Dynamic Occupancy Research Articles

Quantum polyspectra for modeling and evaluating quantum transport measurements: A unifying approach to the strong and weak measurement regime

Quantum polyspectra of up to fourth order are introduced for modeling and evaluating quantum transport measurements offering a powerful alternative to methods of the traditional full counting statistics. Experimental time traces of the occupation dynamics of a single quantum dot are evaluated via simultaneously fitting their second-, third-, and fourth-order spectra. The scheme recovers the same electron tunneling and spin relaxation rates as previously obtained from an analysis of the same data in terms of factorial cumulants of the full counting statistics and waiting-time distributions. Moreover, the evaluation of time traces via quantum polyspectra is demonstrated to be feasible also in the weak measurement regime even when quantum jumps can no longer be identified from time traces and methods related to the full counting statistics cease to be applicable. A numerical study of a double dot system shows strongly changing features in the quantum polyspectra for the transition from the weak measurement regime to the Zeno regime where coherent tunneling dynamics is suppressed. Quantum polyspectra thus constitute a general unifying approach to the strong and weak regime of quantum measurements with possible applications in diverse fields as nanoelectronics, circuit quantum electrodynamics, spin noise spectroscopy, or quantum optics.

Occupancy and Population Abundance of Two Serpent-Eagles (Spilornis elgini and S. cheela) in the Andaman Islands, India

ABSTRACT We estimated occupancy and population abundance of the Andaman Serpent-Eagle (Spilornis elgini) and Crested Serpent-Eagle (Spilornis cheela) in the Andaman Islands, India. We divided the islands that were > 100 km2 into a grid of 84 cells, of which we used 34 cells (5 km × 5 km each) for surveys of two populations in the districts of (1) the North and Middle Andaman Islands, and (2) the South Andaman Islands, which includes Little Andaman Island. We performed single-season, single-species occupancy modeling independently for both regions and single-season, two-species occupancy modeling for co-occupancy in the surveyed landscapes. The estimated abundance for the Andaman Serpent-Eagle and the Crested Serpent-Eagle was 4–5 and 7–8 individuals per 25 km2, respectively. The Andaman Serpent-Eagle is commonly distributed in both regions and has a high detection probability (detection probability, P = 0.8). The Crested Serpent-Eagle is widely distributed in the South Andaman Islands with a low detection probability (P = 0.5). The single-season, two-species occupancy model showed that the endemic Andaman Serpent-Eagle occupied only 22% of the area and did not co-occur with the Crested Serpent-Eagle. It also indicates the possible avoidance or exclusion of the Crested Serpent-Eagle by the Andaman Serpent-Eagle. We encountered both serpent-eagles in all the identified habitat types. The Crested Serpent-Eagle's habitat use was not restricted to the coastal forests, as previously reported, and the Crested Serpent-Eagle is probably dominating the Andaman Serpent-Eagle in the co-occupied areas. We further conclude that the occupancy dynamics and competition for space between these two Spilornis species might significantly affect the distribution and population of the vulnerable and endemic Andaman Serpent-Eagle in the future.

What is the effect of poaching activity on wildlife species?

Poaching is a pervasive threat to wildlife, yet quantifying the direct effect of poaching on wildlife is rarely possible because both wildlife and threat data are infrequently collected concurrently. In this study, we used poaching data collected through the Management Information System (MIST) and wildlife camera trap data collected by the Tropical Ecology Assessment and Monitoring (TEAM) network from 2014 to 2017 in Volcanoes National Park, Rwanda. We implemented co-occurrence multi-season occupancy models that accounted for imperfect detection to investigate the effect of poaching on initial occupancy, colonization, and extinction of five mammal species. Specifically, we focused on two species of conservation concern (mountain gorilla [Gorilla beringei beringei] and golden monkey [Cercopithecus mitis kandti]), and three species targeted by poachers (black-fronted duiker [Cephalophus nigrifrons], bushbuck [Tragelaphus scriptus], and African buffalo [Syncerus caffer]). We found that the probability of local extinction was highest in sites with poaching activity for golden monkey and bushbuck. In addition, the probability of initial occupancy for golden monkey was highest in sites without poaching activity. We only found weak evidence of effects of poaching on parameters governing the occupancy dynamics of the other species. All species showed evidence of poaching presence affecting the probability of detection of the wildlife species. This is the first study to our knowledge to combine direct threat observations from ranger-based monitoring data with camera trap wildlife observations to quantify the effect of poaching on wildlife. Given the widespread collection of ranger-based monitoring and camera trap data, our approach is broadly applicable to numerous protected areas and has the potential to significantly improve conservation management. Specifically, the relationship between poaching activity and wildlife population dynamics can be combined with information on the relationship between ranger patrols and poaching activity to develop models useful for making wise decisions about ranger patrol deployment.

