Population Density Estimates Research Articles

Urban Leopards of National Capital: Estimating Density and Occupancy of Leopard (Panthera pardus) in Asola Bhatti Wildlife Sanctuary, New Delhi, India

Studies, in recent past have revealed that obligate carnivores are adapting to human dominated landscapes. Leopards, amongst other large carnivores are highly adaptable and can survive in a range of environments. Although any sporadic sightings of leopards have occurred in New Delhi. However, any reliable population and occupancy estimation was lacking from the region, whereas understanding of population density estimation is important in providing local and regional level conservation and management of the species. Our study is conducted to better understand leopard status and population density estimation in Asola Bhatti Wildlife Sanctuary of New Delhi. During 588 camera trap nights, we detected 8 individual leopards. Based on spatial capture-recapture framework the leopard density inside the sanctuary was estimated at 4.5 ± 0.019 leopards/100km² despite very high anthropogenic pressure. Occupancy modelling based on Inverse Distance Weighted Interpolation showed species distribution across the sanctuary which was highest in the areas adjoining densely populated region of the city from where it was observed that large number of vehicle and people cross the sanctuary daily to for their work. The moderate leopard density in this small protected area with high human population pressure can be due to the absence of any other large carnivore, less competition with co-predators because of their low numbers (i.e., hyenas), high availability of prey base and inclusive protected area management. We encourage further research to explore the landscape connectivity between the neighboring suitable leopard habitats like Sariska Tiger Reserve in Rajasthan, via Aravalli hill range of South Haryana till Asola Bhatti Wildlife Sanctuary of New Delhi for understanding wildlife corridor connectivity in the Northern Aravalli Range at landscape level

Population status and density estimate of Leopard Panthera pardus fusca in dry thorn forests of southern India

The study aims to assess the population status and density of the Leopard (Panthera pardus fusca) in the Erode Forest Division, Tamil Nadu. The Erode Forest division has numerous villages within its boundaries and is exposed to associated biotic pressures. In order to improve the management practices of the wildlife in the area and to enhance its conservation, it is relevant to assess its status. In 2018 and 2020, we estimated the population density of the leopard in the entire forest division using 2 km2 sample grids and the camera trapping method. In each grid, we deployed a pair of camera traps, the cumulative number of trap-nights being 22983 (10732 trap nights in 2018 and 12251 in 2020). We analysed the obtained data using spatially explicit capture-recapture models (SECR). The surveys yielded 198 images of the leopard in 2018 and 272 images in 2020, of which 48 and 44 leopard individuals were identified in the respective years based on the rosette pattern. The density estimates were 5.16 (SE = ±0.89) and 4.00 (SE ± 0.72) individuals/100 km2 in 2018 and 2020, respectively. We found that in some regions overlapping with the human-use area, leopard densities were high, indicating that the species successfully exploits areas near human habitation and highlighting its high potential for interaction with humans. This baseline estimate and insights will help prioritize management actions, strengthen large mammal conservation beyond the boundaries of protected areas (PA), and plan human-wildlife conflict mitigation measures to enable the persistence of large carnivores in multi-use forests.

Estimating catchability and density of the European lobster Homarus gammarus from continuous, short-term mark-recapture data

Despite the commercial and ecological importance of the European lobster Homarus gammarus, estimates of the population dynamics within socio-economically important fishing areas remain understudied. We implemented a mark-recapture approach to estimate population density, rates of loss and catchability of H. gammarus off the coast of northeast England, an important area for lobster fishers, and one of high exploitation. The short-term study used continuous trapping data from a commercial parlour trap array, fished over 6 wk. Over 9 haul occasions, 562 lobsters were marked using persistent external T-bar tags with unique ID numbers; 13.7% of these lobsters were subsequently recaptured. Catch data were used to determine the relationship between trap soak time and the effective fishing effort over time. Capture histories and effort data were analysed using a modified Cormack-Jolly-Seber (CJS) model, adapted for the short-term and continuous nature of the study. Model estimates of male lobster density varied depending on capture occasion between 732 (95% CI = 423, 1267) and 2730 (95% CI = 1585, 4701) lobsters per km2. Similarly, female density was estimated at between 2410 (95% CI = 476, 12176) and 8060 (95% CI = 1592, 40810) lobsters per km2. Low rates of loss of individuals from the area and large differences in catchability between sexes led to a female-skewed density estimate. If these findings are corroborated, the effects of sex-specific catchability and the potential for biased sex composition in populations and catches should be addressed in stock assessments and when interpreting sex ratio data in commercial catches.

