Orchid Identification and Collection Techniques in the Kembang Kuning Resort Area, Rinjani Mount National Park (RMNP)

The Rinjani Mount National Park (RMNP) area is one part of the tropical rain forest in the West Nusa Tenggara region. Orchid is one of the flora that has a high bioprospective in this area. The spread of natural orchids can continue to grow and there are still many that have not been identified. This study aims to train specific techniques in collecting and identifying natural orchids at The Resort of Kembang Kuning, Rinjani Mount National Park. The collection of orchids was carried out using the roaming method, while the identification of orchid species was carried out using a species determination technique through observation of morphological and anatomical descriptions. The out comes of this study are an increase in participants' appreciation, knowledge and skills in collecting and identifying species of natural orchids in the Kembang Kuning area of Rinjani ​​Mount National Park. Based on the observations obtained 9 species (7 species were identified to the species level and 2 species were identified to the genus level) from 6 genera of natural orchids in area of The Kembang Kuning Resort, The Rinjani Mount National Park (RMNP).

Effect of Climate Change on CO2 Flux in Temperate Grassland, Subtropical Artificial Coniferous Forest and Tropical Rain Forest Ecosystems

The interactions between CO2 flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004–2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003–2010), and the tropical rain forest (TRF) of Xishuangbanna (2003–2010). The main factors of climate change affecting ecosystem CO2 flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO2 flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO2 flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.

IDENTIFIKASI JENIS KANTONG SEMAR (Nepenthes spp) DI HUTAN PENYANGGA DUSUN SEPAN DESA LANJAK DERAS KECAMATAN BATANG LUPAR KABUPATEN KAPUAS HULU

Nepenthes is a type of liana plant (vines) that can grow and develop in the tropical rain forest area. Nepenthes' appearance is very exotic because at of the leaf sheet pockets, appear with different colors and sizes. The unique characteristic that makes this plants different from others. The ability to catch insects that are used as nutrients to help their growth and development, marked by the formation of pockets at the tips of their leaves. The purpose of this research is to identify the species and sites of Nepenthes growth. Obtaining Nepenthes data found in the buffer forests of Sepan sub-village, Lanjak Deras Village, Batang Lupar District, Kapuas Hulu Regency. This study used a field survey method, with multiple plot technique. 45 observational plots were made with a size of 2 x 2 meters each. Six Nepenthes species were found, namely N. ampullaria, N. bicalcarata, N. gracilis, N. mirabilis, N. rafflesiana, N. reinwardtiana. The most common type found in the study site in the Buffor Forest Sepan sub-village, Lanjak Deras Village, is the type of Nepenthes gracilis with a total of 829 individuals. The fewest species found were Nepenthes bicalcarata with 17 individuals. Five from the six types of Nepenthes spp found at the research location were in the IUCN Red List, namely N. ampullaria, N. gracilis, N. mirabilis, N. rafflesiana and N. reinwardtiana included in conservation status, Least Concern (LC) or low risk (IUCN Red List, 2016)Keywords : Identification, Nepenthes, Lanjak Deras sub-village.AbstrakNepenthes merupakan jenis tanaman liana (sulur) yang dapat tumbuh dan berkembang di kawasan hutan hujan tropis. Penampilan Nepenthes sangat eksotik karena pada kantong-kantong lembaran daun, muncul dengan warna dan ukuran yang berbeda. Ciri khas yang membuat tanaman ini berbeda dari yang lain. Kemampuan menangkap serangga yang digunakan sebagai nutrisi untuk membantu pertumbuhan dan perkembangannya, ditandai dengan terbentuknya kantong-kantong pada ujung daunnya. Penelitian ini bertujuan untuk mengidentifikasi spesies dan tempat tumbuhnya Nepenthes. Memperoleh data Nepenthes yang ditemukan di hutan penyangga Dusun Sepan, Desa Lanjak Deras, Kecamatan Batang Lupar, Kabupaten Kapuas Hulu. Penelitian ini menggunakan metode survei lapangan, dengan teknik multiple plot. Dibuat 45 petak pengamatan dengan ukuran masing-masing 2 x 2 meter. Enam spesies Nepenthes yang ditemukan yaitu N. ampullaria, N. bicalcarata, N. gracilis, N. mirabilis, N. rafflesiana, N. reinwardtiana. Jenis yang paling banyak ditemukan di lokasi penelitian di Dusun Sepan Hutan Kerbau, Desa Lanjak Deras, adalah jenis Nepenthes gracilis dengan jumlah total 829 individu. Jenis yang paling sedikit ditemukan adalah Nepenthes bicalcarata dengan jumlah 17 individu. Lima dari enam jenis Nepenthes spp yang ditemukan di lokasi penelitian berada dalam Daftar Merah IUCN, yaitu N. ampullaria, N. gracilis, N. mirabilis, N. rafflesiana dan N. reinwardtiana termasuk dalam status konservasi, Least Concern (LC) atau berisiko rendah (Daftar Merah IUCN, 2016)Kata kunci : Identifikasi, Nepenthes, Dusun Lanjak Deras.

