Minuartia nifensis Mc Neill belongs to Caryophyllaceae family. It is distributed only on Nif Mountain. In order to prepare the basis for the ex-situ and in-situ protection principles, ecological data was collected as well as population size and distributon areas were recorded in an earlier study. Present study investigates the M. nifensis anatomically, morphologically and cytologically, with the aim of improving the description of this endemic species and establishing the basic information for future biosystematic studies.
To advance our limited knowledge of global mosquito biogeography, we analyzed country occurrence records from the Systematic Catalog of the Culicidae (http://www.mosquitocatalog. org/main.asp), and we present world maps of species richness and endemism. A latitudinal biodiversity gradient was observed, with species richness increasing toward the equator. A linear log-log species (y)-area (x) relationship (SAR) was found that we used to compare observed and expected species densities for each country. Brazil, Indonesia, Malaysia, and Thailand had the highest numbers of species, and Brazil also had the highest taxonomic output and number of type locations. Brazil, Australia, the Philippines, and Indonesia had the highest numbers of endemic species, but excluding small island countries, Panama, French Guiana, Malaysia, and Costa Rica had the highest densities of total species and endemic species. Globally, 50% of mosquito species are endemic. Island countries had higher total number of species and higher number of endemic species than mainland countries of similar size, but the slope of the SAR was similar for island and mainland countries. Islands also had higher numbers of publications and type locations, possibly due to greater sampling effort and/or species endemism on islands. The taxonomic output was lowest for some countries in Africa and the Middle East. A consideration of country estimates of past sampling effort and species richness and endemism is proposed to guide mosquito biodiversity surveys. For species groups, we show that the number of species of Anopheles subgenus Anopheles varies with those of subgenus Cellia in a consistent manner between countries depending on the region. This pattern is discussed in relation to hypotheses about the historical biogeography and ecology of this medically important genus. Spatial analysis of country species records offers new insight into global patterns of mosquito biodiversity and survey history.
Population surveys and species recognition for roosting bats are either based on capture, sight or optical-mechanical count methods. However, these methods are intrusive, are tedious and, at best, provide only statistical estimations. Here, we demonstrated the successful use of a terrestrial Light Detection and Ranging (LIDAR) laser scanner for remotely identifying and determining the exact population of roosting bats in caves. LIDAR accurately captured the 3D features of the roosting bats and their spatial distribution patterns in minimal light. The high-resolution model of the cave enabled an exact count of the visibly differentiated Hipposideros larvatus and their roosting pattern within the 3D topology of the cave. We anticipate that the development of LIDAR will open up new research possibilities by allowing researchers to study roosting behaviour within the topographical context of a cave's internal surface, thus facilitating rigorous quantitative characterisations of cave roosting behaviour.
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
A total of 73 localities covering 4,894 premises and 26, 712 breeding habitats were surveyed in 1980 to determine and establish the density and distribution pattern of Aedes aegypti and Aedes albopictus in Sarawak. A similar pattern has been observed in the density of the Aedes aegypti and Aedes albopictus. The number of houses positive with Aedes larvae were found to be highest in the coastal areas followed by the inland rural areas. The Aedes aegypti Breteau Index (B.I.) of 0-525 in the coastal areas is the highest followed by 0-207.5 in the inland rural areas. The study undertaken has now revealed that both the Aedes aegypti and Aedes albopictus are widespread in the State.
This paper attempts to ascertain the impacts of population density on the spread and severity of COVID-19 in Malaysia. Besides describing the spatio-temporal contagion risk of the virus, ultimately, it seeks to test the hypothesis that higher population density results in exacerbated COVID-19 virulence in the community. The population density of 143 districts in Malaysia, as per data from Malaysia's 2010 population census, was plotted against cumulative COVID-19 cases and infection rates of COVID-19 cases, which were obtained from Malaysia's Ministry of Health official website. The data of these three variables were collected between 19 January 2020 and 31 December 2020. Based on the observations, districts that have high population densities and are highly inter-connected with neighbouring districts, whether geographically, socio-economically, or infrastructurally, tend to experience spikes in COVID-19 cases within weeks of each other. Using a parametric approach of the Pearson correlation, population density was found to have a moderately strong relationship to cumulative COVID-19 cases (p-value of 0.000 and R2 of 0.415) and a weak relationship to COVID-19 infection rates (p-value of 0.005 and R2 of 0.047). Consequently, we provide several non-pharmaceutical lessons, including urban planning strategies, as passive containment measures that may better support disease interventions against future contagious diseases.
