The ternary diagram of functional diversity

Among the many diversity indices in the ecologist toolbox, measures that can be partitioned into additive terms are particularly useful as the different components can be related to different ecological processes shaping community structure. In this paper, an additive diversity decomposition is proposed to partition the diversity structure of a given community into three complementary fractions: functional diversity, functional redundancy and species dominance. These three components sum up to one. Therefore, they can be used to portray the community structure in a ternary diagram. Since the identification of community-level patterns is an essential step to investigate the main drivers of species coexistence, the ternary diagram of functional diversity can be used to relate different facets of diversity to community assembly processes more exhaustively than looking only at one index at a time. The value of the proposed diversity decomposition is demonstrated by the analysis of actual abundance data on plant assemblages sampled in grazed and ungrazed grasslands in Tuscany (Central Italy)

Using spectral diversity and heterogeneity measures to map habitat mosaics: An example from the Classical Karst

Questions: Can we map complex habitat mosaics from remote-­sensing data? In doing this, are measures of spectral heterogeneity useful to improve image classification performance? Which measures are the most important? How can multitemporal data be integrated in a robust framework? Location: Classical Karst (NE Italy). Methods: First, a habitat map was produced from field surveys. Then, a collection of 12 monthly Sentinel-­2 images was retrieved. Vegetation and spectral heterogeneity (SH) indices were computed and aggregated in four combinations: (1) monthly layers of vegetation and SH indices; (2) seasonal layers of vegetation and SH indices; (3) yearly layers of SH indices computed across the months; and (4) yearly layers of SH indices computed across the seasons. For each combination, a Random Forest clas- sification was performed, first with the complete set of input layers and then with a subset obtained by recursive feature elimination. Training and validation points were independently extracted from field data. Results: The maximum overall accuracy (0.72) was achieved by using seasonally ag- gregated vegetation and SH indices, after the number of vegetation types was re- duced by aggregation from 26 to 11. The use of SH measures significantly increased the overall accuracy of the classification. The spectral β-­diversity was the most im- portant variable in most cases, while the spectral α-­diversity and Rao's Q had a low relative importance, possibly because some habitat patches were small compared to the window used to compute the indices. Conclusions: The results are promising and suggest that image classification frame- works could benefit from the inclusion of SH measures, rarely included before. Habitat mapping in complex landscapes can thus be improved in a cost-­and time-­effective way, suitable for monitoring applications

Insomnia in the Italian Population During Covid-19 Outbreak: A Snapshot on One Major Risk Factor for Depression and Anxiety

Objectives: One of the largest clusters of Covid-19 infections was observed in Italy. The population was forced to home confinement, exposing individuals to increased risk for insomnia, which is, in turn, associated with depression and anxiety. Through a cross-sectional online survey targeting all Italian adult population (≥18 yrs), insomnia prevalence and its interactions with relevant factors were investigated. Methods: The survey was distributed from 1st April to 4th May 2020. We collected information on insomnia severity, depression, anxiety, sleep hygiene behaviors, dysfunctional beliefs about sleep, circadian preference, emotion regulation, cognitive flexibility, perceived stress, health habits, self-report of mental disorders, and variables related to individual difference in life changes due to the pandemic's outbreak. Results: The final sample comprised 1,989 persons (38.4 ± 12.8 yrs). Prevalence of clinical insomnia was 18.6%. Results from multivariable linear regression showed that insomnia severity was associated with poor sleep hygiene behaviors [β = 0.11, 95% CI (0.07–0.14)]; dysfunctional beliefs about sleep [β = 0.09, 95% CI (0.08–0.11)]; self-reported mental disorder [β = 2.51, 95% CI (1.8–3.1)]; anxiety [β = 0.33, 95% CI (0.25–0.42)]; and depression [β = 0.24, 95% CI (0.16–0.32)] symptoms. Conclusion: An alarming high prevalence of clinical insomnia was observed. Results suggest that clinical attention should be devoted to problems of insomnia in the Italian population with respect to both prevention and treatment

The association between diurnal sleep patterns and emotions in infants and toddlers attending nursery