Unpacking How Employees Navigate Unfulfilled, Unreasonable, and Unexpected Occupational Ideals

Occupations have become stabilizing fixtures of modern-day employment, providing employees with a set of established cultural tools, norms, values, and beliefs that offer meaning to employees and guide their workplace interpretations and action. Yet, as employees perform their occupations “on the ground”, they frequently encounter situations that challenge these occupational meaning systems. This symposium showcases four papers that develop novel theory about how individuals respond to incongruities between situational demands, environmental constraints, and audiences’ expectations, on the one hand, and occupational norms, values, and beliefs, on the other hand. More specifically, we examine (1) how workers counter harmful occupational cultures, (2) how women in male-dominated occupations transcend their status as female “tokens”; (3) how employees respond to labels (e.g., “hero”) cast upon their occupation by external audiences; and (4) how employees manage frequent exposure to tasks that conflict with their occupational ideologies extolling the nature and necessity of the work. Taken together, our papers and discussion endeavor to contribute to and generate future research on contemporary occupational dynamics, as well as deliver actionable insights for managers. Meaning Detachment and Deviation from Invincibility Cultural Scripts among Stunt Performers Presenter: Winnie Jiang; INSEAD Presenter: Karim Ginena; U. of Virginia Darden School of Business Transcending Tokenism: How Women in Male-Dominated Occupations Can Challenge Gendered Work Norms Presenter: Julia DiBenigno; Yale School of Management Heroes from Above and from Below: Workers’ Reactions to the Moralizing of their Work Presenter: Lindsey Cameron; The Wharton School, U. of Pennsylvania Presenter: Michel Anteby; Boston U. Questrom School of Business The Music Between the Notes: How Employees Manage Unforeseen Work Realities Presenter: Pascale Fricke; U. of British Columbia Presenter: Natalya Alonso; Haskayne School of Business, U. of Calgary Presenter: Patrick Reilly; U. of British Columbia

High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape

Groundwater upwellings provide warmer, stable overwinter temperatures for developing salmon embryos, which may be particularly important in cold, braided, gravel-bed sub-Arctic rivers. We used a three-year time series of aerial counts and remote sensing to estimate the distribution of low and high aggregations of spawning fall chum salmon (Oncorhynchus keta), classify approximately 0.5 km long river segments by geomorphic channel type, and map thermal variability along a 25.4 km stretch of the Teedriinjik River, Alaska. We used a dynamic multistate occupancy model to estimate detectability, occupancy, and the dynamics of spawning aggregations among river segments. Detectability was higher for large (>150) relative to smaller aggregations. Unoccupied segments were likely to remain so from year to year; low abundance spawning segments were dynamic and rarely remained in that state for multiple years, while ∼20%–35% of high abundance segments remained stable, indicating the presence of high-quality spawning habitat. Spawning habitat use was associated with warmer water temperatures likely caused by groundwater upwellings. We identified spawning habitat characteristics and trends in usage by fall chum salmon, which will inform land management decisions and assist in evaluating impacts of shifting climate conditions and resource management on Arctic salmon populations.

Learning-based CO2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2 concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-art learning algorithms—including Support Vector Machine, AdaBoost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provided ventilation as needed per the ASHRAE standards.

