Indonesian Institute of Sciences

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Mangrove species are uniquely adapted to tropical and subtropical coasts, and although relatively low in number of species, mangrove forests provide at least US $1.6 billion each year in ecosystem services and support coastal livelihoods worldwide. Globally, mangrove areas are declining rapidly as they are cleared for coastal development and aquaculture and logged for timber and fuel production. Little is known about the effects of mangrove area loss on individual mangrove species and local or regional populations. To address this gap, species-specific information on global distribution, population status, life history traits, and major threats were compiled for each of the 70 known species of mangroves. Each species' probability of extinction was assessed under the Categories and Criteria of the IUCN Red List of Threatened Species. Eleven of the 70 mangrove species (16%) are at elevated threat of extinction. Particular areas of geographical concern include the Atlantic and Pacific coasts of Central America, where as many as 40% of mangroves species present are threatened with extinction. Across the globe, mangrove species found primarily in the high intertidal and upstream estuarine zones, which often have specific freshwater requirements and patchy distributions, are the most threatened because they are often the first cleared for development of aquaculture and agriculture. The loss of mangrove species will have devastating economic and environmental consequences for coastal communities, especially in those areas with low mangrove diversity and high mangrove area or species loss. Several species at high risk of extinction may disappear well before the next decade if existing protective measures are not enforced.

The conservation status of 845 zooxanthellate reef-building coral species was assessed by using International Union for Conservation of Nature Red List Criteria. Of the 704 species that could be assigned conservation status, 32.8% are in categories with elevated risk of extinction. Declines in abundance are associated with bleaching and diseases driven by elevated sea surface temperatures, with extinction risk further exacerbated by local-scale anthropogenic disturbances. The proportion of corals threatened with extinction has increased dramatically in recent decades and exceeds that of most terrestrial groups. The Caribbean has the largest proportion of corals in high extinction risk categories, whereas the Coral Triangle (western Pacific) has the highest proportion of species in all categories of elevated extinction risk. Our results emphasize the widespread plight of coral reefs and the urgent need to enact conservation measures.

Abstract Aim Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better‐surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet V iverra tangalunga in Borneo. Location Borneo, Southeast Asia. Methods We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range‐restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north‐eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas. Results Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased. Main Conclusions We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.

The world is under pressure from the novel COVID-19 pandemic. Indonesia is the fourth most populous country in the world and predicted to be affected significantly over a longer time period. Our paper aims to provide detailed reporting and analyses of the present rapid responses to COVID-19, between January and March 2020, in Indonesia. We particularly highlight responses taken by the governments, non-government organisations and the community. We outline gaps and limitations in the responses, based on our rapid analysis of media contents, from government speeches and reports, social and mass media platforms. We present five recommendations toward more rapid, effective, and comprehensive responses.

Over the past few years, nanocellulose (NC), cellulose in the form of nanostructures, has been proved to be one of the most prominent green materials of modern times. NC materials have gained growing interests owing to their attractive and excellent characteristics such as abundance, high aspect ratio, better mechanical properties, renewability, and biocompatibility. The abundant hydroxyl functional groups allow a wide range of functionalizations via chemical reactions, leading to developing various materials with tunable features. In this review, recent advances in the preparation, modification and emerging application of nanocellulose, especially cellulose nanocrystals (CNCs), are described and discussed based on the analysis of the latest investigations (particularly for the reports of the past three years). We start with a concise background of cellulose, its structural organization as well as the nomenclature of cellulose nanomaterials for beginners in this field. Then, different experimental procedures for the production of nanocelluloses, their properties, and functionalization approaches were elaborated. Furthermore, a number of recent and emerging uses of nanocellulose in nanocomposites, Pickering emulsifiers, wood adhesives, wastewater treatment, as well as in new evolving biomedical applications are presented. Finally, the challenges and opportunities of NC-based emerging materials are discussed.

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth's continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

Understanding the basic properties of natural fibers is important to determine the optimal intended uses for instance as high-quality bio-composite raw material. This review describes the characteristics, and potential uses of some natural fibers in order to improve their sustainability and economic values. The natural fibers have low density and high strength to weight ratio and reduction make them potential as light weight composite and reinforcement materials. The microstructure and chemical compositions of fibers affect the mechanical properties with the fiber cross-sectional area is the most variable influencing the fiber strength. Natural fibers are easy to absorb water due to the presence of hemicellulose that give hydrophilic properties make them less compatible in the interaction with matrix with hydrophobicity properties. Higher cellulose content and crystallinity tend to result better strength properties of fiber while lignin is since versa. Besides that, fiber anatomical characteristics vary between different and same species that affect on the density and mechanical properties. The other factors namely environmental conditions, method of transportation, storage time and conditions, and fiber extraction affect the size and quality of the natural fibers.

