Current Population Density Research Articles

Abstract B140: Further evaluation of social determinants of health including association of neighborhood disadvantage and population density with severity of activity- and mood- related interference in primary brain tumor patients

Abstract Purpose: Growing evidence links living in rural or socioeconomically disadvantaged areas with worse outcomes in cancer patients. Our previous work indicated that growing up in a rural area and experiencing food insecurity in childhood are associated with more severe activity and mood-related interference from symptoms in the primary brain tumor (PBT) population. This study investigates the association of current neighborhood deprivation and population density with activity- and mood-related interference in a cross-sectional cohort of 555 patients with a PBT enrolled in a natural history study (NCT03251989). Methods: National Area Deprivation Index (ADI) and population density were dichotomized into more (>40) and less (<40) disadvantaged and urbanized (>1,000 persons/sq mi) and non-urbanized (<1,000 persons/sq mi). Activity- and mood-related interference was stratified into none/mild (0-1) and moderate/severe (2-10). Logistic regression was used to test univariate and multivariate associations of moderate/severe activity- and mood-related interference with demographic and clinical variables. Bonferroni-Holm was implemented to adjust for multiple comparisons (p < 0.001) in univariate analyses. We used backwards elimination multivariate analyses to fit the final model. Variables were included modeling when univariate p <0.10. Results: The sample included more males (57%), median age 49 (range 18-85), living in more disadvantage neighborhoods (25%), and primarily in urbanized areas (61%). The majority (74%) had high grade tumors, most commonly glioblastoma (39%), with 49% with tumor recurrence, and 21% on active treatment. Univariate analysis showed neither ADI nor population density was significantly associated with activity-related interference (ADI OR=1.35, 95% CI [0.85, 2.13]; population density OR=1.20, 95% CI [0.80, 1.79]) or mood-related interference (ADI OR=0.85, 95% CI [0.52, 1.38]; population density OR=1.19, 95% CI [0.78, 1.81]). In the multivariate analyses tumor diagnosis (OR=0.92 CI [0.53, 1.58]) growing up in a non-urbanized area (OR=1.56 CI [1.02, 2.40]), not having enough to eat when growing up (OR=2.50 CI [1.13, 5.54], and number of surgeries (OR=1.50 CI [1.00, 2.23]) remained associated with moderate/severe activity-related interference with ADI, and similar results were found in the population density model. Tumor recurrence (OR=1.77 CI [1.17, 2.66]) and comorbidities (OR=0.53 CI [0.33, 0.85]) were associated with moderate/severe mood-related interference with ADI and similar results were found in the population density model. Conclusions: Although activity- and mood-related interference were not associated with current ADI or population density, activity-related interference was significantly related to early life social variables including growing up in a rural area and not having enough to eat growing up. This study may be foundational for future study directions exploring other social deprivation factors early life or current that contributes to more interference in the PBT population. Citation Format: Tara S. Davis, Bennett A. McIver, Kimberly Reinhart, Elizabeth Vera, Vivian A. Guedes, Macy L. Stockdill, Orieta Celiku, Terri S. Armstrong, Michelle L. Wright. Further evaluation of social determinants of health including association of neighborhood disadvantage and population density with severity of activity- and mood- related interference in primary brain tumor patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B140.

A stratified review of COVID-19 infection forecasting and an efficient methodology using multiple domain-based transfer learning