Foraging Behaviour and Population Dynamics of Asian Weaver Ants: Assessing Its Potential as Biological Control Agent of the Invasive Bagworms Metisa plana (Lepidoptera: Psychidae) in Oil Palm Plantations

The bagworm (Metisa plana) is a recurrent indigenous invasive defoliator in oil palm plantations. Moderate foliar injury can cost up to 40% yield loss and more for years. The main objective of this review is to disseminate published research demonstrating the versatile services that would benefit farmers by adopting the Asian weaver ant into their pest management agenda. Oecophylla smaragdina is a natural indigenous enemy applied as a successful biological control agent (BCA) and strong component of integrated pest management (IPM) against important damaging pest infestations of commercial crops in the Asia-Pacific region. Farmers facing invasion could benefit by introducing Oecophylla ants as a treatment. The foraging behavior and population dynamics of this species are poorly documented, and hence need further evaluation. Ants of the Oecophylla genus, while exhibiting an intrinsic obligate arboreal pattern, demonstrate additional lengthy diurnal ground activity. The absolute territorial characteristic via continuous surveillance is significantly valuable to maintain pest balance. The exploratory scheme of major workers over large territories is derived from their inner predation instinct. The insufficient understanding of the population dynamics of this weaver ant species diverges from the knowledge of underground species. However, population density estimations of weaver ants by direct nest visual recordings are practicable and viable. The abundance assessment of individual underground ant species colonies by excavation ends with their extinction, which is not a sustainable model for O. smaragdina. Mathematical model estimation by simulation could not resolve this issue, adding inaccuracy to the deficiency of experimental proof. Thus, long-term monitoring of the population dynamics in real time in the field is compulsory to obtain a valid dataset. Oecophylla colonies, with the criteria of population stability, individual profusion, and permanent daily patrol services, are eligible as a BCA and alternative IPM treatment. The last decades have witnessed the closing of the scientific applied research gap between Asian and African species in favor of O. longinoda with comprehensive novel findings. By introducing Oecophylla ants, two main goals are reached: easing the burden of management costs for injurious insects and ending the practice of applying highly toxic pesticides that are harmful to non-target taxa, thus promoting environmental restoration.

Population density of the wild boar (Sus scrofa) in south-western Poland in 1981–2020

The study is based on the analysis of hunting bag data from the years 1981–2020. In 1980–1990, 38 016 wild boars, whereas in 1991–2000, 43 490 wild boars were culled (14.4% increase) in south-western Poland (29 358 km2, forests comprise 28.6%). In 2001–2010, there were 69 052 individuals harvested (58.8% increase in relation to the previous decade). In 2011–2020, the harvest was 3-fold higher in relation to the previous decade and 5.6-fold higher in relation to 1980–1990. During the years 1981–1990, an estimated number of 51–100 wild boars were recorded only in five hunting districts, whereas there were 23 such districts in the next decade. After a population expansion in 2001–2010, there were 32 districts, each one with 101–200 wild boars. Ecological population densities (per forest area) of the wild boar was spatially greatly varied in south-western Poland, ranging from 9.1 ind./1000 ha in extensive woodlands of the Lower Silesian Forests to as much as 147.2 ind./1000 ha in the Wrocław Plain dominated by farmlands with forest fragments. The crude density was much lower and much less spatially varied than the ecological density; it was the lowest (7.4 ind./1000 ha) in the West Sudeten Mts. and the highest, 23.8 ind./1000 ha in the East Sudeten Mts. When only ecological density is calculated, a strongly distorted picture may emerge, where the highest density will always be in deforested areas with forest fragments, whereas it will be inevitably the lowest in the most afforested ones. The crude density will, therefore, reflect much better the actual population densities. In comparison with the line transect track index, the hunting bags analysis provide similar population density estimates, whereas in the comparison with the block count census, population densities based on the hunting bag analysis are underestimated. However, it should be emphasised that density estimates based on hunting bag analysis will always be lower than the real densities, as not all animals are harvested in a given population. The following ecological variables may shape wild boar population density in south-western Poland: food resources (maize, mast); temperature (winter and early spring); precipitation (snow and rainfalls); and diseases (especially African swine fever).

