Tropical Rainforest Research Articles

Central American Red BrocketDieta de Mazama temama (Kerr 1792, Artiodactyla: Cervidae) en Parque Nacional Cañón del Río Blanco

Determining the diet of herbivores through the epidermal structures present in their excreta makes it possible to identify the plants consumed and estimate the variations at different times of the year. The objective of the study was to determine the botanical composition of the diet of the deer Central American Red Brocket (Mazama temama), in the Parque Nacional Cañón del Río Blanco (PNCRB), Veracruz, Mexico. The vegetation where the study was carried out is an evergreen tropical forest with the presence of induced vegetation. Sampling was carried out during the dry and rainy season of 2021. The plant species consumed were identified with the microhistological analysis of epidermal residues in fecal samples. The diet consisted of 18 species of plants belonging to 14 botanical families. The highest percentage of consumption was for the Solanaceae family (16.6%), followed by Arecaceae, Asteraceae, Cucurbitacea and Malvaceae (11.1% each). 66% of the plants were consumed in the dry season, and consumption increased by 34% during the rainy season, showing 100% of the plant species in the rainy season, showing 100% consumption in the rainy season.. The plants consumed were 10 herbaceous plants (55.5%), six arboreal plants (33.5%), one shrub and one grass (5.5% each); forest edge plants (BB = 44%), forest interior plants (IB = 33%) and cultured plants (CP = 23%), constituted the diet. M. temama adapted its diet to the availability and temporal and spatial distribution of plants in the habitat and based on climatic conditions (dry vs. rainy).

Evaluation of oil palm (Elaeis guineensis Jacq.) productivity on peatlands based on DRIS analysis of leaf nutrient content in Siak District of Indonesia

Indonesia is the largest producer of oil palm in the world, with Riau Province particularly Siak District being the major contributor. The study focused on oil palm plantations within Siak District, characterized by a tropical rainforest climate of high humidity. The soil type in this area was a peatland with sapric and hemic maturity. The planting material used primarily consists of the DxP Marihat variety, which was planted between 1995-2005, with an average potential fresh fruit bunch productivity of 29.00 tons/ha/year. Variations in nutrient contents in oil palm leaf were observed across each block of the study location. Diagnosis and recommendation integrated system (DRIS) analysis was conducted on found number 17 to determine the key nutrients required to increase oil palm productivity. This method consists of several stages, including norm analysis, DRIS index, nutrient balance index (NBI), optimum leaf nutrient value, and leaf nutrient interval. Data was obtained from 312 leaf nutrient analyses and fresh fruit bunch productivity across 39 blocks for the period between 2015 and 2022. A value of 26.33 tons/ha/year, derived from DRIS norm calculation, indicated the border between high and low productivity blocks. The results showed that the order of macronutrient and micronutrient requirements in high productivity blocks was N>P>K>Ca>Mg and B>Cu>Zn, while in low productivity blocks, it was Ca>Mg>N>K>P and B>Cu>Zn. Regression of DRIS index and leaf nutrient content obtained optimum nutrient values of 2.78%, 0.16%, 1.02%, 0.66%, 0.35%, 29.51 ppm, 3.65 ppm, and 15.37 ppm for N, P, K, Ca, Mg, B, Cu, and Zn, respectively. Therefore, nutrients Ca and B were prioritized to increase the achievement of oil palm fresh fruit bunch productivity.