The initial outbreak of COVID-19 was reported in December 2019, China. The pandemic has led to unforeseen challenges, causing unimaginable devastation of the economic and social disruption since its inception. An effective approach for forecasting infections will be beneficial for the health sector and administration in better strategic planning and proficient management of all necessary schemes towards preventive and curative treatments. Most existing studies consider image dataset for COVID-19 prediction, whereas studies involving structural data are very rare. Thus, initially the main focus of this paper is to provide an exhaustive review that discusses about COVID-19 forecasting papers with emphasis on structural data. Then, this paper introduces a pioneering approach to COVID-19 infection forecasting, utilizing structural datasets instead of traditional image datasets. It presents a novel multi-source transfer-learning framework to enhance prediction accuracy, integrating demographic, economic, and COVID-19 data for intra-provincial spread forecasts. The COVID-19 forecasting depends on several parameters such as its current statistics, geographical area, population density and economic status like GDP etc. However, the dataset generated for an individual province of a country is alone inadequate for the precise forecast, as it faces data scarcity. Thus, transfer learning helps in such cases, where the dataset has been collected from multiple provinces. Since, it is a time-series data, thus we also consider lagged features for efficient prediction of COVID cases. Thus, apart from the detailed review, this study also aims to develop robust machine learning models by proposing a novel and efficient multi-source transfer learning technique for accurate forecasting of COVID-19 in a province. The proposed approach has been evaluated over a wide range of datasets involving sixty-two different provinces belonging to a diverse set of countries. We also performed hyperparameter tuning using Bayesian optimisation to optimise the machine learning models used. Later, we performed Friedman and Nemenyi test to compare the results generated from different models. Empirical evidence proved that forecasting using the proposed approach is much more precise with the simpler models such as Decision Trees as compared to complex models. In cases of data scarcity, when target domain data could not be used for training/fine-tuning the models simpler models are far more powerful due to their generalization capabilities than complex models. Hence, the proposed methodology is promising and valuable for governments and organizations to deal with the challenges of any pandemic outbreak for better healthcare planning and management, even when the data is in scarcity.

An Autoregulatory Model of Forest Insect Population Dynamics and Forest Stand Damage Dynamics in Different Habitats: An Example of Lymantria dispar L.

This paper addresses the problem of constructing a mathematical model of population density dynamics and the dynamics of forest areas damaged by spongy moth (Lymantria dispar L.) outbreaks in the United States, Europe, Russia, and Japan. The key variable of the model is either the pest population density or the area of forests damaged by spongy moths during a season. This variable can be considered proportional to the total current pest abundance in the study area. For the purposes of modeling, data from a number of different authors was used (see bibliography), as well as data from surveys conducted at the egg or caterpillar stage. The complexity of modeling the dynamics of L. dispar abundance is largely due to the fact that, when studying the dynamics of spongy moth population density, the values of external factors such as parasites, predators, and the amount of available food are often unknown. A simple model was proposed using only two types of data: population density and monthly weather characteristics. Our analysis demonstrated that, even in the absence of knowledge regarding the characteristics of ecosystem components interacting with the spongy moth population (parasites, predators, and the state of forage trees), it is possible to introduce models that characterize the regulatory processes in the population in terms of (i) the presence of negative and positive feedbacks in the system and (ii) the influence of external weather factors. The system under investigation was described as an autoregressive system, whereby the current state of the population is dependent on its state in previous years. The order of autoregression in the system was estimated using the order of the maximum significant partial autocorrelation function. It was found that the regulation of spongy moth population density was characterized by the presence of two feedback loops: positive feedback between the current population density and the population density in the previous season and negative feedback between the current population density and the population density two years ago. To evaluate the model, its stability margin was calculated and found to be directly proportional to the positive feedback coefficient and inversely proportional to the negative feedback coefficient. The model was demonstrated to explain up to 90% of the observed variance of real data. Although the model coefficients for different local populations (North America, Europe, and Asia) differ, the general form of the equation describing both direct data on population densities and indirect data on pest dynamics characterized by areas of stand damage is consistent. Consequently, the form of the ADL model is general, irrespective of the location of the local population.

Autoregression, First Order Phase Transition, and Stochastic Resonance: A Comparison of Three Models for Forest Insect Outbreaks

Three models of abundance dynamics for forest insects that depict the development of outbreak populations were analyzed. We studied populations of the Siberian silkmoth Dendrolimus sibiricus Tschetv. in Siberia and the Far East of Russia, as well as a population of the pine looper Bupalus piniarius L. in Thuringia, Germany. The first model (autoregression) characterizes the mechanism where current population density is dependent on population densities in previous k years. The second model considers an outbreak as analogous to a first-order phase transition in physical systems and characterizes the outbreak as a transition through a potential barrier from a low-density state to a high-density state. The third model treats an outbreak as an effect of stochastic resonance influenced by a cyclical factor such as solar activity and the “noise” of weather parameters. The discussion focuses on the prediction effectiveness of abundance dynamics and outbreak development for each model.