The promise and peril of youth entrepreneurship in the Middle East and North Africa

PurposeEntrepreneurship is promoted as a solution to high rates of youth unemployment around the world and especially in the Middle East and North Africa (MENA). This paper investigates the potential for youth entrepreneurship to alleviate unemployment, focusing on Egypt, Jordan and Tunisia.Design/methodology/approachThe authors examine who entrepreneurs are (in comparison to the unemployed), using multinomial logit models. The authors compare entrepreneurs' and wage workers' working conditions and earnings. They exploit panel data to assess earnings and occupational dynamics. They specifically use the Labor Market Panel Surveys of 2012 (Egypt), 2016 (Jordan), and 2014 (Tunisia), along with previous waves.FindingsThe authors find that entrepreneurs are the opposite of the unemployed in MENA. The unemployed are disproportionately young, educated and women. Entrepreneurs are older, less educated and primarily men. Entrepreneurship does not generally lead to higher earnings and does have fewer benefits.Originality/valuePromoting youth entrepreneurship is not only unlikely to be successful in reducing youth unemployment in MENA, but also, if successful, may even be harmful to youth.

Evaluating the dynamics of occupancy heat gains in a mid-sized airport terminal through agent-based modelling

The occupancy heat gains of airport terminal buildings are driven by the dynamics of passenger flow. In this paper, we evaluate the heat losses from the human body in a transient state to estimate the sensible and latent loads on the HVAC system. The study pertains to a mid-sized airport terminal building in a tropical wet and dry climate of India. The pattern of passenger movement, service time and discretionary activity choices are evaluated through field measurement and subjective surveys. The sequence of passenger movement, dwell time and occupancy profile at different zones for departure and arrival sequences are estimated through validated agent-based simulations. Transient heat losses from the human body are established through thermo-physiology simulations based on the occupancy dynamics. Hourly sensible and latent heat load profiles of different zones are deduced for different terminal operation periods. The evaporative heat losses from human body varies considerably during passenger transit resulting in significant latent heat gain differences among the zones. Despite lower activity levels in certain zones, latent heat loads from occupancy are higher because of preceding activity sequences. The sensible to latent heat load ratio varies from 0.7:0.3 to 0.52:0.48 across the zones during different operational periods.

Modeling multi‐scale occupancy for monitoring rare and highly mobile species

AbstractOccupancy‐based methods are commonly used to model the distribution, habitat use, and relative abundance of species. In particular, occupancy‐based methods are often recommended for monitoring species, allowing researchers to track population trends using detection–non‐detection data alone. Occupancy models, however, have proven difficult to apply to rare, highly mobile species. Species’ movements outside of sampling areas may lead to violation of the geographic closure assumption of occupancy models and overestimated occupancy probability. Low detection probability may further inflate occupancy probability estimates. We developed a novel continuous‐time, multi‐scale occupancy model to simultaneously account for closure assumption violations and low detection probability. We used a simulation study to test our model relative to a discrete‐time multi‐scale model, and we conducted a power analysis to assess the ability of an instantaneous occupancy parameter to detect trends in abundance, relative to standard occupancy alone. The continuous‐time model was competitive with the discrete‐time model and was generally computationally faster than and outperformed the discrete‐time model when detection probability was low. The instantaneous occupancy parameter outperformed occupancy in terms of power to detect trends when we used an implicit (i.e., estimating occupancy independently in each primary occasion) dynamic occupancy model, but performed no better when we used an explicit (i.e., estimating colonization and extinction) dynamic occupancy model. We applied both discrete‐time and continuous‐time multi‐scale occupancy models to a case study of data collected on wolverines (Gulo gulo) in Washington, USA. We found improved precision in estimates with the continuous‐time model and that asymptotic occupancy of wolverines was high, but short‐term use of any given area was low. Our multi‐scale, continuous‐time occupancy model can be used to detect trends in abundance of rare, highly mobile species, regardless of how occupancy dynamics are modeled. Furthermore, our model can allow for more efficient data collection and analysis than traditional discrete‐time or spatially multi‐scale approaches, as our model uses all available detections and requires only one detector per sampling unit by substituting time for space.

Landscape Transformation: Exploring Operations in The Traditional Practice of Brickmaking

This paper investigates the landscape transformation driven by the traditional brick making practice, arguing that brickmaking is a dialectical interaction between the landscape and the particular operations conducted by craftsmen across landscapes. Yet the discussion of the traditional practice of brickmaking itself has not been significantly valued as an important operation that drives the process of landscape transformation. The study investigates two brickmaking workshops in Central Java, Ambarawa and Brebes, that utilise the in-situ material for the brickmaking practice. Through visual documentation and interviews during field observations, it is revealed that various operations involved in the traditional brickmaking practice are utilised by the natural opportunities within the context, not only for sourcing raw material but also other activities in brickmaking. The findings also suggest that such operations demonstrate the understanding of landscape as a resource and place of transformation, reflected through its spatial and temporal arrangements. This paper arguably expands the discussion of brickmaking not only as an ecological architecture material production but as the basis of understanding dynamic occupation of a context.

