Biochar preparation and evaluation of its effect in composting mechanism: A review.

This article provides an overview of biochar application for organic waste co-composting and its biochemical transformation mechanism. As a composting amendment, biochar work in the adsorption of nutrients, the retention of oxygen and water, and the promotion of electron transfer. These functions serve the micro-organisms (physical support of niche) and determine changes in community structure beyond the succession of composing primary microorganisms. Biochar mediates resistance genes, mobile gene elements, and biochemical metabolic activities of organic matter degrading. The participation of biochar enriched the α-diversity of microbial communities at all stages of composting, and ultimately reflects the high γ-diversity. Finally, easy and convincing biochar preparation methods and characteristic need to be explored, in turn, the mechanism of biochar on composting microbes at the microscopic level can be studied in depth.

Disentangling direct and indirect drivers of farmland biodiversity at landscape scale.

To stop the ongoing decline of farmland biodiversity there are increasing claims for a paradigm shift in agriculture, namely from conserving and restoring farmland biodiversity at field scale (α-diversity) to doing it at landscape scale (γ-diversity). However, knowledge on factors driving farmland γ-diversity is currently limited. Here, we quantified farmland γ-diversity in 123 landscapes and analysed direct and indirect effects of abiotic and land-use factors shaping it using structural equation models. The direction and strength of effects of factors shaping γ-diversity were only partially consistent with what is known about factors shaping α-diversity, and indirect effects were often stronger than direct effects or even opposite. Thus, relationships between factors shaping α-diversity cannot simply be up-scaled to γ-diversity, and also indirect effects should no longer be neglected. Finally, we show that local mitigation measures benefit farmland γ-diversity at landscape scale and are therefore a useful tool for designing biodiversity-friendly landscapes.

Undersampling correction methods to control γ-dependence for comparing ß-diversity between regions.

Measures of ß-diversity are known to be biased by differences in γ-diversity (i.e., γ-dependence), making it challenging to compare ß-diversity across regions. Undersampling corrections have been designed to reduce effects of γ-dependence on ß-diversity arising from the problem of incomplete sampling. However, no study has systematically tested the effectiveness of these corrections or examined how well they reflect ß-diversity patterns across ecological gradients. Here, we conduct these tests by comparing two undersampling corrections with the widely used individual-based null model approach, using both simulated communities along an ecological gradient and empirical data across a wide range of γ-diversity and sample sizes. We found that undersampling corrections using diversity accumulation curves were more effective than the null-model approaches in removing γ-dependence. In particular, the corrected ß-Shannon diversity index was least dependent on γ-diversity, and was the most reflective of the ß-diversity pattern along a simulated ecological gradient. Moreover, a corrected Jaccard-Chao index applied to null model results removed γ-dependence more effectively than either the correction alone or the null model alone. Undersampling corrections are effective tools for removing γ-dependence bias, thus facilitating comparisons of ß-diversity across regions.

Biotic homogenization destabilizes ecosystem functioning by decreasing spatial asynchrony.

Our planet is facing significant changes of biodiversity across spatial scales. Although the negative effects of local biodiversity (α diversity) loss on ecosystem stability are well documented, the consequences of biodiversity changes at larger spatial scales, in particular biotic homogenization, that is, reduced species turnover across space (ß diversity), remain poorly known. Using data from 39 grassland biodiversity experiments, we examine the effects of ß diversity on the stability of simulated landscapes while controlling for potentially confounding biotic and abiotic factors. Our results show that higher ß diversity generates more asynchronous dynamics among local communities and thereby contributes to the stability of ecosystem productivity at larger spatial scales. We further quantify the relative contributions of α and ß diversity to ecosystem stability and find a relatively stronger effect of α diversity, possibly due to the limited spatial scale of our experiments. The stabilizing effects of both α and ß diversity lead to a positive diversity-stability relationship at the landscape scale. Our findings demonstrate the destabilizing effect of biotic homogenization and suggest that biodiversity should be conserved at multiple spatial scales to maintain the stability of ecosystem functions and services.

Long-term spatio-temporal changes of the muddy fine sand benthic community of the Bay of Seine (eastern English Channel).