Top‐Down Regulation by a Reindeer Herding System Limits Climate‐Driven Arctic Vegetation Change at a Regional Scale

AbstractWarming‐driven growth of tall woody vegetation in the Arctic has the potential to accelerate climate change through multiple positive feedbacks. Local‐scale evidence suggests that large herbivores limit this vegetation shift, but there is uncertainty at larger, regional scales whether current herbivory pressure is a major top‐down control on ecosystem structure and functioning. Across a 67,000 km2 region of the Yamal Peninsula in West Siberia, we integrated satellite remote sensing with a novel data set mapping the migrations of herds comprising 151,000 domesticated reindeer. Where reindeer numbers varied over space, higher reindeer herbivory pressure was consistently linked with lower coverage of tall woody vegetation. Within areas dominated by this vegetation type, productivity and climate were increasingly decoupled where reindeer density was higher. Our spaceborne fingerprint detection suggests that large herbivores, at current population densities, counteract Arctic vegetation responses to climate change over large spatial scales.

Wolverine density distribution reflects past persecution and current management in Scandinavia

After centuries of intense persecution, several large carnivore species in Europe and North America have experienced a rebound. Today's spatial configuration of large carnivore populations has likely arisen from the interplay between their ecological traits and current environmental conditions, but also from their history of persecution and protection. Yet, due to the challenge of studying population‐level phenomena, we are rarely able to disentangle and quantify the influence of past and present factors driving the distribution and density of these controversial species. Using spatial capture‐recapture models and a data set of 742 genetically identified wolverines Gulo gulo collected over ½ million km2 across their entire range in Norway and Sweden, we identify landscape‐level factors explaining the current population density of wolverines in the Scandinavian Peninsula. Distance from the relict range along the Swedish–Norwegian border, where the wolverine population survived a long history of persecution, remains a key determinant of wolverine density today. However, regional differences in management and environmental conditions also played an important role in shaping spatial patterns in present‐day wolverine density. Specifically, we found evidence of slower recolonization in areas that had set lower wolverine population goals in terms of the desired number of annual reproductions. Management of transboundary large carnivore populations at biologically relevant scales may be inhibited by administrative fragmentation. Yet, as our study shows, population‐level monitoring is an achievable prerequisite for a comprehensive understanding of the distribution and density of large carnivores across an increasingly anthropogenic landscape.

Alarming decline of the Little Bustard Tetrax tetrax in one of its two population strongholds in Sardinia, Italy

Summary Farmland biodiversity is declining worldwide, and especially in Western countries largely owing to the large-scale intensification of agricultural practices. The Little Bustard Tetrax tetrax is a steppe bird adapted to agro-pastoral ecosystems in Western Europe, and is one of those many farmland species declining due to changes in agricultural production systems. In the EU, the majority of the extant population of this species is concentrated in the Iberian Peninsula. In Italy, the species has now disappeared from the mainland and is currently present only in Sardinia, where two populations, in the central-western areas, hold about two-thirds of the whole island’s numbers, with the rest scattered across numerous smaller nuclei. While there are indications and anecdotal information suggesting a possible population decline during recent decades, robust monitoring across different time periods that would allow a comparison of numbers is lacking in Sardinia. Here we repeated a Little Bustard survey performed in 2008 in two areas of western Sardinia: Abbasanta, which is one of the two strongholds for the species in Sardinia, and Campeda, which holds a small population (about 10 territorial males). Using the same methodology as in the past survey, we assessed current population size and density, and quantified changes over time. We found alarming declines, at a rate of around 30% in 14 years in both areas, with an estimated current population of 87 males in Abbasanta and 8 males in Campeda. We highlight current and emerging threats, such as the downsizing of the Special Protection Area of Abbasanta, and the encroachment of solar power plants within the same area.

