Sundarbans, the world’s largest mangrove biomes, have a rich biodiversity of diverse flora and fauna. Although various attempts had been made previously to explore the diversity of this World Heritage Site, information related to the diversity and ecology of macrofungi in this region is sparse. In this context, the aim of this study was to record the macrofungal diversity and describe the macrofungal communities of this ecosystem whose lifecycles are intricately woven with the mangrove ecosystem of the Indian part of Sundarbans. Carpophore surveys were conducted from June 2010 to September 2012 over 77 randomly placed quadrats (20 × 20 m²). A total of 455 carpophores belonging to 62 species across 27 families and 46 genera were recorded. Of the total number of macrofungal species listed, around 55% were saprophytic. The genera with the greatest species richness were Ganoderma and Tricholoma. Comparing the species richness estimators, the cumulative number of species over the three successive years revealed that 75–100% of potential macrofungal species were recorded. Results from the present study are an important contribution to the knowledge of the macrofungal diversity of the mangrove ecosystems, both in India and worldwide.

Pradhan P, Setyawan AD. 2021. Filtering multi-collinear predictor variables from multi-resolution rasters of WorldClim 2.1 for Ecological Niche Modeling in Indonesian context. Asian J For 5: 111-122. WorldClim is one of the popular environmental datasets which hosts multi-resolution interpolated gridded climate raster surfaces and derived bioclimatic variables for both the immediate past, present and future scenarios. Bioclimatic variables along with other environmental factors like solar radiation, wind speed, water vapour pressure etc. have been used as primary set of explanatory variables for mapping and spatial modeling of many biological processes, including defining environmental niche of a species and identifying potential areas for its distribution through machine learning methods like Ecological Niche Modeling or Species Distribution Modeling or Habitat Suitability Modeling. However, the interpolated explanatory datasets are known to cause over-fitting of the models mainly due to multi-collinearity or redundancy within the variables. In the present study, 58 bioclimatic and environmental variables of Indonesian extent extracted from WorldClim 2.1 are screened to investigate the presence of multi-collinearity or redundancy. From the total 3364 variable pairs per raster resolution, 174 variable pairs were known to be affected by multicollinearity, from which temperature related bioclimatic variables, water vapour pressure and elevation associated variables were highly notable. For all the raster resolutions, bioclimatic variable 2, 3, 4, 15, 18 and 19, as well as slope, aspect, solar radiation for January, April, May, September, wind speed for August and November were found to be non-collinear. While, solar radiation for March and July were found to be non-collinear for 30s, 2.5m and 5m raster resolutions; Wind speed of July was non-collinear for 30s and 2.5m; Solar radiation for February and June were non-collinear for 10m; water vapour pressure for August for 2.5m and wind speed for January was non-collinear for 30s raster resolutions. The results of this study might serve as a convenient reference for investigators of the region for selection of bioclimatic and other environmental variables for conducting ecological niche modeling studies.

The diversity of macrofungi in the lateritic region of West Bengal was explored and 120 species, one subgenus and a variety, having eight ecological functions, were found to grow among three types of habitats, i.e. natural forests, plantation forests and villages. Yate’s corrected chi-square (χ2) test statistic was performed upon the 2 × 2 table (contingency table) and testing the null hypotheses of independence of observed cell frequencies of the presence/absence of a species in a given habitat type. Various degrees of specificities of macrofungi to their habitats were observed, i.e. Amanita vaginata, Astraeus hygrometricus, Laccaria laccata, Lactarius zonarius, Porphyrellus malaccensis, Russula brevipes, Russula delica, Russula emetica and Russula laurocerasi were absolutely specific for natural forests; Pisolithus arhizus and Ramaria fumigata were absolutely specific for plantation forests; Auricularia auricula, Schizophyllum commune and Termitomyces clypeatus (only association coefficient 100%) were found to absolutely specific for village habitat. MS Excel-based formulas for calculation of association/specificity of species to habitat and species to species as well as other diversity indices are provided. Local and tribal populations used 19 species of macrofungi during their fruiting period, of which 17 had culinary values and four were locally considered medicinal. This study is a first of its kind, and has various applications to allied disciplines in understanding diversity, ecology and biological prospects of the macrofungal realm.

Macrofungi are broad in diversity and play an important role in sustaining ecosystems. However, the quantity and quality of their habitat is decreasing and the threat of extinction looms over the remaining 95% of the world's undiscovered fungal species. There is an urgent need for inventorisation, monitoring and conservation of macrofungi and the habitats supporting their growth. This paper focuses on the species richness, assemblage and spatial ecology of the macrofungi whose lifecycles are intricately woven with natural Shorea robusta forests in the lateritic region of West Bengal, India. Decreasing soil productivity, poor regeneration of Shorea seedlings and subsequent habitat degradation for macrofungi are a prime cause of concern.