Offline Dynamic Grid Generation for Automotive Environment Perception Using Temporal Inference Methods

The validation of online perception algorithms in automotive systems requires a large amount of ground-truth data. Since manual labeling is inefficient and error-prone, an automatic generation of accurate and reliable reference data is desirable. We present a post-processing approach based on a particle-based dynamic occupancy grid representation of the environment. In contrast to existing online dynamic grid algorithms, our estimation additionally utilizes future measurements by applying offline smoothing algorithms. Our proposed concept uses a two-filter procedure for smoothing the occupancy states of the grid cells. We further introduce two methods based on particle reweighting and two-filter smoothing to improve the velocity estimates. We show that our approach enhances the situational awareness and thus provides a more precise environment model. We demonstrate these benefits using lidar data from real-world experiments.

Dynamic landscape of protein occupancy across the Escherichia coli chromosome.

Free-living bacteria adapt to environmental change by reprogramming gene expression through precise interactions of hundreds of DNA-binding proteins. A predictive understanding of bacterial physiology requires us to globally monitor all such protein-DNA interactions across a range of environmental and genetic perturbations. Here, we show that such global observations are possible using an optimized version of in vivo protein occupancy display technology (in vivo protein occupancy display-high resolution, IPOD-HR) and present a pilot application to Escherichia coli. We observe that the E. coli protein-DNA interactome organizes into 2 distinct prototypic features: (1) highly dynamic condition-dependent transcription factor (TF) occupancy; and (2) robust kilobase scale occupancy by nucleoid factors, forming silencing domains analogous to eukaryotic heterochromatin. We show that occupancy dynamics across a range of conditions can rapidly reveal the global transcriptional regulatory organization of a bacterium. Beyond discovery of previously hidden regulatory logic, we show that these observations can be utilized to computationally determine sequence specificity models for the majority of active TFs. Our study demonstrates that global observations of protein occupancy combined with statistical inference can rapidly and systematically reveal the transcriptional regulatory and structural features of a bacterial genome. This capacity is particularly crucial for non-model bacteria that are not amenable to routine genetic manipulation.

The History and Driving Force for Prehistoric Human Expansion Upward to the Hinterland of the Tibetan Plateau Post–Last Glacial Maximum

The timing and motivation of prehistoric human expansion into the hinterland of the Tibetan Plateau (TP) is a widely debated scientific issue. Recent archaeological studies have brought forward predictions of the earliest human occupation of the TP to the late–Middle Pleistocene. However, massive human occupation of the TP did not appear until the termination of the Last Glacial Maximum (LGM). The spatio-temporal distribution of prehistoric hunter-gatherers on the TP varies significantly before the permanent occupation after 3600 BP (before present). Here, we report on environmental-archaeological evidence from the Canxionggashuo (CXGS) site in Yushu Prefecture, which provides information that is key to understanding the dynamics of post-LGM human occupation on the TP. Radiocarbon dating has revealed two occupation periods of the CXGS site at 8600–7100 cal (calibrated years) BP and 2400–2100 cal BP. The charcoal concentration in cultural layers correlates well with paleo–human activities. Hunter-gatherers expanded westwards from the northeastern margin of the TP to the hinterland of the TP during the warming period of the early–middle Holocene (~11,500–6000 BP). However, these groups retreated during the middle–late Holocene (~6000–3600 BP) under a cooling-drying climate. Prehistoric humans finally occupied the hinterland of the TP permanently after 3600 BP, with an enhanced cold-adaptive lifestyle, although the climate was still deteriorating.

Can dynamic occupancy models improve predictions of species' range dynamics? A test using Swiss birds.