Regulatory Processes in Populations of Forest Insects (A Case Study of Insect Species Damaging the Pine Pinus sylvestris L. in Forests of SIBERIA)

The present study addresses the population dynamics of five species of phyllophagous forest insects in five habitats located in the Krasnoturansk pine forest (south Middle Siberia). Based on the data of insect surveys obtained during 1979–2016, autoregressive (AR) models of population dynamics have been proposed, with the current population density being dependent on population densities of the preceding years. Methods of calculation of the autoregression order and coefficients of AR equations have been presented. The study shows that, for different insect species in different habitats, the lags between the current population density and the densities of the previous years are not the same. AR equations characterize positive and negative feedbacks regulating population dynamics. By using AR equations, up to 90% of population density variance can be taken into account. Stability margin, which is calculated from coefficients of AR models, has been proposed as a parameter to assess the stability of population dynamics. A small stability margin indicates a high risk of outbreak of an insect species.

Are genetic variation and demographic performance linked?

Quantifying relationships between genetic variation and population viability is important from both basic biological and applied conservation perspectives, yet few populations have been monitored with both long-term demographic and population genetics approaches. To empirically test whether and how genetic variation and population dynamics are related, we present one such paired approach. First, we use eight years of historical demographic data from five populations of Boechera fecunda (Brassicaceae), a rare, self-compatible perennial plant endemic to Montana, USA, and use integral projection models to estimate the stochastic population growth rate (λ S) and extinction risk of each population. We then combine these demographic estimates with previously published metrics of genetic variation in the same populations to test whether genetic diversity within populations is linked to demographic performance. Our results show that in this predominantly inbred species, standing genetic variation and demography are weakly positively correlated. However, the inbreeding coefficient was not strongly correlated with demographic performance, suggesting that more inbred populations are not necessarily less viable or at higher extinction risk than less inbred populations. A contemporary re-census of these populations revealed that neither genetic nor demographic parameters were consistently strong predictors of current population density, although populations showing lower probabilities of extinction in demographic models had larger population sizes at present. In the absence of evidence for inbreeding depression decreasing population viability in this species, we recommend conservation of distinct, potentially locally adapted populations of B. fecunda rather than alternatives such as translocations or reintroductions.

Population density and distribution of the Endangered Black Shama Kittacincla cebuensis

Summary The Endangered Black Shama Kittacincla cebuensis is endemic to the island of Cebu, Philippines. We surveyed 11 forest patches from February 2018 to March 2020 to determine current distribution, habitat requirements, and population density of the Black Shama. A total of 111 point count stations was surveyed resulting in 93 Black Shama detections. Using point count Distance sampling, the population density was estimated at 313 individuals/km2 for a total population of 11,839 individuals (9,160–15,415). The largest sub-population (10,470) was in Alcoy, followed by Argao (711), and Dalaguete (325). Our total population estimate and sub-population estimates were higher than the estimate of 6,650 individuals made by BirdLife International for the International Union for the Conservation of Nature. The species was found to survive in a variety of habitats in at least 20 localities covering roughly 37 km2 of karst forest. We did not encounter the bird in seven areas of its former range. Protection of the remaining forests of Cebu and the establishment of plantations of native tree species in between forest patches are crucial to the survival of the species.

Challenges and opportunities for restoration of high-elevation Andean peatlands in Ecuador

Páramo peatlands are a regional reservoir of biodiversity and ecosystem services, accumulating large amounts of carbon and buffering water flows. Despite their importance, they have a long history of use and impacts including drainage for agriculture and grazing, and water withdrawal for human uses. Here we present a preliminary assessment of the conservation status of páramo peatlands in Ecuador and, using a case study, discuss peatland restoration as a tool for mitigation and adaptation to the impacts of current climate change. Through a simple index assessing the cumulative presence of signs of human activities on 163 peatland sites, we found that the level of impact was higher for peatlands located in the Western branch of the cordillera, whereas current human population density, precipitation, and elevation were not significant predictors of the levels of impact. Also, starting in 2017, we implemented a pilot restoration initiative on a 21-ha peatland which had been drained and converted into pasture for at least 150 years. The restoration consisted of two ditch blocking techniques implemented to stop fast-moving water and promote the rewetting of the peatland. During the next 3 years, water table increased from 27 ± 3 cm below the soil surface to 7 ± 1 cm by 2021, while wetland plant communities are colonizing and closing the pools in the blocked ditches. Re-wetting of the peatland has led to an increase in the abundance of native species. This case study suggests that restoration initiatives are an efficient and cost-effective approach to a better management of páramo peatlands, with high potential as a tool for mitigation and adaptation to climate change.

