Eco-systematic assessment of the spring herbaceous vegetation under edaphic and topographic effects

The distribution and composition of the vegetation are greatly affected by the edaphology and topography of an area. The current study explores the vegetation structure of the herbaceous layer at various habitats of district Kohat for the first time. A survey was conducted during the spring seasons of 2021, 2022 and 2023 selecting 40 sites on the basis of edaphology, topography, altitude, aspect and status. Data was collected via quadrat approach to establish plant communities by species Importance Value (IV), point out dominant species by Total IV (TIV) and dominant families via Total Family IV (TFIV). The quantitative biological spectrum was also calculated. Communities' phytosociological characteristics were analyzed via various diversity indices (Shannon's Index (H), Simpson's Index (D), Species Richness (SR), Evenness (E) and Maturity index (Mi)) while similarity between the communities was calculated by using Sorensen's Index. The findings revealed a total of 253 species belonging to 57 families having the dominant species Cynodon dactylon (L.) Pers. (TIV, 484.3) followed by Saussuria heteromalla (D. Don) Hand. (TIV, 360.4), Anagallis arvensis L. (TIV, 353.2) and Aristida adscensionis L. (TIV, 349.65). Among 40 plant communities, Poaceae (TFIV, 2706.6), Asteraceae (TFIV, 2018.8), Fabaceae (TFIV, 1071.5) and Brassicaceae (TFIV, 825.9) were the dominant families. Therophytes (TIV, 7882) class was the dominant life form class followed by hemicryptophytes (TIV, 2517) while microphylls (TIV, 4669) class was the dominant leaf size class followed by nanophylls (TIV, 5469). Environmental factors i.e. topography and edaphic characteristics, showed significant effects on the diversity of the communities. The study concludes in a diverse pattern of distribution with a rich flora in the area warranting its documentation which will preserve the valuable species opening vistas for future research.

Effects of a Dominant Species on the Functional Diversity of Coexisting Species in Temperate Deciduous Understorey

The herb layer plays a significant role in maintaining forest functions, and its community composition is determined by various abiotic factors and biotic interactions. This study attempted to investigate the interspecific plant–plant biotic interactions using a functional traits approach. Specifically, the effects of a dominant species coverage on the functional diversity of coexisting species in the temperate forest understory were studied. Species coverage and soil moisture data were collected using a 1 m² quadrat couplet (2 × 1 m²) from six sites alongside a 20 m linear transect encompassing a cover gradient of Allium ursinum in southwest Hungary. Major plant functional dimensions i.e., aboveground, and clonal functional traits were considered. Linear and nonlinear mixed models to quantify the effects of biotic interaction on the functional diversity of every single trait and multiple traits were employed. Both aboveground traits and clonal traits of persistent clonal growth organs responded positively to the A. ursinum L., cover gradient. The coexistence of understory species in the presence of a monodominant species seems to be mainly influenced by aboveground traits as compared to the clonal traits suggesting, a role of niche differentiation. The consistent impact of A. ursinum coverage on coexisting species dynamics highlights a need for similar in-depth studies in various forest settings.

Empirical Approach for Modelling Tree Phenology in Mixed Forests Using Remote Sensing

Phenological events are good indicators of the effects of climate change, since phenological phases are sensitive to changes in environmental conditions. Although several national phenological networks monitor the phenology of different plant species, direct observations can only be conducted on individual trees, which cannot be easily extended over large and continuous areas. Remote sensing has often been applied to model phenology for large areas, focusing mostly on pure forests in which it is relatively easier to match vegetation indices with ground observations. In mixed forests, phenology modelling from remote sensing is often limited to land surface phenology, which consists of an overall phenology of all tree species present in a pixel. The potential of remote sensing for modelling the phenology of individual tree species in mixed forests remains underexplored. In this study, we applied the seasonal midpoint (SM) method with MODIS GPP to model the start of season (SOS) and the end of season (EOS) of six different tree species in Slovenian mixed forests. First, substitute locations were identified for each combination of observation station and plant species based on similar environmental conditions (aspect, slope, and altitude) and tree species of interest, and used to retrieve the remote sensing information used in the SM method after fitting the best of a Gaussian and two double logistic functions to each year of GPP time series. Then, the best thresholds were identified for SOS and EOS, and the results were validated using cross-validation. The results show clearly that the usual threshold of 0.5 is not best in most cases, especially for estimating the EOS. Despite the difficulty in modelling the phenology of different tree species in a mixed forest using remote sensing, it was possible to estimate SOS and EOS with moderate errors as low as <8 days (Fagus sylvatica and Tilia sp.) and <10 days (Fagus sylvatica and Populus tremula), respectively.

The Legacy of the Past Logging: How Forest Structure Affects Different Facets of Understory Plant Diversity in Abandoned Coppice Forests

Predicting how biodiversity affects ecosystem functioning requires a multifaceted approach based on the partitioning of diversity into its taxonomic and functional facets and thus redundancy. Here, we investigated how species richness (S), functional diversity (FD) and functional redundancy (FR) are affected by forest structure. Sixty-eight abandoned coppice-with-standards plots were selected in two mountain areas of the Apennine chain. We performed linear models to quantify the influence of structural parameters on S, FD and FR of clonal traits. Each diversity facet was affected differently by structural parameters, suggesting a complex interweaving of processes that influence the understory layer. Namely, tree layer density influences S, the height of the standards affects the lateral spread and persistence of clonal growth organs, and diameter of standards affects the FD of the number of clonal offspring. Opposite relationships compared to FD was found for the FR, suggesting how clonal traits play a key role in species assemblage. The observation that structural parameters exert opposite impact on FR seems to indicate a counterbalance effect on ecosystem stability. Multifaceted approaches yield a better understanding of relationship between forest structure and understory, and this knowledge can be exploited to formulate indications for more sustainable management practices.