Predictions of species' current and future ranges are needed to effectively manage species under environmental change. Species ranges are typically estimated using correlative species distribution models (SDMs), which have been criticized for their static nature. In contrast, dynamic occupancy models (DOMs) explicitily describe temporal changes in species' occupancy via colonization and local extinction probabilities, estimated from time series of occurrence data. Yet, tests of whether these models improve predictive accuracy under current or future conditions are rare. Using a long-term data set on 69 Swiss birds, we tested whether DOMs improve the predictions of distribution changes over time compared to SDMs. We evaluated the accuracy of spatial predictions and their ability to detect population trends. We also explored how predictions differed when we accounted for imperfect detection and parameterized models using calibration data sets of different time series lengths. All model types had high spatial predictive performance when assessed across all sites (mean AUC>0.8), with flexible machine learning SDM algorithms outperforming parametric static and DOMs. However, none of the models performed well at identifying sites where range changes are likely to occur. In terms of estimating population trends, DOMs performed best, particularly for species with strong population changes and when fit with sufficient data, while static SDMs performed very poorly. Overall, our study highlights the importance of considering what aspects of performance matter most when selecting a modelling method for a particular application and the need for further research to improve model utility. While DOMs show promise for capturing range dynamics and inferring population trends when fitted with sufficient data, computational constraints on variable selection and model fitting can lead to reduced spatial accuracy of predictions, an area warranting more attention.

Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians.

Monitoring programs serve to detect trends in the distribution and abundance of species. To do so, monitoring programs often use static state variables. Dynamic state variables that describe population dynamics might be more valuable because they allow for a mechanistic understanding of the processes that lead to population trends. We fit multistate occupancy models to data from a country-wide multispecies amphibian occupancy monitoring program and estimated occupancy and breeding probabilities. If breeding probabilities are determinants of occupancy dynamics, then they may serve in monitoring programs as state variables that describe dynamic processes. The results showed that breeding probabilities were low and that a large proportion of the populations had to be considered to be non-breeding populations (i.e., populations where adults are present but no breeding occurs). For some species, the majority of populations were non-breeding populations. We found that non-breeding populations have lower persistence probabilities than populations where breeding occurs. Breeding probabilities may thus explain trends in occupancy but they might also explain other ecological phenomena, such as the success of invasive species, which had high breeding probabilities. Signs of breeding, i.e., the presence of eggs and larvae, were often hard to detect. Importantly, non-breeding populations also had low detection probabilities, perhaps because they had lower abundances. We suggest that monitoring programs should invest more in the detection of life history stages indicative of breeding, and also into the detection of non-breeding populations. We conclude that breeding probability should be used as a state variable in monitoring programs because it can lead to deeper insights into the processes driving occupancy dynamics.

The Land-Use Change Dynamics Based on the CORINE Data in the Period 1990–2018 in the European Archipelagos of the Macaronesia Region: Azores, Canary Islands, and Madeira

Islands as peripheral and ultra-peripheral are typically highlighted as ecologically sensitive areas to human activities due to the tremendous biological diversity of beings and the future possibility of habitat loss. In this regard, the comprehension of the land occupation dynamics and trends in the ultra-peripheral territories is crucial to attempt long-lasting regional sustainability, as is the island region’s case. Therefore, the present article aims to analyze the trends and dynamics of the land-use changes on the European Archipelagos of the Macaronesia Region over the last three decades, using the CORINE (Coordination of Information on the Environment) data. Some of the obtained results show that about 3.4% of the Azores’ surface is characterized mainly by discontinuous urban fabric, representing 67% of the total urban fabric of the Azores over the last thirty years. Additionally, in Madeira Archipelago, the land is mainly occupied by forest and semi-natural areas, representing almost three-thirds of the territory. A similar scenario is verified in the Canary Islands, where forests and semi-natural areas represent approximately three-quarters of the territory. Once more, this study shows the relevance of the island areas’ unique character, which should be preserved and protected. Therefore, the priorities must be defined and established management strategies that are significant for the well-being of these highly valued areas. Moreover, the study showed that notable changes had occurred in the period 1990–2018 in this landscape. Hence there is a need for appropriate measures to mitigate these negative impacts on the environment.