Plasma electrolytic oxidation of magnesium by sawtooth pulse current

Mg 2 SiO 4 coatings were formed on cp-Mg by Plasma Electrolytic Oxidation (PEO) using electrical regimes based on sawtooth anodic current pulses with extended ascending or descending segments (ramps). Voltage, current and light emission signals were simultaneously acquired to derive and analyse the evolution of system current and discharge population density during PEO process, while optical emission spectroscopy was employed for identification of plasma species. Coating morphological characterisation was carried out using Scanning Electron Microscopy. Phase composition was identified by X-ray diffraction. The corrosion performance was evaluated with Electrochemical Impedance Spectroscopy at various periods of exposure to corrosive media (0.5 wt% NaCl). It was shown that the application of sawtooth pulses allowed the controlling of microdischarge characteristics and coating morphology in both pulsed unipolar and reversed current regimes. Results further demonstrate that the application of anodic sawtooth pulses with the negative ramp facilitated defect healing during coating formation leading to production of more uniform PEO coatings with lower porosity and a slower degradation rate of magnesium substrate. A steady decay in the coating resistance with immersion time provides a possibility for controlling magnesium degradation and thereby for optimisation of component lifetime in applications where predictable Mg dissolution rate is required, such as sacrificial anodic protection of metallic structures and resorbable biomedical implants. • The quality of PEO coatings is modified by sawtooth pulse current regimes with controlled positive or negative anodic ramp. • Applying sawtooth waveforms with positive ramps refined the coating morphology. • Negative ramps introduced a defect healing effect reducing coating porosity and roughness. • Corrosion resistance of refined coating was proved to be better by EIS measurement.

Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization

PurposeThe intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method.Design/methodology/approachBased on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016.FindingsUnder the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO2 and [0, 51,800.942] ktCO2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas.Originality/valueWhile many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit.

Mapping dynamic peri-urban land use transitions across Canada using Landsat time series: Spatial and temporal trends and associations with socio-demographic factors

Transformations of agriculture and natural lands to urban use are dominant and well known effects of urbanization, but consistent and reliable methods to map regional-scale land transitions are limited. Herein, we develop a land use classification approach to assess spatiotemporal patterns of urban expansion and associated land use changes. We utilized a 33-year annual time series (1984–2016) of fractional land characteristics and cover data from Landsat satellite imagery to summarize multidecadal land use transitions on the pixel and census dissemination area level for 18 major Canadian cities. Across Canada, 41% of peri-urban areas analyzed experienced a transition, converting about 2,700 sq-km of natural and/or agriculture to an urban use. West coast peri-urban areas observed the greatest area conversion of natural to urban use (39%). In contrast, peri-urban areas of the Prairies (i.e. west-center stratum) experienced the greatest area transition from an agriculture to urban use (41%), while west- and east-center observed marked rates of natural to urban transitions (3.9 and 3.5% per annum per sq-km, respectively). Current high population densities were generally associated with historic losses of agriculture or natural use, while regional differences in correlations between land use trends and current levels of income, new residential construction, and single-detached housing highlight the potential influence of urban policies and historic socio-economic trajectories. The developed dynamic land use classification provides a reliable, transparent, and nationally consistent method to tabulate land use intensity across various spatiotemporal scales and may enhance interpretation of interdisciplinary studies involving social and community outcomes.

Reality analysis of the state of spatial distribution of green areas using geographic information systems (GIS) – The holy city of Najaf as a case study