Silvopastoral transitions in Latin America: toward diverse perennial systems

AbstractAgroecosystems with greater diversity and perenniality have been proposed to promote resilience to climate change, stability of production, multiple ecosystem services, and socioeconomic outcomes. A wide diversity of silvopastoral systems have been promoted in Latin America for their production and environmental outcomes. In this brief perspective article, we discuss the implications of different trajectories towards silvopastoral systems within the framework of ecological intensification. Transitioning from agricultural systems dominated by annual crops towards complex silvopastoral systems integrating multiple perennial species and livestock constitutes a clear trajectory of ecological intensification. In the context of the tropical dry forests and Amazon rainforests, re-introducing native trees into degraded sown pastures to establish silvopastoral systems increases biodiversity, perenniality, and ecosystem services. In contrast, in the context of native grasslands, plantations of exotic trees for timber or silvopastoral systems reduce biodiversity and ecosystem services. Therefore, transitioning to silvopastoral systems is not always a trajectory of ecological intensification but depends on the contexts and native ecosystems.

Linkages among forests, food security and livelihoods: A comparative analysis of tropical dry forests and tropical wet evergreen forests in Sri Lanka

Forests are increasingly recognised as an important contributor to food security and nutrition, especially for the poorest people, in various ways. Their roles and impacts including the degree of access to forest-based nutrition to the poorer segments however vary depending on the specific geographic and socio-political contexts and forest types. This study examines the nature of forest dependence for food security and nutrition in two dominant forest types in Sri Lanka, namely dry humid forest and wet evergreen forests. Proportionate to the forest cover area in either forest system, this study enumerated 500 households in the dry forest ecology and 190 households in the wet evergreen forest ecology. The findings provide a first quantitative benchmarking of the nature of forest food collection and modelling of the socio-demographic factors determining the forest food collection in the Sri Lankan context. The results show that food produce collection in terms of quantity and value are significantly higher in the wet evergreen forest system and the factors driving the dependence on forests are tied to agricultural involvement of the households. Other factors such as economic status, education, accessibility of the forest emerge statistically insignificant. On the other hand, in dry humid forests, economic status and access to forest become significant factors. Evidence confirms the location specific nature of forest food connection and make the case for context-relevant interventions to foster forest-food interface.

Olfaction foraging in visually oriented tropical arboreal ants Oecophylla smaragdina: Implications for insect predation studies using artificial sentinel prey

AbstractBecause of the brief and cryptic nature of predatory behavior, sentinel prey has been widely adopted as an indirect way to identify predators and understand trophic interactions. However, sentinel prey presents only static visual cues, potentially biasing toward visually oriented predators while ignoring those that utilize other sensory cues for foraging. Despite this, the effectiveness of sentinel prey has rarely been tested. In this study, we focused on the weaver ant Oecophylla smaragdina Fabricius (Hymenoptera: Formicidae), a keystone predator widespread in the Asian and Australian tropics. As this species has large eyes and is known to visually navigate in its arboreal habitats, we hypothesized that it relies on visual cues to forage and that its predatory behavior will be captured by caterpillar‐shaped sentinel prey. Ants were collected as colonies, and preference trials on baits were conducted using combinations of olfactory and static visual cues, including the caterpillar shape. Surprisingly, O. smaragdina showed little or no preference for baits in the absence of olfactory cues and did not differentiate the shapes of baits regardless of olfactory cues. Our results indicate that O. smaragdina is likely to make predatory decisions based primarily on olfactory cues, whereas visual cues might be used for other behaviors. Furthermore, O. smaragdina is likely to be left out by the predation studies using sentinel prey models, which is particularly alarming considering the dominant role of this species in the trophic interactions of tropical rainforests. Our study demonstrates that morphological characteristics, arboreal habitats, and visually oriented behavior do not necessarily suggest the use of static visual cues for predatory decisions. We suggest that sentinel prey models should not be used alone when the dominant predators are unlikely to use visual cues to make predatory decisions.