In the English Channel, the eastern Bay of Seine is exposed to numerous anthropogenic disturbances, in particular major changes in sediment dynamics, which are expected to greatly impact benthic communities. To assess the long-term effects of these stressors on the muddy fine sand benthic community, an original long-term monitoring program has been implemented since 1988. It is based on the sampling of a network of 60 stations during seven surveys over 28 years from 1988 to 2016. We investigate changes of species density, species composition and species diversity at different scales (α-diversity, ß-diversity and γ-diversity). Contrary to results obtained in many coastal areas, our results showed a long-term persistence of the community in terms of species composition and structure although a general shift towards muddy sediment has resulted in increased colonisation by species associated with muddy habitats and a decrease in spatial beta diversity.

Biogeographic, climatic and spatial drivers differentially affect α-, ß- and γ-diversities on oceanic archipelagos.

Island biogeographic studies traditionally treat single islands as units of analysis. This ignores the fact that most islands are spatially nested within archipelagos. Here, we took a fundamentally different approach and focused on entire archipelagos using species richness of vascular plants on 23 archipelagos worldwide and their 174 constituent islands. We assessed differential effects of biogeographic factors (area, isolation, age, elevation), current and past climate (temperature, precipitation, seasonality, climate change velocity) and intra-archipelagic spatial structure (archipelago area, number of islands, area range, connectivity, environmental volume, inter-island distance) on plant diversity. Species diversity of each archipelago (γ) was additively partitioned into α, ß, nestedness and replacement ß-components to investigate the relative importance of environmental and spatial drivers. Multiple regressions revealed strong effects of biogeography and climate on α and γ, whereas spatial factors, particularly number of islands, inter-island distance and area range, were key to explain ß. Structural equation models additionally suggested that γ is predominantly determined by indirect abiotic effects via its components, particularly ß. This highlights that ß and the spatial arrangement of islands are essential to understand insular ecology and evolution. Our methodological framework can be applied more widely to other taxa and archipelago-like systems, allowing new insights into biodiversity origin and maintenance.

Diversity and distribution of ferns in sub-Saharan Africa, Madagascar and some islands of the South Atlantic.

Aim This paper reports the diversity and endemism patterns of African ferns, and explores the potential role of diversity refuges and environmental and historical factors in the shaping of these patterns. Material and locations The extant fern taxa occupying Africa south of the Sahara, Madagascar and some islands of the South Atlantic. Methods The number of taxa in each area or operational geographical unit (OGU) was scored, and the correlation between this number and physical and climatic variables analysed by standard pairwise and stepwise multiple regression analysis (SPR and SMR). The effects of biological factors such as dispersal capacity, reproductive biology, genetic features and certain physiological adaptations were evaluated by comparing the number of species in each OGU. Floral affinities among OGUs were analysed using non-metric multi-dimensional scaling (NMS) and parsimonic analysis of dispersion (PAD), and compared with ß-turnover and inter-OGU distances. Results OGU area, elevation and the distance between refuges determined the composition of local floras, but only greater OGU area and the existence of higher maximum elevations increased species richness. The distance between refuges also affected the number of endemic species, especially on islands. The biological features studied only slightly influenced fern distribution. The main climatic predictor of species number was humidity. SPR and SMR revealed three main groups of ferns with different ecological trends. NMS and PAD analyses separated the four areas of highest diversity in Africa, three of which are inhabited by ferns with distinct ecological requirements. The fourth area was Madagascar, which shows an accumulation of endemic and relict diversity that is not easy to explain. Main conclusions The distribution of ferns in Africa has been influenced by refuges. These probably allowed many species to recolonize the neighbouring areas after the extinctions of the Pleistocene. Three major components were detected in the African flora: Guinea-Congolian thermophilous, cold-tolerant Afro-montane, and Southern drought-tolerant elements. These are related to the three main refuge areas, i.e. the Gulf of Guinea area, the eastern tropical region, and the Cape region. Endemicity in ferns was found to be lower than that of seed plants due to the higher dispersability of fern spores. The distance between OGUs seems to be the main predictor of the number of endemic fern species these areas contain.