Green areas are an essential component of city planning, as they serve as an outlet for them to spend their free time, in addition to the environmental role that these green areas play in improving the city’s climate by purifying the air and beautifying the city. The study’s problem is summarized in identifying the appropriateness of the current spatial distribution of green areas in the city of Najaf with the current population densities and the pattern in which green areas are distributed using GIS and knowing the per capita share of those green areas in the city, the research assumes that the inconsistency of spaces between regions Green and residential neighbourhoods need to conform to the standards for the individual share. The research also aims to know the reality of the green areas in the holy city of Najaf using GIS to take advantage of the capabilities provided by the program in the field of entering and analysing information related to its spatial distribution, as well as identifying the pattern in which the green areas are distributed in the city of Najaf, and come up with recommendations and proposals to address the existing imbalance. The research found that more than half of the neighbourhoods in the region do not conform to the standard followed in assessing the individual’s share, where the individual’s share ranged between (0.4-3.9) square meters, and there are neighbourhoods completely devoid of green areas, and this is due to poor planning in those areas. On the neighbourhood link index, the pattern of distribution of these green areas was aggregated to random. As for the Moran coefficient, its value departed from one frequently, indicating a weak spatial and random correlation of green areas, The area reached by the impact area of the green areas reached (5512) hectares, which is equivalent to (83.32%) of the total area of the Holy City of Najaf, and the neighbourhoods near the middle centre and surrounding it are the most intersecting neighbourhoods in the impact area.

Combining camera‐trap surveys and hunter interviews to determine the status of mammals in protected rainforests and rubber plantations of Menglun, Xishuangbanna, SW China

AbstractHunting and deforestation are the two biggest threats to vertebrates in Southeast Asia. In the last 50 years, monoculture rubber plantations replaced large areas of tropical rainforests in Xishuangbanna, southwest China. We set up camera traps at 109 stations (57 in forest reserves and 52 in rubber plantations) to determine the distribution of mammal species in Menglun, Xishuangbanna. We also interviewed 37 experienced hunters (mean age: 54) in the study area to understand their perceptions of species abundance trends. We used hierarchical multispecies occupancy modelling to determine the effect of distance to village, distance to forest edge and elevation on mammal occupancy after accounting for imperfect detection. We used non‐parametric tests for the rank data to evaluate perceived species trends. Using a combination of historical literature (1954–1985), hunter interviews, direct observations and camera‐trap surveys, we only recorded 56% (15 out of 27) of the medium‐to‐large sized (>1 kg) mammal species known previously from the study region. Interviews suggested that current population densities of all extant mammal species are below historical levels. Our camera traps captured 11 mammal species in the forest reserve and only two species in rubber plantations. Low capture rates (10 captures) in rubber mean we could only determine mammal occupancy in forests. Environmental variables did not affect community level mammal occupancy in forests, but common muntjac (Muntiacus muntjak) and the northern pig‐tailed macaque (Macaca leonina) avoided forest edges. At the time of the survey, hunting was still prevalent in the region. Therefore, conservation interventions that end both hunting and deforestation are urgently needed to stabilize and increase mammal populations in the region.

Normal-form analysis of the cusp-transcritical interaction: applications in population dynamics

Bistability, the presence of alternative stable states, is an important feature of population models as it indicates that long-term predictions are dependent on the current population density. Two distinct kinds of bistability re-occur in population modelling studies, Allee Bistability and Positive Bistability. In this article, we show that a novel codimension-3 bifurcation, the cusp-transcritical interaction, can act as an organising centre for ordinary differential equations that exhibit both Allee Bistability and Positive Bistability. We first show how a normal form for cusp-transcritical interactions emerges from the unfolding of a particular one-dimensional degeneracy. We then illustrate the ecological relevance of the cusp-transcritical interaction. Finally, we provide a comprehensive example of normal-form analysis of an existing population model that demonstrates the occurrence of the codimension-3 bifurcation. We note that Allee Bistability and Positive Bistability may manifest unexpectedly in complex, ecological models, and therefore, this bifurcation-focused approach can provide valuable insight into the behaviour of newly developed ecosystem models.

Seasonal movements and site utilisation by Asian water buffalo (Bubalus bubalis) in tropical savannas and floodplains of northern Australia