The rapid transmission of highly contagious infectious diseases within communities can yield potential hotspots or clusters across geographies. For COVID-19, the impact of population density on transmission models demonstrates mixed findings. This study aims to determine the correlations between population density, clusters, and COVID-19 incidence across districts and regions in Malaysia. This countrywide ecological study was conducted between 22 January 2021 and 4 February 2021 involving 51,476 active COVID-19 cases during Malaysia's third wave of the pandemic, prior to the reimplementation of lockdowns. Population data from multiple sources was aggregated and spatial analytics were performed to visualize distributional choropleths of COVID-19 cases in relation to population density. Hierarchical cluster analysis was used to synthesize dendrograms to demarcate potential clusters against population density. Region-wise correlations and simple linear regression models were deduced to observe the strength of the correlations and the propagation effects of COVID-19 infections relative to population density. Distributional heats in choropleths and cluster analysis showed that districts with a high number of inhabitants and a high population density had a greater number of cases in proportion to the population in that area. The Central region had the strongest correlation between COVID-19 cases and population density (r = 0.912; 95% CI 0.911, 0.913; p < 0.001). The propagation effect and the spread of disease was greater in urbanized districts or cities. Population density is an important factor for the spread of COVID-19 in Malaysia.
Although dengue haemorrhagic fever is widely established in South-East Asia, no cases have been reported from Borneo. In order to help to assess whether the infection could become established in Borneo, a survey was made, using the single-larva collection method, of the distribution and prevalence of the principal vector, Aedes aegypti, in Sabah and in a few towns and villages of Brunei and Sarawak. In addition, the prevalence of Ae. aegypti was compared with that of certain other species of Aedes.Ae. aegypti was found to be well established in the north, east, and south-west of Sabah but to be absent from almost all of the west coast. It was either uncommon in, or absent from, several small coastal villages; in others, very high Breteau indices were recorded. No reasonable explanation for this discontinuous distribution can be suggested. Large numbers of potential larval habitats were found, giving reason to believe that Ae. aegypti will spread further within these territories.
For an economy to excel in growth, there is usually a trade-off between financial development and environment deterioration. For a country like Singapore, which has shown a radical growth and is known for its population density, it is important to explore the role of green technology innovation in the pursuit of economic excellence with the least possible cost to the environment. By employing the novel bootstrap autoregressive-distributed lag (BARDL) technique using a time series data from 1990 to 2018, the results reported a positive and significant relationship of green technology innovation with economic growth and negative and significant relationship with carbon emissions in both long run and short run. Based on the findings, several managerial implications were discussed, whereas based on the limitations, directions for future researchers are also given.
The coastal zones of Small Island States are hotspots of human habitation and economic endeavour. In the Pacific region, as elsewhere, there are large gaps in understandings of the exposure and vulnerability of people in coastal zones. The 22 Pacific Countries and Territories (PICTs) are poorly represented in global analyses of vulnerability to seaward risks. We combine several data sources to estimate populations to zones 1, 5 and 10 km from the coastline in each of the PICTs. Regional patterns in the proximity of Pacific people to the coast are dominated by Papua New Guinea. Overall, ca. half the population of the Pacific resides within 10 km of the coast but this jumps to 97% when Papua New Guinea is excluded. A quarter of Pacific people live within 1 km of the coast, but without PNG this increases to slightly more than half. Excluding PNG, 90% of Pacific Islanders live within 5 km of the coast. All of the population in the coral atoll nations of Tokelau and Tuvalu live within a km of the ocean. Results using two global datasets, the SEDAC-CIESIN Gridded Population of the World v4 (GPWv4) and the Oak Ridge National Laboratory Landscan differed: Landscan under-dispersed population, overestimating numbers in urban centres and underestimating population in rural areas and GPWv4 over-dispersed the population. In addition to errors introduced by the allocation models of the two methods, errors were introduced as artefacts of allocating households to 1 km x 1 km grid cell data (30 arc-seconds) to polygons. The limited utility of LandScan and GPWv4 in advancing this analysis may be overcome with more spatially resolved census data and the inclusion of elevation above sea level as an important dimension of vulnerability.
