Estimating Aboveground Biomass in Dense Hyrcanian Forests by the Use of Sentinel-2 Data

Due to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for estimating the AGB in pure stands of Carpinus betulus (L., common hornbeam) located in the Hyrcanian forests, northern Iran. For this purpose, the diameter at breast height (DBH) of all trees thicker than 7.5 cm was measured in 55 square plots (45 × 45 m). In situ AGB was estimated using a local volume table and the specific density of wood. To estimate the AGB from remotely sensed data, parametric and nonparametric methods, including Multiple Regression (MR), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), and Random Forest (RF), were applied to a single image of the Sentinel-2, having as a reference the estimations produced by in situ measurements and their corresponding spectral values of the original spectral (B2, B3, B4, B5, B6, B7, B8, B8a, B11, and B12) and derived synthetic (IPVI, IRECI, GEMI, GNDVI, NDVI, DVI, PSSRA, and RVI) bands. Band 6 located in the red-edge region (0.740 nm) showed the highest correlation with AGB (r = −0.723). A comparison of the machine learning methods indicated that the ANN algorithm returned the best ABG-estimating performance (%RMSE = 19.9). This study demonstrates that simple vegetation indices extracted from Sentinel-2 multispectral imagery can provide good results in the AGB estimation of C. betulus trees of the Hyrcanian forests. The approach used in this study may be extended to similar areas located in temperate forests.

Degradation of dibutyl phthalate by Paenarthrobacter sp. Shss isolated from Saravan landfill, Hyrcanian Forests, Iran

Phthalic acid esters are predominantly used as plasticizers and are industrially produced on the million ton scale per year. They exhibit endocrine-disrupting, carcinogenic, teratogenic, and mutagenic effects on wildlife and humans. For this reason, biodegradation, the major process of phthalic acid ester elimination from the environment, is of global importance. Here, we studied bacterial phthalic acid ester degradation at Saravan landfill in Hyrcanian Forests, Iran, an active disposal site with 800 tons of solid waste input per day. A di-n-butyl phthalate degrading enrichment culture was established from which Paenarthrobacter sp. strain Shss was isolated. This strain efficiently degraded 1 g L–1 di-n-butyl phthalate within 15 h with a doubling time of 5 h. In addition, dimethyl phthalate, diethyl phthalate, mono butyl phthalate, and phthalic acid where degraded to CO2, whereas diethyl hexyl phthalate did not serve as a substrate. During the biodegradation of di-n-butyl phthalate, mono-n-butyl phthalate was identified in culture supernatants by ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry. In vitro assays identified two cellular esterase activities that converted di-n-butyl phthalate to mono-n-butyl phthalate, and the latter to phthalic acid, respectively. Our findings identified Paenarthrobacter sp. Shss amongst the most efficient phthalic acid esters degrading bacteria known, that possibly plays an important role in di-n-butyl phthalate elimination at a highly phthalic acid esters contaminated landfill.

New earthworm records from the Caspian Hyrcanian Forests of Iran (Oligochaeta: Megadrili)

Earthworms are the most important soil invertebrates worldwide, in terms of biomass and effects on soil processes. In this study, 21 earthworm species, including four new records were identified from Caspian Hyrcanian Forests (North of Iran). Four species; Criodrilus lacuum, Lumbricus rubellus, Metaphire californica, and Octodrilus transpadanus and the family Criodrilidae are reported for the first time. Previous studies have identified 31 earthworm species belonging to 14 genera and three families (Lumbricidae, Acanthodrilidae, and Megascolecidae) in Iran; therefore, these new records increase the number of earthworm species to a total of 35.

Vegetation Growth Analysis of UNESCO World Heritage Hyrcanian Forests Using Multi-Sensor Optical Remote Sensing Data

Freely available satellite data at Google Earth Engine (GEE) cloud platform enables vegetation phenology analysis across different scales very efficiently. We evaluated seasonal and annual phenology of the old-growth Hyrcanian forests (HF) of northern Iran covering an area of ca. 1.9 million ha, and also focused on 15 UNESCO World Heritage Sites. We extracted bi-weekly MODIS-NDVI between 2017 and 2020 in GEE, which was used to identify the range of NDVI between two temporal stages. Then, changes in phenology and growth were analyzed by Sentinel 2-derived Temporal Normalized Phenology Index. We modelled between seasonal phenology and growth by additionally considering elevation, surface temperature, and monthly precipitation. Results indicated considerable difference in onset of forests along the longitudinal gradient of the HF. Faster growth was observed in low- and uplands of the western zone, whereas it was lower in both the mid-elevations and the western outskirts. Longitudinal range was a major driver of vegetation growth, to which environmental factors also differently but significantly contributed (p < 0.0001) along the west-east gradient. Our study developed at GEE provides a benchmark to examine the effects of environmental parameters on the vegetation growth of HF, which cover mountainous areas with partly no or limited accessibility.