Abstract ContextThe Asian water buffalo (Bubalus bubalis) is an introduced herbivore of the savannas and floodplains of northern Australia. Despite the significant environmental damage caused by water buffalo, important cultural and commercial stakeholders request this species is managed rather than eradicated. However, gaps in knowledge of buffalo ecology limit effective policy and planning. AimsTo better understand how buffalo, at current population densities, respond to seasonally changing resources in the two key habitat types that they occupy in northern Australian – upland eucalypt savanna and seasonally inundated floodplain. MethodsSatellite telemetry was used to record the location of a single female buffalo from each of 11 independent clans every hour over a 12-month period. Generalised linear mixed modelling was used to assess the extent to which buffalo movements, activity-space and site revisitation correlated with forage quality (inferred from the normalised difference vegetation index – NDVI) and localised buffalo density. Key resultsAs the dry season progressed, forage quantity and quality within the activity-space of buffalo clans decreased. In response, buffalo inhabiting floodplain exhibited increased rates of movement and enlarged the size of their activity-space. This resulted in low repeated visitation of foraging areas in the late dry season and NDVI remained relatively high within these areas. In comparison, buffalo in upland savanna maintained similar rates of activity and occupied the same activity-space size throughout the year. This resulted in frequent revisitation of the same areas in the late dry season and NDVI reached as low as zero in these foraging areas. Clan size and localised buffalo density had no significant effect on measured movement parameters. ConclusionsBuffalo exhibited a behavioural strategy in upland savanna that resulted in acute removal of green herbaceous vegetation within a few kilometres of the clan’s permanent water source. Buffalo inhabiting the floodplain used multiple wallows that reduced grazing impacts, but likely resulted in hoof-derived impacts over a broad area. ImplicationsCurrent buffalo densities in Kakadu National Park appear to be well below carrying capacity but localised environmental degradation around permanent water sources remains severe in upland savanna.

Fitness of the pestiferous small rodent Mastomys natalensis in an agroecosystem in Mayuge district, Lake Victoria Crescent, Uganda

Abstract A 2.5-year study was conducted to understand the fitness of Mastomys natalensis in an agroecosystem in relationship with environmental predictors. The study was conducted in Mayuge district, in the Lake Victoria Crescent zone in Eastern Uganda. Fitness was measured in terms of survival, maturation and capture probability and estimated using multi-event capture-recapture models. Survival rates were higher after high rainfall in the previous month and increased with increasing population density of the animals. Maturation rate, on the other hand, showed no significant association with any predictor variables, while capture probability was significantly associated with sex of the animals, with higher capture probability for males. The results demonstrate that the fitness of M. natalensis in an agroecosystem is dependent on rainfall, sex and current population density. The aforementioned results were associated with increasing vegetation which provides cover for animal nesting and abundant food for the animals during rainfall periods and thus increased survival, high mobility in males in search for mates thus exposing animals to high chances of being captured and increased prey saturation at high population density resulting in high animal survival. These results have important implications for the timing of management strategies, i.e. control efforts should be enforced during the rainfall seasons to prevent high population buildup in the succeeding seasons.

Monitoring hawksbill turtle nesting sites in some protected areas from the Persian Gulf

Iranian nesting populations of the critically endangered hawksbill turtle (Eretmochelys imbricate) are some of the most important in the Indian Ocean. In this study, four of the most important hawksbill nesting grounds in the Persian Gulf, situated within three Iranian marine protected areas, were surveyed during nesting season, including Nakhiloo, Ommolgorm and Kharko Islands and the mainland beaches of the Naiband Marine-Coastal National Park (NMCNP). We present GIS maps of these key nesting grounds and describe sand texture of key nesting zones, along with conservation recommendations. About 9.2 (28.3%) out of 32.5 km of all shores surveyed in this study were used by nesting hawksbill turtles follows: Nakhiloo: 1.4 km (52% of potential nesting area); Ommolgorm: 1.94 km (40%); Kharko: 3.4 km (28%), and NMCNP: 2.46 km (18.9%). The average nesting density was calculated as 131 nests/km at Nakhiloo, 76 nests/km at Ommolgorm, 7 nests/km at Kharko, and 15 nests per km at NMCNP. Highest nesting density was observed in Nakhiloo and Ommolgorm. It is thought that high hawksbill nesting density in these islands seems likely a result of limiting adequate nesting shores rather than the size of population, and also low density in Kharko and NMCNP more related to past and current pressures and low population density. With the exception of Ommolgorm Island, sands at the nesting grounds were well sorted. Grain size indicated that female hawksbill turtles in the Iranian Persian Gulf nest in sands that are generally mixed, with mean grain size ranging from coarse sands (0.4Φ; ~0.5-1 mm) to fine sands (2Φ; ~0.25 mm). We provide and discuss conservation recommendations and suggestions for future.