundance of individuals in addition to metrics of taxonomic, functional, or phylogenetic diversity, thus confirming the importance of population abundance as an essential biodiversity variable.

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Purpose The purpose of this paper is to test the relationship between earnings quality and the cost of debt for private companies in a “code-law” country (Ball et al., 2000). The analysis controls for company size, debt level and audited information. Design/methodology/approach The paper uses the ordinary least squares regression technique to test the relationship between earnings quality and the cost of debt. Findings The collected empirical evidence shows a negative relationship between earnings quality and the cost of debt and controls for company size and debt level. Such a relationship is stronger when the company information is audited. Research limitations/implications Similar to other studies, this paper has two main limitations. There was no access to specific data on the interest rates charged on bank loans, implying that the cost of debt is measured by the ratio of the interest expense to interest-bearing debt. The research only uses earnings quality measures based on abnormal accruals. Practical implications The collected evidence suggests that earnings quality have economic consequences for private companies by affecting their cost of debt, similar to those observed in previous studies for listed companies. This evidence can be seen as an incentive for private companies to increase their financial information quality. For debt providers, namely, financial institutions, the findings can be of interest to help them price properly the loans they make available to private companies. In general, the findings of this research can be of interest for company managers and financial institutions in countries with an institutional environment similar to that of Portugal. Originality/value The relation between earnings quality and the cost of debt has been so far studied for listed companies in “common law” countries. This paper provides new and complementary evidence about such relation for private companies and “code-law” country.

Aim Our aim was to test whether species richness patterns are best explained by the effect of the total amount of habitat within the landscape, or instead by a combination of patch size and patch isolation effects. To this end, we jointly contrast the habitat amount hypothesis and countryside biogeography with patch size and isolation concepts from island biogeography. Location Three multi‐habitat landscapes in Peneda‐Gerês National Park, NW Portugal. Taxon Macro‐moths (Lepidoptera). Methods Light‐trapping using a semi‐nested design at 84 fixed sites which were each repeatedly sampled six times. Results Autocovariate models show that sampling sites with a higher number of forest and meadow macro‐moth species (alpha diversity) were surrounded by a higher amount of forest and meadow habitat, respectively within a 160 and 320 m radius (scale of effect). These top‐ranked models, containing only habitat amount as a significant variable, had lower Akaike's information criteria (AIC) than models (only) containing patch size and/or isolation. Complementary to this, the countryside species–area relationship (SAR) model outperforms the classic SAR model, so that the effective area of habitat explains landscape species richness (gamma diversity) across spatial scales (beta diversity) better than the classic SAR. Specifically, we show that forest macro‐moths have a higher spatial turnover than meadow macro‐moths and that, on average, there are more species in forest than in meadow habitat. Main conclusions The habitat amount hypothesis predicts alpha species richness in multi‐habitat landscapes better than do patch size and isolation while the countryside SAR predicts beta and gamma diversity better than the classic SAR. We suggest that evidence is mounting to revise the application of the classical approaches of island biogeography and metapopulation theory to conservation biogeography.

Farmland abandonment and the accompanying natural succession are largely perceived as unwanted amongst many European conservationists due to alleged negative effects on biodiversity levels. Here, we test this assumption by analysing alpha, beta and gamma diversity patterns of macro-moth communities in habitats on an ecological succession gradient, from extensively managed meadows to scrub-encroached and wooded sites. Macro-moths were light-trapped at 84 fixed circular sampling sites arranged in a semi-nested design within the National Park of Peneda-Gerês, NW-Portugal. In total, we sampled 22825 individuals belonging to 378 species. Alpha, beta and gamma diversity patterns suggest that farmland abandonment is likely to positively affect both overall macro-moth diversity and forest macro-moth diversity, and to negatively affect species diversity of non-forest macro-moth species. Our results also show that spatial habitat heterogeneity is important to maintain gamma diversity of macro-moths, especially for rare non-forest species and habitat specialists.

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In this article, and in a context of regularly varying tails, we analyze a generalization of the classical Hill estimator of a positive tail index. The members of this general class of estimators are not asymptotically more eficient than the original one, the Hill estimator. We thus propose a class of generalized Jackknife estimators associated with any two members of the first class. They enable the reduction of the main component of bias of the Hill estimator and are dependent of a tuning parameter, which is adequately chosen through an asymptotic variance minimization criterion. These new estimators are compared with the Hill estimator, both asymptotically and for finite samples and, when the underlying distribution is in Hall's class of models, they really improve on the well-known, bias-variance, trade-off characteristic of the Hill estimator.