Background: Childcare programs often include mandatory naptime during the day. Loss of daytime sleep could lead to a moderate-to-large decrease in self-regulation, emotion processing, and learning in early childhood. Nevertheless, daytime sleep has been less accurately studied than nighttime sleep. This study aims to explore the relationship between diurnal sleep habits in nursery settings, nocturnal sleep quality, and post-nap emotional intensity in infants and toddlers. Methods: Data of 92 children (52 girls, 40 boys) aged 6 to 36 months were obtained. Sleep habits as well as positive and negative emotions were monitored by educators during nursery times through a sleep and emotion diary for two weeks. Results: Explorative analyses showed that diurnal sleep hours decreased across age groups (except for females aged 25–36 months) and that all age groups had a lower amount of nocturnal sleep than is recommended by the National Sleep Foundation. Partial correlation analysis showed significant correlation between daytime sleep onset latency and positive emotions. Mediation analyses showed that daytime napping is relevant for emotional functioning independently of nocturnal sleep quality. Conclusions: Daytime sleep in early childhood seems to be linked to the management of positive and negative emotions and could play a role in healthy development of emotional processes

A systematic review and network meta-analysis of randomized controlled trials evaluating the evidence base of melatonin, light exposure, exercise, and complementary and alternative medicine for patients with insomnia disorder

Insomnia is a prevalent disorder and it leads to relevant impairment in health-related quality of life. Recent clinical guidelines pointed out that Cognitive-Behavior Therapy for Insomnia (CBT-I) should be considered as first-line intervention. Nevertheless, many other interventions are commonly used by patients or have been proposed as effective for insomnia. These include melatonin, light exposure, exercise, and complementary and alternative medicine. Evaluation of comparable effectiveness of these interventions with first-line intervention for insomnia is however still lacking. We conducted a systematic review and network meta-analysis on the effects of these interventions. PubMed, PsycInfo, PsycArticles, MEDLINE, and CINAHL were systematically searched and 40 studies were included in the systematic review, while 36 were entered into the meta-analysis. Eight network meta-analyses were conducted. Findings support effectiveness of melatonin in improving sleep-onset difficulties and of meditative movement therapies for self-report sleep efficiency and severity of the insomnia disorder. Some support was observed for exercise, hypnotherapy, and transcranial magnetic resonance, but the number of studies for these interventions is still too small. None of the considered interventions received superior evidence to CBT-I, which should be more widely disseminated in primary care

Focusing on the role of abiotic and biotic drivers on cross-taxon congruence

Diversity patterns can show congruence across taxonomic groups. Consistent diversity patterns allow the identification of indicator surrogates potentially representative of unobserved taxa or the broader biodiversity patterns. However, the effective use of biodiversity surrogates depends on underlying mechanisms driving the strength of the relationship among taxonomic groups. Here, we explored congruence patterns in community composition among taxa occupying different trophic levels, accounting for abiotic and biotic factors: vascular plants and six groups of ground-dwelling arthropods (pseudoscorpions, spiders, darkling beetles, rove beetles, ground beetles and ants) were chosen as potential indicator surrogates. We evaluated the cross-taxon relationships using Mantel test; subsequently, we investigated if these relationships could partially depend on abiotic drivers, using partial Mantel tests; then, we evaluated the partial contributions of abiotic and biotic drivers in explaining these relationships through a series of variation partitioning analyses. Our results showed that a consistent cross-taxon congruence pattern was evident across almost all group pairs: pseudoscorpions, spiders, ground beetles and vascular plants showed the largest number of significant correlations with other taxa. Environmental gradients resulted as drivers of cross-taxon congruence, shaping composition patterns. However, they were not the only ones. Biotic drivers account for part of cross-taxon congruence among vascular plants and arthropod predators (i.e., pseudoscorpions and spiders, but also ground beetles), as well as among taxa at high trophic levels. Almost all strictly predatory taxa, known as biological control agents, emerged as the best predictors of plant community composition even when the role of environmental factors was considered. Spiders/ants and spiders/ground beetles showed close relationships and congruent composition patterns, irrespective of environmental parameters. Relationships among taxa might be driven by several complex biotic interactions (e.g., non-trophic and trophic interactions, direct and indirect interactions). Bottom-up and top-down forces, consumptive and non-consumptive interactions may play a role in influencing the community composition of taxa and driving the observed relationships. Future studies should broaden knowledge about the role of these forces and interactions in determining the congruence across taxa. The multi-trophic perspective in cross-taxon studies can be promising for identifying biodiversity surrogates and their application in conservation planning

Effectiveness of different metrics of floristic quality assessment: The simpler, the better?