Inventarisasi Jenis-Jenis Anggrek di Kawasan Banyak Angkrem dan Kedung Kopong, Kecamatan Salaman, Kabupaten Magelang, Jawa Tengah

Banyak Angkrem and Kedung Kopong are medium lowland tropical rain forest areas where many types of orchids can be found. This study aims to determine the types and diversity of orchids found in the area of ​​Banyak Angkrem and Kedung Kopong. Data was collected using the Visual Encounter Survey (VES) method with a radius to the right and to the left 5 m from the observation path with a research area ​​6.24 ha. The results showed that in the two areas found 15 species of orchids consisting of 10 species of epiphytic orchids (Acriopsis lilifolia, Agrostophyllum laxum, Bulbophyllum sp 1, Bulbophyllum sp 2, Dendrobium sagittatum, Dendrobium sp, Oberonia lotsyana, Pholidota sp, Polystaschya concreta, Vanila. planifolia) and 5 species of terrestrial orchids (Geodorum densivelorum, Malaxis ophrydis, Malaxis sp, Nervilia plicata, Perystilus goodyroides). The level of diversity (H ') of orchids in the two regions is classified as moderate with an H' value of 2.22

Vegetation diversity and its interspecies association with merbau (Intsia bijuga) at three habitats of tropical rain forest in West Papua, Indonesia

Tasik S, Widyastuti SM, Musyafa, Suryanto P. 2021. Vegetation diversity and its interspecies association with merbau (Intsia bijuga) at three habitats of tropical rain forest in West Papua, Indonesia. Biodiversitas 22: 3383-3391. The stability of vegetation community indicated by species diversity, structure and composition affects the relationship between species. The understanding of interspecies association in their natural habitat is important especially for management and conservation strategies of species with particular interest, including merbau (Intsia bijuga O. Colebr Kuntze), a timber tree species with high commercial value. This study aims to investigate the diversity and composition of vegetation coexisting with merbau, and to see whether there is pattern of interspecies association with merbau. Vegetation analyses of species richness, diversity index, evenness index and interspecies relationship were conducted at three research locations in West Papua, Indonesia, namely Mount Meja Natural Tourism Park (Hutan Taman Wisata Alam Gunung Meja/HTWAGM), Bembab Beach Forest of South Manokwari (Hutan Bembab Pantai Manokwari Selatan/HBPMS) and Bembab Mountain Forest of South Manokwari (Hutan Bembab Gunung Manokwari Selatan/HBGMS). The results showed that the species Caryota rumphiana, Licuala sp 1, Calophyllum inophyllum, Garcinia pichoriza, Pometia coreacea and Pometia pinnata always grew side by side with Intsia bijuga in three locations. Furthermore, the association analysis indicated a positive and strong relationship between Intsia bijuga and Pometia coreacea, Licuala sp1, Licuala sp 2, Caryota rumphiana at all three research sites. In addition, Pometia coracea had the highest Chi-square value (X2 = 20.00) with the value of the three association indexes reached maximum value. We also found that the vegetation communities in the habitat of merbau had varying vegetation structure and composition as well as biodiversity indicators, yet they were all at stable state. The finding on vegetation analyses was confirmed with the result of soil analyses in which the physical and chemical properties had optimal conditions for vegetation to grow, including for merbau.

Modelling height-diameter relationships in complex tropical rain forest ecosystems using deep learning algorithm

Modelling tree height-diameter relationships in complex tropical rain forest ecosystems remains a challenge because of characteristics of multi-species, multi-layers, and indeterminate age composition. Effective modelling of such complex systems required innovative techniques to improve prediction of tree heights for use for aboveground biomass estimations. Therefore, in this study, deep learning algorithm (DLA) models based on artificial intelligence were trained for predicting tree heights in a tropical rain forest of Nigeria. The data consisted of 1736 individual trees representing 116 species, and measured from 52 0.25 ha sample plots. A K-means clustering was used to classify the species into three groups based on height-diameter ratios. The DLA models were trained for each species-group in which diameter at beast height, quadratic mean diameter and number of trees per ha were used as input variables. Predictions by the DLA models were compared with those developed by nonlinear least squares (NLS) and nonlinear mixed-effects (NLME) using different evaluation statistics and equivalence test. In addition, the predicted heights by the models were used to estimate aboveground biomass. The results showed that the DLA models with 100 neurons in 6 hidden layers, 100 neurons in 9 hidden layers and 100 neurons in 7 hidden layers for groups 1, 2, and 3, respectively, outperformed the NLS and NLME models. The root mean square error for the DLA models ranged from 1.939 to 3.887 m. The results also showed that using height predicted by the DLA models for aboveground biomass estimation brought about more than 30% reduction in error relative to NLS and NLME. Consequently, minimal errors were created in aboveground biomass estimation compared to those of the classical methods.