Exploring the eDNA dynamics of the host-pathogen pair Pacifastacus leniusculus (Decapoda) and Aphanomyces astaci (Saprolegniales) under experimental conditions

The oomycete Aphanomyces astaci causes crayfish plague, a disease threatening native European crayfish. It is carried and transmitted by American crayfish species, which are the original hosts of A. astaci. In recent years, environmental DNA (eDNA) methods have been successfully implemented to monitor the spread of both A. astaci and its hosts. However, still little is known about how population density and other environmental factors influence the detectability of this host-pathogen complex. In a mesocosm experiment, we tested the influence of crayfish density, temperature and food availability on the detectability of eDNA for A. astaci and its host, signal crayfish Pacifastacus leniusculus. We also compared eDNA results with crayfish population density measured by catch per unit effort (CPUE) from two lakes with varying crayfish density and A. astaci prevalence. The mesocosm experiment revealed that a limited set of controlled factors can substantially change the detectable amount of eDNA, even though the physical presence of the target organisms remains the same. In cold, clear water, eDNA quantities of both targets increased far more than in a linear fashion with increased crayfish density. However, the presence of food decreased the detectability of crayfish eDNA, presumably through increased microbial-induced eDNA degradation. For A. astaci, where eDNA typically represents living spores, food did not affect the detectability. However, high water temperature strongly reduced it. The increased complexity and variability of factors influencing eDNA concentration under natural conditions, compared to a controlled experimental environment, suggests that establishing a reliable relationship between eDNA quantities and crayfish density is difficult to achieve. This was also supported by field data, where we found minimal correspondence between eDNA quantity and CPUE data. A comparison between quantitative real-time PCR (qPCR) analysis and droplet-digital PCR (ddPCR) analysis revealed higher detection success of the targets in field samples when using qPCR. Overall, our results support eDNA as an effective tool for presence-absence monitoring, but it seems less suited for biomass quantification and population density estimates. Detection of A. astaci and P. leniusculus is not influenced uniformly by respective environmental factors. Consequently, we recommend a strategy of monitoring both targets, where the detection of one may point towards the presence of the other.

Acoustic sampling of Antarctic krill with simulated underwater buoyancy gliders: Does the sawtooth dive pattern work?

Autonomous underwater gliders may be viable adjuncts to or in some cases replacements for ship-based oceanographic sampling. Gliders and ships acoustically sample the water column differently, with ships sampling all depths simultaneously in a single vertical pulse and gliders sampling shorter vertical segments of the water column in an up and down, sawtooth pattern. We simulated gliders following this flight pattern to sample the densities at depth of Antarctic krill (Euphausia superba), a patchily-distributed crustacean that is targeted by an international fishery. Krill densities from ship-based surveys conducted between 2001 to 2011 were treated as the “true” population densities sampled by the simulated gliders. Depth-integrated densities estimated from the glider sampling were compared to the population densities for each year. Coverage probabilities (the proportion of population means within a standard deviation of the glider sample means) for gliders diving to 150 m were near 100% in most years, better than the nominal 68%. Gliders diving to a maximum depth of 150 m estimated the annual population means better than gliders diving deeper because shallow dives provided more samples for a given length of trackline. Modeling the zero and non-zero data as separate distributions (the delta approach), an alternative to the lognormal CV approach used in this study, resulted in less accurate estimates of krill population densities. These results suggest that the sawtooth flight pattern of gliders can produce density estimates of krill comparable to the annual time series of density estimates from ship-based surveys. Gliders may also be useful to survey other patchily-distributed pelagic organisms.

Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring

AbstractIndirect wildlife population surveying largely depends upon counts of artifacts of behavior (e.g., nests or dung). Likelihood to encounter these artifacts is derived from both artifact production and decay, and variability in production behavior is considered to contribute minimally to inaccuracy in wildlife estimation. Here, we demonstrate how ignoring behavioral variability leads to significant population misestimation, using an example of an endangered ape, the bonobo (Pan paniscus). Until now, a single estimate of nest construction rate has been used to extrapolate bonobo densities, assumed to be broadly representative of bonobo sign production behavior. We estimated nest construction rates across seasons and social groups at the Kokolopori Bonobo Reserve, Democratic Republic of the Congo, and find nest construction rates in bonobos to be highly variable across populations as well as seasonal within populations. Failure to account for this variability led to degradation in the accuracy of bonobo population density estimates, accounting for a likely overestimation of bonobo numbers by 34%, and at worst as high as 80%. With this example, we demonstrate that failure to account for inter‐ and intrapopulation behavioral variation compromises the ability to estimate both relative and absolute wildlife abundances. We argue that variation in sign production is but one of the several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability can have upon wildlife population estimation. Our results underline the importance of observational research to wildlife monitoring schemes as a critical component of conservation management. We discuss the avenues through which behavioral variability is likely to impact wildlife monitoring accuracy and precision and propose potential approaches for accounting for behavioral variability in wildlife monitoring.

Spatial capture-recapture and LiDAR-derived vegetation metrics reveal high densities of ocelots on Texas ranchlands

Reliable estimates of population density and size are crucial to wildlife conservation, particularly in the context of the Endangered Species Act. In the United States, ocelots (Leopardus pardalis pardalis) were listed as endangered in 1982, and to date, only one population density estimate has been reported in Texas. In this study, we integrated vegetation metrics derived from LiDAR and spatial capture-recapture models to discern factors of ocelot encounter rates and estimated localized population estimates on private ranchlands in coastal southern Texas. From September 2020 to May 2021, we conducted a camera trap study across 42 camera stations on the East Foundation’s El Sauz Ranch, which was positioned within a larger region of highly suitable woody and herbaceous cover for ocelots. We observed a high density of ocelots (17.6 ocelots/100 km2) and a population size of 36.3 ocelots (95% CI: 26.1–58.6) with the 206.25 km2 state space area of habitat. The encounter probability of ocelots increased with greater canopy cover at 1-2 m height and decreasing proximity to woody cover. These results suggest that the incorporation of LiDAR-derived vegetative canopy metrics allowed us to understand where ocelots are likely to be detected, which may aid in current and future population monitoring efforts. These population estimates reflect the first spatially explicit and most recent estimates in a portion of the northernmost population of ocelots in southern Texas. This study further demonstrates the importance of private working lands for the recovery of ocelots in Texas.