Forest 3D Radar Reflectivity Reconstruction at X-Band Using a Lidar Derived Polarimetric Coherence Tomography Basis

Tomographic Synthetic Aperture Radar (SAR) allows the reconstruction of the 3D radar reflectivity of forests from a large(r) number of multi-angular acquisitions. However, in most practical implementations it suffers from limited vertical resolution and/or reconstruction artefacts as the result of non-ideal acquisition setups. Polarisation Coherence Tomography (PCT) offers an alternative to traditional tomographic techniques that allow the reconstruction of the low-frequency 3D radar reflectivity components from a small(er) number of multi-angular SAR acquisitions. PCT formulates the tomographic reconstruction problem as a series expansion on a given function basis. The expansion coefficients are estimated from interferometric coherence measurements between acquisitions. In its original form, PCT uses the Legendre polynomial basis for the reconstruction of the 3D radar reflectivity. This paper investigates the use of new basis functions for the reconstruction of X-band 3D radar reflectivity of forests derived from available lidar waveforms. This approach enables an improved 3D radar reflectivity reconstruction with enhanced vertical resolution, tailored to individual forest conditions. It also allows the translation from sparse lidar waveform vertical reflectivity information into continuous vertical reflectivity estimates when combined with interferometric SAR measurements. This is especially relevant for exploring the synergy of actual missions such as GEDI and TanDEM-X. The quality of the reconstructed 3D radar reflectivity is assessed by comparing simulated InSAR coherences derived from the reconstructed 3D radar reflectivity against measured coherences at different spatial baselines. The assessment is performed and discussed for interferometric TanDEM-X acquisitions performed over two tropical Gabonese rainforest sites: Mondah and Lopé. The results demonstrate that the lidar-derived basis provides more physically realistic vertical reflectivity profiles, which also produce a smaller bias in the simulated coherence validation, compared to the conventional Legendre polynomial basis.

Effect of Depositional Environment and Climate on Organic Matter Enrichment in Sediments of the Upper Miocene—Pliocene Kampungbaru Formation, Lower Kutai Basin, Indonesia

The Upper Miocene–Pliocene Kampungbaru Formation crops out in the easternmost part of the Lower Kutai Basin, Indonesia. The sedimentological analysis of seven outcrops was carried out, and a total of twenty-five samples from these outcrops was analyzed for bulk geochemistry, organic petrography, and bulk and clay mineralogy to assess the effect of the climate and depositional environment on organic matter enrichment. The Kampungbaru Formation consists of interbedded sandstone, siltstone, claystone, and thick coal beds, which were classified into eleven lithofacies. Subsequently, seven facies associations were identified, namely the fluvial-dominated distributary channel, sheet-like sandstone, tide-influenced distributary channel, mouth bar, crevasse splay, delta plain, and delta front. The coal facies generally have a high amount of total organic carbon (TOC, 5.1–16.9; avg. 10.11 wt.%), and non-coal layers range from 0.03 to 4.22 wt.% (avg. 1.54 wt.%). The dominant maceral is vitrinite, while liptinite occurs only rarely in the samples. Organic matter is inferred to have originated from terrestrial plants growing in mangrove swamps. Identified clay minerals include varying proportions of kaolinite, illite, chlorite, and mixed layer illite/smectite (I/S). Kaolinite, which commonly constitutes up to 30% of the clay volume, indicates intensive chemical weathering during a warm and humid climate. In accordance with the Köppen climate classification, the paleoclimate during the deposition of the Kampungbaru Formation is classified as type Af, which is a tropical rainforest. Tropical climate was favorable for the growth of higher plants and deposition of organic matter under anoxic conditions and led to higher amounts of TOC in the Kampungbaru Formation.

Complete phylogeny of Micrathena spiders suggests multiple dispersal events among Neotropical rainforests, islands and landmasses, and indicates that Andean orogeny promotes speciation.