Vascular plants are good environmental indicators. Thus, floristic inventories have a high potential in environmental management since they reflect the current and past status of the environment. In this study, we used the flora of a suburban riverscape in central Italy to test the performance of the Floristic Quality Assessment (FQA) approach, an expert-based evaluation technique. Ten expert botanists assigned coefficients of conservatism (CC) to 382 plant species. We found statistically significant differences between the values assigned to the inventoried flora by botanical experts. In spite of this, the analysis of pseudo multivariate dissimilarity-based standard errors of CC values assigned by the different experts revealed that, in our case, an assessment by a minimum of five botanists allows characterizing the flora with a stable level of precision. We used the distance from agricultural and urban surfaces as a proxy of anthropogenic disturbance to divide the area around the river in four belts of increasing disturbance. The disturbance gradient was mirrored by median CC values and by the Adjusted Floristic Quality Assessment Index (Adjusted FQAI). Conversely, the Floristic Quality Assessment Index (FQAI), which is based on CC values and on the number of native species, showed increasing values with increasing disturbance. Comparing the performance of median CC values to Ellenberg Indicator Values (EIVs), life forms, and chorotypes, we revealed that the last three indicators may be ineffective in highlighting the conservation status of the environment. We suggest that the use of the median CC values may be a simpler and effective alternative to the calculation of indices in FQA, when the adequacy of the number of experts in minimizing the variability of CC values is a posteriori verified

Cross Taxon Congruence Between Lichens and Vascular Plants in a Riparian Ecosystem

Despite that congruence across taxa has been proved as an effective tool to provide insights into the processes structuring the spatial distribution of taxonomic groups and is useful for conservation purposes, only a few studies on cross-taxon congruence focused on freshwater ecosystems and on the relations among vascular plants and lichens. We hypothesized here that, since vascular plants could be good surrogates of lichens in these ecosystems, it would be possible to assess the overall biodiversity of riparian habitats using plant data only. In this frame, we explored the relationship between (a) species richness and (b) community composition of plants and lichens in a wetland area located in central Italy to (i) assess whether vascular plants are good surrogates of lichens and (ii) to test the congruence of patterns of species richness and composition among plants and lichens along an ecological gradient. The general performance of plant species richness per se, as a biodiversity surrogate of lichens, had poor results. Nonetheless, the congruence in compositional patterns between lichens and vascular plants varied across habitats and was influenced by the characteristics of the vegetation. In general, we discussed how the strength of the studied relationships could be influenced by characteristics of the data (presence/absence vs. abundance), by the spatial scale, and by the features of the habitats. Overall, our data confirm that the more diverse and structurally complex the vegetation is, the more diverse are the lichen communities it hosts

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette

Effects of spatial scales and vegetation types on Observer bias: practical implications for long term monitoring programs

Global changes mainly due to habitat fragmentation and climate variation, are rapidly influencing terrestrial and aquatic ecosystems. Long-term monitoring programs based on periodic reliefs represent important tools to understand ecosystem changes in time and in space. Under this perspective, it is crucial to understand the amount of variation in species inventories due to the observer: in long-term monitoring programs, it is often impossible to maintain the same teams of observers over the years and this variation through years can results in a major impact on the data quality and consistency; biased data can result into changes in time due to systematic differences among observers instead of true variations. Non-sampling errors (both within and between observer) can be classified in: 1) overlooking errors, when a species is not recorded when it is present; 2) misidentification errors, occurring when the species is not correctly identified; 3) estimation errors, when species abundances are not accurately estimated. This work aims to: i) investigate the role of observer subjectivity in sampling vegetation in forest monitoring plots in relation to different parameters such as vegetation complexity, observer expertise and the spatial scale of observation and ii) suggest ideas to reduce the observer bias for reliable and repeatable monitoring programs over long periods. We analyzed the observers’ influence on vegetation records using data collected in six forest areas in Tuscany (Central Italy): 10 nested multi-scale plots (three plot measures: 1 m2, 10 m2 and 100 m2) were sampled in spring/summer 2009 by three different teams of botanists with different level of knowledge of the vegetation in the areas. We analyzed the observers’ influence on vegetation data using different analytic methods such as comparisons among field notebooks and permutation analysis of variance (PERMANOVA). We observed that most of the divergence in species records are related with different characteristics of the sampled area, therefore ecologically and structurally complex sites increase observer bias due to the difficulty in species detection. Furthermore, we highlighted the importance of training for new observers to level off their experience with the other more-trained members of the monitoring team