Economic Development Planning in Medan City

Economic development in an area must go through several plans and targets both long term and short term. The process leading to the realization of some of these targets is useful for conditioning the capacity for increasing the economy of the community. One of the characteristics of society that has gone hand in hand with economic development is marked by the widespread use of technology and changes in a more positive direction from the mindset of the people to institutional institutions. The research method used as an analytical tool in this study is a descriptive type with the aim of obtaining a projected representation of a participation and procedural regulatory mechanism in the community during the process of preparing the RPJMD in Medan City from 2010 to 2025. The analytical steps used are secondary data or data. supporting information in the form of a collection of information regarding the results of interviews with respondents as well as providing an appropriate presentation with an explanation of the matrix accompanied by the presentation that has been displayed by the researcher. The variety of informants or respondents used as a collection of information in this study involved various elements such as social organizations, elements from the Medan city government to academics under the auspices of universities to the mass media and the main element is the Medan City DPRD. The process of compiling the results of this research is oriented towards a question and answer process or interviews by applying qualitative analysis steps with the aim of criticizing various phenomena in the process of preparing reports and investigating phenomena regarding the research topic. The continuation of the process is a data analysis technique using logical interpretation supported by previously collected data. The results of this study are that in development planning, Medan City has a challenge by having to handle an area of 265.10 km2, with an estimated population density of 9,836.56 people/km2 in 2025. This population increase can be an obstacle in handling development planning., however This is also an opportunity if the government can take advantage of this population increase. For population growth itself in 2025 there will be a decline, which in 2020 is expected to grow by 1.03 to 0.94% in 2025.

Population Estimate of Long-Tailed Macaques (Macaca fascicularis) on Tinjil Island

Tinjil Island was established as a Natural Habitat Breeding Facility for long-tailed macaques (Macaca fascicularis) in 1997. Between February 1998 and January 2007, 603 (61 males and 542 females) simian retrovirus (SRV) free long-tailed macaques were introduced to the island on the south coast of West Java and function as a primate resource and conservation program. To date, 3256 progenies have been harvested and used as the animal model. Therefore, it is necessary to survey the current population of the long-tailed macaques to evaluate whether the population is still under the island’s carrying capacity. This research aims to identify the population estimate of long-tailed macaques currently occupying the island. The observation was conducted in July 2021 using line transect sampling starting from 07.00 AM and 01.00 PM. Twelve observations were conducted during the study using CD and ES transects. CD (Chuck Darsono) and ES (Emil Salim) are the two longest trails on the island and represent the names of the people who initiated the captive breeding of Tinjil Island. The estimated group density of the long-tailed macaques on Tinjil Island is 13.46 groups/km2, while the estimated population density is 111.04 individuals/km2. The population estimated on the island is 627.38±23.53 individuals. The number indicates that the population is still under carrying capacity.

Index‐based large carnivore population density and abundance estimates for the Ruaha‐Rungwa conservation complex in Tanzania

Index‐based large carnivore population density and abundance estimates for the <scp>Ruaha‐Rungwa</scp> conservation complex in Tanzania

Isophya modesta Frivaldszky, 1868 (Orthoptera: Tettigoniidae): a new bush-cricket species in Poland

Isophya modesta, a bush-cricket species belonging to the subfamily Phaneropterinae, was found for the first time outside of the forest-steppe zone. This study is the first report on I. modesta in Poland. It was found at our sites in the Przemyśl Foothills (Pogórze Przemyskie) in the south-eastern Polish Carpathians, where I. modesta inhabits xerothermic grasslands, dry and semi-dry meadows, but also successional meadows on abandoned arable land. One site occupied by I. modesta in the Przemyśl Foothills is located within a nature reserve, but other sites may be threatened by secondary succession or afforestation. We estimated population densities of around 30–80 adult individuals per hectare, and the whole known population consisted of a total of 3,000 to 15,000 adult individuals. The discovered populations may either be insular in character or connected by a continuous range with populations from Opilia Upland in Western Ukraine.