The Neotropical region is the most diverse on the planet, largely owing to its mosaic of tropical rainforests. Multiple tectonic and climatic processes have been hypothesized to contribute to generating this diversity, including Andean orogeny, the closure of the Isthmus of Panama, the GAARlandia land bridge and historical connections among currently isolated forests. Micrathena spiders are diverse and widespread in the region, and thus a complete phylogeny of this genus allows the testing of hypotheses at multiple scales. We estimated a complete, dated phylogeny using morphological data for 117 Micrathena species and molecular data of up to five genes for a subset of 79 species. Employing event-based approaches and biogeographic stochastic mapping while considering phylogenetic uncertainty, we estimated ancestral distributions, the timing and direction of dispersal events and diversification rates among areas. The phylogeny is generally robust, with uncertainty in the position of some of the species lacking sequences. Micrathena started diversifying around 25 Ma. Andean cloud forests show the highest in-situ speciation, while the Amazon is the major dispersal source for adjacent areas. The Dry Diagonal generated few species and is a sink of diversity. Species exchange between Central and South America involved approximately 23 dispersal events and started ~20 Ma, which is consistent with a Miocene age for the Isthmus of Panama closure. We inferred four dispersal events from Central America to the Antilles in the last 20 Myr, indicating the spiders did not reach the islands through the GAARlandia land bridge. We identified important species exchange routes among the Amazon, Andean cloud forests and Atlantic forests during the Plio-Pleistocene. Sampling all species of the genus was fundamental to the conclusions above, especially in identifying the Andean forests as the area that generated the majority of species. This highlights the importance of complete taxonomic sampling in biogeographic studies.

Assessment of maize-cowpea intercropping response to row orientation in diverse agro-ecologies of Côte d'Ivoire

The stability of cropping systems in a changing climate context depends on numerous factors, including row orientation, to optimize the use of environmental resources. This study aimed to evaluate the performance of agricultural systems based on the row orientation of cowpea (Vigna unguiculata) and maize (Zea mays) in three different ecological conditions in Côte d’Ivoire, in 2020 and 2021. An experimental design with plots divided into three complete randomized blocks with six subplots per block and three repetitions was set up, varying the row orientation in intercropping and monoculture. Row orientation, cropping system used, and ecological zone significantly influenced crop yield and its components. In intercropping, cowpea (tiligré) showed the best yields when oriented North–South (NS) in the tropical rainforest zone and the sub-Sudanian savannah, while East–West (EW) orientation was optimal in the forest-savannah mosaic zone. In contrast, maize (GMRP18) yielded the best in intercropping when rows were oriented East–West, regardless of the season. In monoculture, cowpea yielded best when oriented EW in the tropical rainforest zone (488.17 kg ha−1) and in the forest-savannah mosaic zone (1262.12 kg ha−1), while NS orientations were preferable (228.6 and 259.54 kg ha−1) in the sub-Sudanian savannah zone. For maize monoculture, EW orientation was also preferable. Throughout the study, for both seasons, the highest yield advantages in maize-cowpea intercropping were obtained in EW orientation, regardless of the ecological zone. Overall, the forest-savannah mosaic zone yielded the best cowpea yields (1262.12 and 663.9 kg ha−1).

Medicinal Plants Recommendation System using ROC and MOORA

Kalimantan has extraordinary biodiversity, including medicinal plants. Medicinal plants are a type of plant that certain parts, such as roots, leaves, bark, stems, and the results of their excretions. However, people sometimes need help choosing plants that suit their needs because of the many types of medicinal plants and the need for knowledge regarding their use. Decision support systems (DSS) combine computer capabilities with data processing or manipulation that utilizes unstructured models or solution rules. Furthermore, the method of documenting knowledge of traditional medicine is through the media of information systems. This system helps select medicinal plants according to user needs. This research developed a DSS using Rank Order Centroid (ROC) and Multi-Objective Optimization by Ratio Analysis (MOORA) methods to select medicinal plants for fungal and skin infections, including Furuncles, Tinea corporis, Tinea versicolor, and Acne. ROC method for determining criteria weight values. This research has four criteria: plant part, processing method, use method, and habitus. Determining recommendations for alternative ranking results using the MOORA method. This study aims to help the public get recommendations for medicinal plants in human skin disease treatment. This study aims to increase the preservation of biodiversity, particularly sustainable medicinal plants in the tropical rainforest of East Kalimantan.