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Abstract At sufficiently high temperature and energy density, nuclear matter undergoes a transition to a phase in which quarks and gluons are not confined: the quark–gluon plasma (QGP) 1 . Such an exotic state of strongly interacting quantum chromodynamics matter is produced in the laboratory in heavy nuclei high-energy collisions, where an enhanced production of strange hadrons is observed 2,3,4,5,6 . Strangeness enhancement, originally proposed as a signature of QGP formation in nuclear collisions 7 , is more pronounced for multi-strange baryons. Several effects typical of heavy-ion phenomenology have been observed in high-multiplicity proton–proton (pp) collisions 8,9 , but the enhanced production of multi-strange particles has not been reported so far. Here we present the first observation of strangeness enhancement in high-multiplicity proton–proton collisions. We find that the integrated yields of strange and multi-strange particles, relative to pions, increases significantly with the event charged-particle multiplicity. The measurements are in remarkable agreement with the p–Pb collision results 10,11 , indicating that the phenomenon is related to the final system created in the collision. In high-multiplicity events strangeness production reaches values similar to those observed in Pb–Pb collisions, where a QGP is formed.

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

The era of climate change involves the mutation of systems beyond 20th century anthropomorphic models and has stood, until recently, outside representation or address. Understood in a broad and critical sense, climate change concerns material agencies that impact on biomass and energy, erased borders and microbial invention, geological and nanographic time, and extinction events. The possibility of extinction has always been a latent figure in the textual production and archives; but the current sense of depletion, decay, mutation and exhaustion calls for new modes of address, new styles of publishing and authoring, and new formats and speeds of distribution. As the pressures and re-alignments of this re-arrangement occur, so must the critical languages and conceptual templates, political premises and definitions of "life." There is a particular need to publish in a timely fashion experimental monographs that redefine the boundaries of disciplinary fields, rhetorical invasions, the interface of conceptual and scientific languages, and geomorphic and geopolitical interventions. Critical Climate Change is oriented, in this general manner, toward the epistemo-political mutations that correspond to the temporalities of terrestrial mutation.

Continuously recording Global Positioning System stations near the 28 March 2005 rupture of the Sunda megathrust [moment magnitude (Mw) 8.7] show that the earthquake triggered aseismic frictional afterslip on the subduction megathrust, with a major fraction of this slip in the up-dip direction from the main rupture. Eleven months after the main shock, afterslip continues at rates several times the average interseismic rate, resulting in deformation equivalent to at least a M(w) 8.2 earthquake. In general, along-strike variations in frictional behavior appear to persist over multiple earthquake cycles. Aftershocks cluster along the boundary between the region of coseismic slip and the up-dip creeping zone. We observe that the cumulative number of aftershocks increases linearly with postseismic displacements; this finding suggests that the temporal evolution of aftershocks is governed by afterslip.

Conductivity (EC) and total dissolved solids (TDS) are water quality parameters, which are used to describe salinity level. These two parameters are correlated and usually expressed by a simple equation: TDS = k EC (in 25 °C). The process of obtaining TDS from water sample is more complex than that of EC. Meanwhile, TDS analysis is very important because it can illustrate groundwater quality, particularly in understanding the effect of seawater intrusion better than EC analysis. These conditions make research in revealing TDS/EC ratios interesting to do. By finding the ratio value, TDS concentration can be measured easily from EC value. However, the ratio cannot be defined easily. Previous research results have found that the correlation between TDS and EC are not always linear. The ratio is not only strongly influenced by salinity contents, but also by materials contents. Furthermore, the analysis of TDS concentration from EC value can be used to give an overview of water quality. For more precision, TDS concentrations need to be analyzed using the gravimetric method in the laboratory.