Sympatric gibbon species Hylobates lar and H. syndactylus were censused on a mountain in Malaya (West Malaysia). Habitat quality was assessed between 380- and 1,525-m altitudes. H. syndactylus was found to occur up to altitudes higher than does H. lar, and this is discussed with reference to the two species' divergent foraging strategies indicated by previous research. It is suggested that gibbons are restricted in their altitudinal range by an increasingly unfavourable ratio of food consumed to energy expended in its location, caused by a reduced food-source density and more difficult terrain at higher elevations.
Bacterial cells sense their population density and respond accordingly by producing various signal molecules to the surrounding environments thereby trigger a plethora of gene expression. This regulatory pathway is termed quorum sensing (QS). Plenty of bacterial virulence factors are controlled by QS or QS-mediated regulatory systems and QS signal molecules (QSSMs) play crucial roles in bacterial signaling transduction. Moreover, bacterial QSSMs were shown to interfere with host cell signaling and modulate host immune responses. QSSMs not only regulate the expression of bacterial virulence factors but themselves act in the modulation of host biology that can be potential therapeutic targets.
Great apes are threatened with extinction, but precise information about the distribution and size of most populations is currently lacking. We conducted orangutan nest counts in the Malaysian state of Sabah (North Borneo), using a combination of ground and helicopter surveys, and provided a way to estimate the current distribution and size of the populations living throughout the entire state. We show that the number of nests detected during aerial surveys is directly related to the estimated true animal density and that a helicopter is an efficient tool to provide robust estimates of orangutan numbers. Our results reveal that with a total estimated population size of about 11,000 individuals, Sabah is one of the main strongholds for orangutans in North Borneo. More than 60% of orangutans living in the state occur outside protected areas, in production forests that have been through several rounds of logging extraction and are still exploited for timber. The role of exploited forests clearly merits further investigation for orangutan conservation in Sabah.
A new topic of Zero Energy Building (ZEB) is getting famous in research area
because of its goal of reaching zero carbon emission and low building cost. Renewable
energy system is one of the ideas to achieve the objective of ZEB. Genetic Algorithm (GA)
is widely used in many research areas due to its capability to escape from a local minimal
to obtain a better solution. In our study, GA is chosen in sizing optimization of the
number of photovoltaic, wind turbine and battery of a hybrid photovoltaic-wind-battery
system. The aim is to minimize the total annual cost (TAC) of the hybrid energy system
towards the low cost concept of ZEB. Two GA parameters, which are generation number
and population size, have been analysed and optimized in order to meet the minimum
TAC. The results show that the GA is efficient in minimizing cost function of a hybrid
photovoltaic-wind-battery system with its robustness property.
Mite foci were fenced above and below ground to prevent the entry of host animals and to prevent the migration of mites within the soil. Weekly counts were made over a period of thirty weeks with larvae being collected at the beginning and end of the study, but not during the intervening period of hot, dry weather. Post-larval forms can survive for long periods and mite foci can remain productive without being visited by the host animals. Mite foci may be missed by normal survey methods during hot, dry weather.
The integration of Bayesian analysis into existing great ape survey methods could be used to generate precise and reliable population estimates of Bornean orang-utans. We used the Marked Nest Count (MNC) method to count new orang-utan nests at seven previously undocumented study sites in Sarawak, Malaysia. Our survey teams marked new nests on the first survey and revisited the plots on two more occasions; after about 21 and 42 days respectively. We used the N-mixture models to integrate suitability, abundance and detection models which account for zero inflation and imperfect detection for the analysis. The result was a combined estimate of 355 orang-utans with the 95% highest density interval (HDI) of 135 to 602 individuals. We visually inspected the posterior distributions of our parameters and compared precisions between study sites. We subsequently assess the strength or reliability of the generated estimates using identifiability tests. Only three out of the seven estimates had <35% overlap to indicate strong reliability. We discussed the limitations and advantages of our study design, and made recommendations to improve the sampling scheme. Over the course of this research, two of the study sites were gazetted as extensions to the Lanjak-Entimau Wildlife Sanctuary for orang-utan conservation.