Untangling the complex food webs of tropical rainforest streams.

Food webs depict the tangled web of trophic interactions associated with the functioning of an ecosystem. Understanding the mechanisms providing stability to these food webs is therefore vital for conservation efforts and the management of natural systems. Here, we first characterised a tropical stream meta-food web and five individual food webs using a Bayesian Hierarchical approach unifying three sources of information (gut content analysis, literature compilation and stable isotope data). With data on population-level biomass and individually measured body mass, we applied a bioenergetic model and assessed food web stability using a Lotka-Volterra system of equations. We then assessed the resilience of the system to individual species extinctions using simulations and investigated the network patterns associated with systems with higher stability. The model resulted in a stable meta-food web with 307 links among the 61 components. At the regional scale, 70% of the total energy flow occurred through a set of 10 taxa with large variation in body masses. The remaining 30% of total energy flow relied on 48 different taxa, supporting a significant dependency on a diverse community. The meta-food web was stable against individual species extinctions, with a higher resilience in food webs harbouring omnivorous fish species able to connect multiple food web compartments via weak, non-specialised interactions. Moreover, these fish species contributed largely to the spatial variation among individual food webs, suggesting that these species could operate as mobile predators connecting different streams and stabilising variability at the regional scale. Our results outline two key mechanisms of food web stability operating in tropical streams: (i) the diversity of species and body masses buffering against random and size-dependent disturbances and (ii) high regional diversity and weak omnivorous interactions of predators buffering against local stochastic variation in species composition. These mechanisms rely on high local and regional biodiversity in tropical streams, which is known to be strongly affected by human impacts. Therefore, an urgent challenge is to understand how the ongoing systematic loss of diversity jeopardises the stability of stream food webs in human-impacted landscapes.

Vertical niche and trait associations in Central African amphibians

AbstractTropical forests are vertically complex and offer unique niche opportunities in the form of resources, climate, and habitat gradients from the forest floor to the canopy. Rainforest amphibians have diversified within this vertical space, resulting in partitioned niches and corresponding morphological, behavioral, and reproductive traits. However, a lack of data regarding the vertical niche space used by amphibian species has prevented a nuanced analysis of the form‐function relationship between traits and vertical height. We performed 74 ground‐to‐canopy surveys for amphibians in the tropical rainforest of Gabon and described the vertical stratification patterns of the assemblage in terms of richness, abundance, and species‐specific vertical niches. We determined that the community shift in richness and abundance between the ground and understory was pronounced, while the community change from understory to canopy was gradual. We analyzed the relationships between amphibian traits with vertical height using linear mixed effects models, finding strong support (>60% variance explained) that frogs with bigger toes in relation to their length access greater height in the canopy. This relationship provides support for the form‐function hypothesis: that morphology changes predictably to meet the functional demands of species along niche gradients. Furthermore, we documented differences in the vertical heights of species according to their reproductive modes, highlighting the potential impact of reproductive mode diversity on the vertical stratification patterns of amphibian assemblages.

Renewable Energy Analysis and Evaluation with Economic Utilization of Solar Powered Air Conditioning System in Nigeria

This article focuses on the analysis and integration of PV systems to load ratio correlation and the economic importance of the left over to grid supply and integration. The paper focusses on the different methods of PV generation to load utilization using the solar powered air conditioner as the load while minimizing the use of fossil fuel (petroleum, natural gas and coal) which have serious environmental implications. Air conditioners are becoming more commonly used load power consumption metrics and are a major strain on energy demands especially in tropical rainforest climate countries like Nigeria. The photovoltaic electricity is a clean and sustainable energy. In this paper, we present a techno-economic feasibility study for solar powered air conditioning system in Nigeria. The method used made a correlation of four alternatives of PV to load ratio factor being investigated. In the first instance, the PV system supplied 50% of the energy to the loads. In the second method, the PV system supplied 75% of the energy to the loads. Thirdly, the PV system supplied 100% of the energy to the loads. Fourthly, on a final design, the PV system supplied 125% of the energy to the loads. In the first two case the PV energy generated is used solely to power the air conditioner system. In the last two design, there is excess electrical energy which is proposed to be sold to the Nigeria grid system especially if the grid system optimized and broken down into smaller grid array within 0.3$ feed-in tariff. The best alternative method is the grid-connected PV system with 125% capacity factor which is chosen due to its short payback time period as well as high profit rate over the lifetime of the project.