Summary In coastal and estuarine systems, foundation species like seagrasses, mangroves, saltmarshes or corals provide important ecosystem services. Seagrasses are globally declining and their reintroduction has been shown to restore ecosystem functions. However, seagrass restoration is often challenging, given the dynamic and stressful environment that seagrasses often grow in. From our world‐wide meta‐analysis of seagrass restoration trials (1786 trials), we describe general features and best practice for seagrass restoration. We confirm that removal of threats is important prior to replanting. Reduced water quality (mainly eutrophication), and construction activities led to poorer restoration success than, for instance, dredging, local direct impact and natural causes. Proximity to and recovery of donor beds were positively correlated with trial performance. Planting techniques can influence restoration success. The meta‐analysis shows that both trial survival and seagrass population growth rate in trials that survived are positively affected by the number of plants or seeds initially transplanted. This relationship between restoration scale and restoration success was not related to trial characteristics of the initial restoration. The majority of the seagrass restoration trials have been very small, which may explain the low overall trial survival rate (i.e. estimated 37%). Successful regrowth of the foundation seagrass species appears to require crossing a minimum threshold of reintroduced individuals. Our study provides the first global field evidence for the requirement of a critical mass for recovery, which may also hold for other foundation species showing strong positive feedback to a dynamic environment. Synthesis and applications . For effective restoration of seagrass foundation species in its typically dynamic, stressful environment, introduction of large numbers is seen to be beneficial and probably serves two purposes. First, a large‐scale planting increases trial survival – large numbers ensure the spread of risks, which is needed to overcome high natural variability. Secondly, a large‐scale trial increases population growth rate by enhancing self‐sustaining feedback, which is generally found in foundation species in stressful environments such as seagrass beds. Thus, by careful site selection and applying appropriate techniques, spreading of risks and enhancing self‐sustaining feedback in concert increase success of seagrass restoration.

Abstract Aim Large trees (d.b.h. ≥ 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan‐tropical scales. Location Pan‐tropical. Methods Aboveground biomass ( AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights ( AICc ‐wi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB /density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c . 70% of the variation in pan‐tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) ± 105.0 ( SD ) M g ha −1 ] versus Palaeotropical forests (Africa 418.3 ± 91.8 M g ha −1 ; Asia 393.3 ± 109.3 M g ha −1 ). Pan‐tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in‐depth analyses of the community dynamics of large trees.

Previous studies have described the development of control methods against bacterial wilt diseases caused by Ralstonia solanacearum. This review focused on recent advances in control measures, such as biological, physical, chemical, cultural, and integral measures, as well as biocontrol efficacy and suppression mechanisms. Biological control agents (BCAs) have been dominated by bacteria (90%) and fungi (10%). Avirulent strains of R. solanacearum, Pseudomonas spp., Bacillus spp., and Streptomyces spp. are well-known BCAs. New or uncommon BCAs have also been identified such as Acinetobacter sp., Burkholderia sp., and Paenibacillus sp. Inoculation methods for BCAs affect biocontrol efficacy, such as pouring or drenching soil, dipping of roots, and seed coatings. The amendment of different organic matter, such as plant residue, animal waste, and simple organic compounds, have frequently been reported to suppress bacterial wilt diseases. The combined application of BCAs and their substrates was shown to more effectively suppress bacterial wilt in the tomato. Suppression mechanisms are typically attributed to the antibacterial metabolites produced by BCAs or those present in natural products; however, the number of studies related to host resistance to the pathogen is increasing. Enhanced/modified soil microbial communities are also indirectly involved in disease suppression. New promising types of control measures include biological soil disinfection using substrates that release volatile compounds. This review described recent advances in different control measures. We focused on the importance of integrated pest management (IPM) for bacterial wilt diseases.

The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Using improved theoretical calculations of the decay form factors in the light cone QCD sum rule approach, we investigate the decay rates, dilepton invariant mass spectra and the forward-backward (FB) asymmetry in the decays $\stackrel{\ensuremath{\rightarrow}}{B}{(K,K}^{*}{)l}^{+}{l}^{\ensuremath{-}}$ ${(l}^{\ifmmode\pm\else\textpm\fi{}}{=e}^{\ifmmode\pm\else\textpm\fi{}},{\ensuremath{\mu}}^{\ifmmode\pm\else\textpm\fi{}},{\ensuremath{\tau}}^{\ifmmode\pm\else\textpm\fi{}})$ in the standard model (SM) and a number of popular variants of the supersymmetric (SUSY) models. Theoretical precision on the differential decay rates and FB asymmetry is estimated in these theories taking into account various parametric uncertainties. We show that existing data on $\stackrel{\ensuremath{\rightarrow}}{B}{X}_{s}\ensuremath{\gamma}$ and the experimental upper limit on the branching ratio $\mathcal{B}(\stackrel{\ensuremath{\rightarrow}}{B}{K}^{*}{\ensuremath{\mu}}^{+}{\ensuremath{\mu}}^{\ensuremath{-}})$ provide interesting bounds on the coefficients of the underlying effective theory. We argue that the FB asymmetry in $\stackrel{\ensuremath{\rightarrow}}{B}{K}^{*}{l}^{+}{l}^{\ensuremath{-}}$ constitutes a precision test of the SM and its measurement in forthcoming experiments may reveal new physics. In particular, the presently allowed large-$\mathrm{tan}\ensuremath{\beta}$ solutions in SUGRA models, as well as more general flavor-violating SUSY models, yield FB asymmetries which are characteristically different from the corresponding ones in the SM.