Data-driven risk analysis of unmanned aircraft system operations considering spatiotemporal characteristics of population distribution

One of the challenges of Unmanned Aircraft System (UAS) operations is to operate an unmanned aircraft with minimal risk to people on the ground. The purpose of this study is to define and measure such risks as population risk, by incorporating spatiotemporal changes in population density. Unlike previous studies, we use high-resolution de facto population data instead of residential population data to reflect the spatiotemporal characteristics of population distribution. Furthermore, we analyze the impact of mitigation measures based on population risk in the context of airspace management. We set a restricted airspace by using population risk and an acceptable level of safety. Scenario analysis of the study area in Seoul, South Korea provides a richer set of findings regarding spatiotemporal differences in restricted airspace. During the daytime, there are many restricted airspaces around commercial areas, but few around residential areas. Additionally, we observe the difference between restricting airspace based on population risk derived from the residential population and from the de facto population. These findings confirm the importance of accurately considering population density when assessing and mitigating the population risk associated with UAS operations. Sensitivity analysis also reveals the need to precisely estimate population density when estimating population risk with combinations of multiple parameter values. The proposed approach captures spatiotemporal characteristics of population distribution when assessing the population risk associated with UAS.

Recent population size of Timor Friarbird and resources utilization at three landscapes in West Timor Island, Indonesia

The Timor Friarbird is an endemic species of Timor Island that plays an important role in forest ecosystems, agriculture and other natural environments in the semiarid region. Although classified as an endemic species and declining population, the bird is protected by Indonesian law. This study aims to assess the density, group size, and population distribution of Timor Friarbird and resource uses in three landscape at Western Timor. Distance sampling methods with transect lines was used to estimate population density and bird distribution. The highest estimated bird population density (3.31 ind./ha) in the Baumata landscape and lowest (0.15 ind./ha) in Bipolo. Individual sizes per group of 1-4 individuals in all landscapes. Utilization of distributed feed resources in the main area, secondary and low potency area. The distribution of species in the rainy season is higher found in low-lying, higher dry seasons in lowlands. High anthropogenic pressures and changes in dominant habitats in the low-lying west Timor Island contribute to the rate of population decline of this species thus impacting crop productivity and conservation efforts of this species in the future.

Frequency-Enhanced Channel-Spatial Attention Module for Grain Pests Classification

For grain storage and protection, grain pest species recognition and population density estimation are of great significance. With the rapid development of deep learning technology, many studies have shown that convolutional neural networks (CNN)-based methods perform extremely well in image classification. However, such studies on grain pest classification are still limited in the following two aspects. Firstly, there is no high-quality dataset of primary insect pests specified by standard ISO 6322-3 and the Chinese Technical Criterion for Grain and Oil-seeds Storage (GB/T 29890). The images of realistic storage scenes bring great challenges to the identification of grain pests as the images have attributes of small objects, varying pest shapes and cluttered backgrounds. Secondly, existing studies mostly use channel or spatial attention mechanisms, and as a consequence, useful information in other domains has not been fully utilized. To address such limitations, we collect a dataset named GP10, which consists of 1082 primary insect pest images in 10 species. Moreover, we involve discrete wavelet transform (DWT) in a convolutional neural network to construct a novel triple-attention network (FcsNet) combined with frequency, channel and spatial attention modules. Next, we compare the network performance and parameters against several state-of-the-art networks based on different attention mechanisms. We evaluate the proposed network on our dataset GP10 and open dataset D0, achieving classification accuracy of 73.79% and 98.16%. The proposed network obtains more than 3% accuracy gains on the challenging dataset GP10 with parameters and computation operations slightly increased. Visualization with gradient-weighted class activation mapping (Grad-CAM) demonstrates that FcsNet has comparative advantages in image classification tasks.

Feral cats on Rakiura Stewart Island: population attributes and potential eradication tools

As a major threat to New Zealand’s biodiversity, feral cats (Felis catus) are the subject of planned eradications on a number of offshore islands, including Rakiura Stewart Island. We used camera traps to estimate population density of feral cats on the north-east coast of Rakiura, and to investigate their movement behaviour and detection probability. We also used camera footage to compare the consumption of two types of non-toxic sausage baits (chicken and rabbit) with a view to future use of toxic baits.