Sosialisasi Tumbuhan Nelambo Suon (Rubiaceae) Sebagai Pencegah Penyakit Malaria Berdasarkan Kearifan lokal Pada Masyarakat Distrik Walma dan Heriapini, Yahukimo

Nelambo Suon (Rubiaceae) is one of the traditional antimalarial medicinal plants used by people in Walma and Heriapini Districts, Yahukimo. This plant lives on cliffs and grows wild in home yards to tropical rainforests. The purpose of this activity is to provide education to the community about how to use the Nelambo Suon plant as a prevention of malaria. The activity was carried out in Perumnas 4 Waena, Jayapura City to people from Walma and Heriapini districts who were studying further. The method of this activity is Focus Group Discussion (FGD) and training in making medicinal herbs to prevent and treat malaria. Activities were carried out in August-October 2022, which were carried out well and smoothly. The results of the activity showed that there was an increase in understanding in the utilization of Nelambo Suon plants up to an average of 78.57% (74.44% to 94.74%). This increase is expected to be able to maintain the understanding and motivation of the community to continue to pay attention and utilize the Nelambo Suon plant as a traditional medicine to prevent and cure malaria.

Deep-learning-derived planetary boundary layer height from conventional meteorological measurements

Abstract. The planetary boundary layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, which can estimate PBLH by integrating the morning temperature profiles and surface meteorological observations. The DNN model is developed by leveraging a rich dataset of PBLH derived from long-standing radiosonde records augmented with high-resolution micro-pulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden-layer structures, which collectively yield a robust 27-year PBLH dataset over the southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micro-pulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (Green Ocean Amazon; tropical rainforest) and CACTI (Cloud, Aerosol, and Complex Terrain Interactions; middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary layer processes with implications for improving the representation of PBL in weather forecasting and climate modeling.

A systematic map of evidence on the relationship between agricultural production and biodiversity in tropical rainforest areas

BackgroundThe tropical rainforest biome plays a significant role in providing habitats for terrestrial biodiversity and delivering ecosystem service values, contributing to agricultural production. However, the increasing demand for tropical commodities with high economic value threatens this humid ecosystem and its biodiversity. To our knowledge, no studies have systematically mapped the relationship between the impacts of agricultural production on biodiversity and the effects of biodiversity on agricultural production in tropical rainforest areas.MethodsSince we were interested in systematically mapping the evidence measuring the impact of tropical agriculture on biodiversity (Map 1), and the vice versa relations, the influence of biodiversity on tropical agriculture production (Map 2), we developed a respective set of search strings, eligibility criteria, and subsequently performed independent searching, screening, and data coding processes. We searched articles from six peer-reviewed databases and 22 gray literature sources. Articles were screened based on the inclusion criteria at the title, abstract, and full-text levels. Individual articles that passed full-text screening were coded and synthesized to create heatmaps. Selected information of interest was also extracted and visualized in the graphics which were clustered based on the year of publication, geographical distribution, type of rainforest, exposure, outcome, farm commodity, and study comparators.Review findingsTwo heatmaps were generated from a contrasting number of references, with heatmap 1 extracted from 222 studies and heatmap 2 derived from 10 times fewer references (n = 20). In heatmap 1, impacts of land conversion to aboveground biodiversity and wild species and ecosystem functions in natural ecosystems were the most common relationships examined, with 115 articles and 62 articles, respectively. Conversely, heatmap 2 showed evidence that focused predominantly on the examination of the links between the impacts of genetic resource diversity on environmental factors and soil management in tropical agricultural production, with four articles each exploring these relations.ConclusionsThese systematic maps reveal that while studies investigating the impacts of tropical agricultural production on biodiversity were abundant, studies examining the impacts of biodiversity on tropical agricultural production were lacking despite both systematic maps experiencing an increasing trend of publication during 2000–2020. Map 1 emphasized the examination of the effects of land conversion on aboveground biodiversity, and on wild species and ecosystem functions. Map 2 highlighted the influence of crop genetic resources on environmental factors, and on soil management as the most frequently studied. The evidence cluster identified here can be the starting point for further systematic review study (to assess, for example, their cause–effect significance).