The Rajah Brooke's Birdwing, Trogonoptera brookiana, is a large, iconic butterfly that is facing heavy commercial exploitation and habitat loss. Males of some subspecies exhibit puddling behavior. A method of conservation monitoring was developed for subspecies albescens in Ulu Geroh, Peninsular Malaysia, where the males consistently puddle in single-species aggregations at stable geothermal springs, reaching well over 300 individuals when the population is at its highest. Digital photography was used to conduct counts of numbers of males puddling. The numbers of birdwings puddling were significantly correlated with counts of birdwings in flight, but were much higher. The numbers puddling during the peak hour were correlated with numbers puddling throughout the day and could be predicted using the numbers puddling at an alternative hour, enabling flexibility in the time of counts. Average counts for three images taken at each puddle at three peak hours between 1400-1600 hours over 2-3 days were used as a monthly population index. The numbers puddling were positively associated with higher relative humidity and brightness during monitoring hours. Monthly counts of birdwings from monitoring of puddles over a period of two years are presented. The minimum effort required for a monitoring program using counts of puddling males is discussed, as well as the potential of using the method to monitor other species of puddling butterflies.
Migration is typically associated with risk and uncertainty at the population level, but little is known about its cost-benefit trade-offs at the species level. Migratory insects in particular often exhibit strong demographic fluctuations due to local bottlenecks and outbreaks. Here, we use genomic data to investigate levels of heterozygosity and long-term population size dynamics in migratory insects, as an alternative to classical local and short-term approaches such as regional field monitoring. We analyse whole-genome sequences from 97 Lepidoptera species and show that individuals of migratory species have significantly higher levels of genome-wide heterozygosity, a proxy for effective population size, than do nonmigratory species. Also, we contribute whole-genome data for one of the most emblematic insect migratory species, the painted lady butterfly (Vanessa cardui), sampled across its worldwide distributional range. This species exhibits one of the highest levels of genomic heterozygosity described in Lepidoptera (2.95 ± 0.15%). Coalescent modelling (PSMC) shows historical demographic stability in V. cardui, and high effective population size estimates of 2-20 million individuals 10,000 years ago. The study reveals that the high risks associated with migration and local environmental fluctuations do not seem to decrease overall genetic diversity and demographic stability in migratory Lepidoptera. We propose a "compensatory" demographic model for migratory r-strategist organisms in which local bottlenecks are counterbalanced by reproductive success elsewhere within their typically large distributional ranges. Our findings highlight that the boundaries of populations are substantially different for sedentary and migratory insects, and that, in the latter, local and even regional field monitoring results may not reflect whole population dynamics. Genomic diversity patterns may elucidate key aspects of an insect's migratory nature and population dynamics at large spatiotemporal scales.
The proliferation of camera-trapping studies has led to a spate of extensions in the known distributions of many wild cat species, not least in Borneo. However, we still do not have a clear picture of the spatial patterns of felid abundance in Southeast Asia, particularly with respect to the large areas of highly-disturbed habitat. An important obstacle to increasing the usefulness of camera trap data is the widespread practice of setting cameras at non-random locations. Non-random deployment interacts with non-random space-use by animals, causing biases in our inferences about relative abundance from detection frequencies alone. This may be a particular problem if surveys do not adequately sample the full range of habitat features present in a study region. Using camera-trapping records and incidental sightings from the Kalabakan Forest Reserve, Sabah, Malaysian Borneo, we aimed to assess the relative abundance of felid species in highly-disturbed forest, as well as investigate felid space-use and the potential for biases resulting from non-random sampling. Although the area has been intensively logged over three decades, it was found to still retain the full complement of Bornean felids, including the bay cat Pardofelis badia, a poorly known Bornean endemic. Camera-trapping using strictly random locations detected four of the five Bornean felid species and revealed inter- and intra-specific differences in space-use. We compare our results with an extensive dataset of >1,200 felid records from previous camera-trapping studies and show that the relative abundance of the bay cat, in particular, may have previously been underestimated due to the use of non-random survey locations. Further surveys for this species using random locations will be crucial in determining its conservation status. We advocate the more wide-spread use of random survey locations in future camera-trapping surveys in order to increase the robustness and generality of inferences that can be made.