Sampling effort and information quality provided by rare and common species in estimating assemblage structure

Reliable biological assessments are essential to answer ecological and management questions but require well-designed studies and representative sample sizes. However, large sampling effort is rarely possible, because it demands large financial resources and time, restricting the number of sites sampled, the duration of the study and the sampling effort at each site. In this context, we need methods and protocols allowing cost-effective surveys that would, consequently, increase the knowledge about how biodiversity is distributed in space and time. Here, we assessed the minimal sampling effort required to correctly estimate the assemblage structure of stream insects sampled in near-pristine boreal and subtropical regions. We used five methods grouped into two different approaches. The first approach consisted of the removal of individuals 1) randomly or 2) based on a count threshold. The second approach consisted of simplification in terms of 1) sequential removal from rare to common species; 2) sequential removal from common to rare species; and 3) random species removal. The reliability of the methods was assessed using Procrustes analysis, which indicated the correlation between a reduced matrix (after removal of individuals or species) and the complete matrix. In many cases, we found a strong relationship between ordination patterns derived from presence/absence data (the extreme count threshold of a single individual) and those patterns derived from abundance data. Also, major multivariate patterns derived from the complete data matrices were retained even after the random removal of more than half of the individuals. Procrustes correlation was generally high ( > 0.8), even with the removal of 50% of the species. Removal of common species produced lower correlation than removal of rare species, indicating higher importance of the former to estimate resemblance between assemblages. Thus, we conclude that sampling designs can be optimized by reducing the sampling effort at a site. We recommend that such efforts saved should be redirected to increase the number of sites studied and the duration of the studies, which is essential to encompass larger spatial, temporal and environmental extents, and increase our knowledge of biodiversity.peerReviewe

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low

Data from: You don’t belong here: explaining the excess of rare species in terms of habitat, space and time

Ecological communities are composed of a few common and several rare species. Many studies have evaluated the shape of abundance distribution curves, but few studies have assessed the causes of rarity. Using a dataset of stream macroinvertebrates, we investigated whether the excess of rare species in three focal communities of stones in riffles were common i) in other habitats at the same stream site and period of sampling (Environment), ii) in other stream sites in the same habitat and period of sampling (Space), and iii) in other years in the same stream site and habitat (Time). We observed that around 28% of the rare species were common in other habitats (Environment), stream sites (Space) or years (Time). Among the three factors, rarity was mostly explained by habitat type, whereas a significant portion of the rare species in riffles were common in pools, submerged roots of terrestrial plants or in partially submerged moss patches. This result suggests that the presence in non-optimum habitat is a strong determinant of the rarity observed in natural communities and most rare species are due to sampling artifacts or accidentally sampled transient species

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low

Frontal assessment battery scores and non-motor symptoms in parkinsonian disorders

Using data from the PRIAMO study, we investigated non-motor symptoms (NMS) versus frontal lobe dysfunction in patients with idiopathic Parkinson disease (PD); 808 patients with PD and 118 with atypical parkinsonisms (AP) were consecutively enrolled at 55 Centers in Italy. Twelve categories of NMS were investigated. Cognitive impairment was defined as a Mini-Mental Status Evaluation score B23.8 and frontal lobe dysfunction as a Frontal Assessment Battery (FAB) score B13.48. Multivariable logistic regression was used to identify predictor of frontal lobe dysfunction in 524 PD patients, and a generalized linear model was used for each of the six FAB items. Not only the total FAB scores but also the single FAB items were lower in AP versus PD (p ≤ 0.005). Age (OR = 1.05), cognitive impairment (OR = 9.54), lack of cardiovascular symptoms (OR = 3.25), attention or memory problems (OR = 0.59) and treatment with L-DOPA (OR = 5.58) were predictors of frontal lobe dysfunction. MMSE was negatively associated with all FAB items (≤ B -0.16) and age with all FAB items but prehension On behalf of the PRIAMO study group. behavior (≤ B -0.01). Previous use of L-DOPA was. © 2011 Springer-Verlag. © 2011 Springer-Verlag