Advances in Retrofitting Strategies for Energy Efficiency in Tropical Climates: A Systematic Review and Analysis

The global construction industry significantly contributes to energy consumption and greenhouse gas emissions, necessitating immediate action for sustainable development. Recognizing the impact of buildings on emissions, the United Nations has set ambitious energy-related goals for 2030. Retrofitting buildings emerges as a strategic method for reducing energy consumption, offering lower environmental impact and life cycle costs. However, retrofitting is a complex process influenced by diverse factors such as policies, available resources, techniques, building-specific data, and uncertainties. Thus, this paper reviews the existing literature on retrofitting strategies for tropical and humid climates to identify effective approaches for enhancing energy efficiency, thermal comfort, and overall building performance in these regions. Through comprehensive analyses, including bibliometric analysis using VOSviewer version 1.6.18 and systematic assessments, this study investigates various retrofitting strategies. This study categorizes tropical climates into Af (Tropical Rainforest Climate) and Aw (Tropical Savanna Climate) based on the Köppen climate classification. It reveals distinct emphases, with Af climates concentrating on office buildings and Aw climates prioritizing residential structures. Passive strategies were predominantly favored in office buildings, with glazing being the most commonly implemented approach. Residential structures, on the other hand, adopted a combination of passive strategies such as phase change materials along with active methods like appliance replacement. Educational buildings tended to rely on passive strategies, including roof covers, shading, and glazing. The absence of specific cost values underscores the importance of establishing baseline metrics, revealing significant challenges in retrofit techniques. This study further highlights an opportunity to explore passive methods in educational buildings, stressing the need for comprehensive guidelines, especially in institutional settings. Moreover, it emphasizes the urgency for ambitious regulations to address carbon emissions and optimize energy efficiency in tropical climates.

Fire in the rainforest: A 3200‐year history of fire in a West Kalimantan, Indonesia, tropical rainforest

AbstractDespite its perceived historical rarity, fire is an important disturbance in tropical rainforests. Very large rainforest fires have been observed multiple times in recent decades, often during years of strong El Niño‐Southern Oscillation droughts. Fire in rainforest has major short‐term consequences for humans and wildlife by converting forest to fire‐prone fern, shrub, and grass, but the long‐term effects remain to be seen. Borneo's indigenous groups have been using fire to clear land for centuries, yet the prevalence and spatial patterns of premodern fire across forest types in Borneo are not well understood. This research set out to reconstruct fire in a 1500‐ha primary rainforest spanning 800 m of elevation in Indonesian Borneo with the goal of elucidating the role humans have played in rainforest fire. We found that humans played an important role in the occurrence of fire in recent centuries. Evidence of fire—charcoal >2 mm—is more abundant in forest types where humans would be more likely to live and/or practice swidden agriculture. However, pyrogenic material is ubiquitous across the study area, showing that all forest types have experienced fire. A set of 50 radiocarbon dates showed that in lowland areas—where human‐caused fire is most likely—fire occurred throughout the last 3200 years, peaking 1300–1600 ce. The upland areas lacked evidence of fire before 1250 ce but otherwise had a similar pattern to the lowlands. The period of high fire coincides with regional demographic changes as well as regional droughts documented elsewhere in Southeast Asia. In upland areas, fires likely burned only under regional drought when fires could more easily spread upslope. Although forest plot studies at this site show little structural evidence of past fires, tree diversity is lower than expected in the most burned areas (alluvial benches). Thus, our results suggest that land clearance was a major source of fire, but the current intact state of these rainforests indicates that they were largely resilient to fires and land use hundreds of years ago. Recent fires mirror patterns of fire spread that occurred hundreds of years ago, though their severity and extent are likely much greater.