Effects of anthropogenic disturbance on group densities of Thomas' langurs (Presbytis thomasi) within a lowland tropical forest, north Sumatra

AbstractEcosystems around the globe are facing irreversible impacts due to climate change, habitat destruction, hunting, and an ever‐increasing human population. Estimating densities of species across their geographical range helps us to understand natural variation and anthropogenic effects on species densities and to assess the effectiveness of existing conservation measures. Various methods have been used to produce accurate and precise population density estimates, each with associated limitations. Acoustic surveys for species producing loud calls have become common due to their ease of use, low cost, and reduced timescale. Relative to many other mammal taxa, primate species have been studied extensively, producing a wealth of data on socioecology and behavior, but for most species, density estimates over large geographical ranges are still lacking. We used an acoustic spatial capture–recapture model to estimate group density of unhabituated Thomas' langurs (Presbytis thomasi), a primate endemic to the Indonesian island of Sumatra, over a 60 km2 area of lowland dipterocarp forest. We then assessed if vegetation structure and distance from human habitation affected density estimates. Estimates of group density differed almost threefold between survey locations (from 2.79 to 8.08 groups/km2); there was no clear relationship with forest structure, but there was a significantly positive relationship between group density and distance from human habitation, with an increase of 0.38 groups/km2 for every km of distance. Although large‐scale logging within the Sikundur region ceased ~30 years ago, the impacts of logging continue to have detrimental effects on the species within the area.

A comparative assessment of the statistical methods based on urban population density estimation

Population density is important spatial information for addressing the use and access to land resources in cities under the Sustainable Development Goals. This is because the spatial data support appropriate spatial policies at the spatial scale and predicts how much land will be consumed in the future. The study aims to compare and evaluate the regression tools in the context of estimating the population density difference. The three analysis tools used are Random Forest-Based Classification, Multiple Linear Regression, and Geographically Weighted Regression. The sampling area covers cities around Türkiye. Comparative results showed that the two most important descriptive variables in the Random Forest-Based Classification model are the density difference of the new developed area and the connectivity. The three main explanatory variables of the Multiple Linear Regression model are centrality, vehicle ownership, and accessibility. The results of the Multiple Linear Regression model (a non-spatial model) and the Geographically Weighted Regression model (a spatial model), were found to be quite similar. The importance of accessibility and connectivity is more evident in the Multiple Linear Regression model when the Random Forest-Based Classification model highlights the density values in the new development areas.

Monitoring riverine traffic from space: The untapped potential of remote sensing for measuring human footprint on inland waterways

Mass urbanisation and intensive agricultural development across river deltas have driven ecosystem degradation, impacting deltaic socio-ecological systems and reducing their resilience to climate change. Assessments of the drivers of these changes have so far been focused on human activity on the subaerial delta plains. However, the fragile nature of deltaic ecosystems and the need for biodiversity conservation on a global scale require more accurate quantification of the footprint of anthropogenic activity across delta waterways. To address this need, we investigated the potential of deep learning and high spatiotemporal resolution satellite imagery to identify river vessels, using the Vietnamese Mekong Delta (VMD) as a focus area. We trained the Faster R-CNN Resnet101 model to detect two classes of objects: (i) vessels and (ii) clusters of vessels, and achieved high detection accuracies for both classes (f-score = 0.84–0.85). The model was subsequently applied to available PlanetScope imagery across 2018–2021; the resultant detections were used to generate monthly, seasonal and annual products mapping the riverine activity, termed here the Human Waterway Footprint (HWF), with which we showed how waterborne activity has increased in the VMD (from approx. 1650 active vessels in 2018 to 2070 in 2021 - a 25 % increase). Whilst HWF values correlated well with population density estimates (R2 = 0.59–0.61, p < 0.001), many riverine activity hotspots were located away from population centres and varied spatially across the investigated period, highlighting that more detailed information is needed to fully evaluate the extent, and type, of human footprint on waterways. High spatiotemporal resolution satellite imagery in combination with deep learning methods offers great promise for such monitoring, which can subsequently enable local and regional assessment of environmental impacts of anthropogenic activities on delta ecosystems around the globe.