Comparing the allometric model to machine learning algorithms for aboveground biomass estimation in tropical forests

Estimating aboveground biomass (AGB) pools is critical for understanding the structural characteristics of forest ecosystems, as the quantitative analysis of biomass contributes to a better understanding of carbon sequestration and in studying the productivity within forest ecosystems. A more precise estimation of AGB is necessary for the estimation of the amount of carbon stored in an ecosystem that is needed for the valuation of the ecosystem services. Though regression models have been used previously for both tree-level and stand-level biomass estimations, supervised machine learning models have rarely been put to test in field-based estimations of AGB. This study was done in the tropical forests of Northeast India (two reserve forests in Tripura) to compare the allometric performance of weighted nonlinear regression model (NLM) to random forest regression (RFR), extreme gradient boost regression (XGB), and support vector machine regression (SVR) in estimating tree-level AGB. Due to their ease of measurement in field conditions and ensuring practical use, tree diameter at breast height (DBH) and tree height (H) were used as the independent variables to train the models. 506 trees representing 21 local tree species were inventoried. Then, the four models (NLM, RFR, XGB, and SVM) were trained separately on the data and compared to find an optimal method to estimate AGB using modeling efficiency of fit (MEfit) and Root Mean Squared Error (RMSE). The models were then validated using the predicted residual error sum of squares (PRESS) statistics. The best fit model in our study was using RFR, with a high MEfit (0.95–0.99), low RMSE (63.10–132.39 kg), and outperforming all other methods in the PRESS statistics, with the highest modeling efficiency of prediction (0.94–0.99) and lowest mean of absolute PRESS residuals (34.99–78.23). The results from Northeast India presented here provide preliminary evidence that RFR could be a reliable method for determining the field-level carbon stock and understanding the biomass dynamics for evergreen and moist deciduous tropical forests. The model accuracy may be constrained by a limited number of variables chosen to suit practical use in the field, and incorporating additional tree-level or stand-level variables such as crown diameter and stand basal area could enhance the robustness and generalizability of AGB estimation.

Patterns and inferred causes of liana mortality in a tropical forest.

Lianas are major contributors to tropical forest dynamics, yet we know little about their mortality. Using overlapping censuses of the lianas and trees across a 50 ha stand of moist tropical forest, we contrasted community-wide patterns of liana mortality with relatively well-studied patterns of tree mortality to quantify patterns of liana death and identify contributing factors. Liana mortality rates were 172% higher than tree mortality rates, but species-level mortality rates of lianas were similar to trees with 'fast' life-history strategies and both growth forms exhibited similar spatial and size-dependent patterns. The mortality rates of liana saplings (<2.1 cm in diameter), which represent about 50% of liana individuals, decreased with increasing disturbance severity and remained consistently low during post-disturbance stand thinning. In contrast, larger liana individuals and trees of all sizes had elevated mortality rates in response to disturbance and their mortality rates decreased over time since disturbance. Within undisturbed forest patches, liana mortality rates increased with increasing soil fertility in a manner similar to trees. The distinct responses of liana saplings to disturbance appeared to distinguish liana mortality from that of trees, whereas similarities in their patterns of death suggest that there are common drivers of woody plant mortality.