Moose Habitat Selection and Fitness Consequences During Two Critical Winter Tick Life Stages in Vermont, United States†

The moose (Alces alces) is a charismatic species in decline across much of their southern distribution in North America. In the northeastern United States, much of the reduction has been attributed to winter tick (Dermacentor albipictus) infestations. Winter ticks are fairly immobile throughout all life stages, and therefore their distribution patterns at any given time are shaped largely by the occurrence of moose across the landscape during the peak of two critical time periods: fall questing (when ticks latch onto moose) and spring drop-off (when engorged female ticks detach from moose). We used recent land cover and lidar data within a dynamic occupancy modeling framework to estimate first-order habitat selection (use vs. non-use) of female moose (n = 74) during the tick questing and drop-off periods. Patch extinction and colonization rates between the fall questing and spring drop-off periods were strongly influenced by habitat and elevation, but these effects were diminished during the fall questing period when moose were more active across the landscape. From the fall questing period to the spring drop-off period, patches where colonization was high and extinction was low had higher proportions of young (shrub/forage) mixed forest at higher elevations. Further, we evaluated the fitness consequences of habitat selection by adult females during the fall questing period, when females and their calves acquire ticks. We compared Resource Selection Functions (RSF) for five females that successfully reared a calf to age 1 with five females whose calves perished due to ticks. Adult female moose whose offspring perished selected habitats in the fall that spatially coincided with areas of high occupancy probability during the spring tick drop-off period. In contrast, adult female moose whose offspring survived selected areas where the probability of occupancy during the spring drop-off was low; at present, natural selection may favor female adults who do not select the same habitats in fall as in spring. Our model coefficients and mapped results define “hotspots” that are likely encouraging the deleterious effects of the tick-moose cycle. These findings fill knowledge gaps about moose habitat selection that may improve the effectiveness of management aimed at reversing declining population trends.

Optimal allocation of law enforcement patrol effort to mitigate poaching activities.

Poaching is a global problem causing the decline of species worldwide. Optimizing the efficiency of ranger patrols to deter poaching activity at the lowest possible cost is crucial for protecting species with limited resources. We applied decision analysis and spatial optimization algorithms to allocate efforts of ranger patrols throughout a national park. Our objective was to mitigate poaching activity at or below management risk targets for the lowest monetary cost. We examined this trade-off by constructing a Pareto efficiency frontier using integer linear programming. We used data from a ranger-based monitoring program in Nyungwe National Park, Rwanda. Our measure of poaching risk is based on dynamic occupancy models that account for imperfect detection of poaching activities. We found that in order to achieve a 5% reduction in poaching risk, 622 ranger patrol events (each corresponding to patrolling 1-km2 sites) were needed within a year at a cost of US$49,760. In order to attain a 60% reduction in poaching risk, 15,560 patrol events were needed at a cost of US$1,244,800. We evaluated the trade-off between patrol cost and poaching risk based on our model by constructing a Pareto efficiency frontier and park managers found the solution for a 50% risk reduction to be a practical trade-off based on funding constraints (comparable to recent years) and the diminishing returns between risk mitigation and cost. This expected reduction in risk required 8,558 patrol events per year at a cost of US$684,640. Our results suggest that optimal solutions could increase efficiency compared to the actual effort allocations from 2006 to 2016 in Nyungwe National Park (e.g., risk reductions of ~30% under recent budgets compared to ~50% reduction in risk under the optimal strategy). The modeling framework in this study took into account imperfect detection of poaching risk as well as the directional and conditional nature of ranger patrol events given the spatial adjacency relationships of neighboring sites and access points. Our analyses can help to improve the efficiency of ranger patrols, and the modeling framework can be broadly applied to other spatial conservation planning problems with conditional, multilevel, site selection.

Artisanal Petroleum Refining and Occupational Dynamics in the Niger Delta Region, Nigeria

This study examines the occupational dynamics of the population as a result of artisanal refining of crude oil in the Niger Delta using structured questionnaire administered to 240 household heads selected from two settlements, one far from area of artisanal refineries (controlled settlement) and the other in area of artisanal refineries (experimental settlement). The questionnaire covered location and demographic characteristics of the respondents, as well as the typology of occupations. The pair-wise Student t-test and simple percentages were used to analyse the data collected. The study revealed that there were significant dynamics (t = -0.22, df =12, p<0.05) in the number of respondents in identified occupational typologies as indirect impact of artisanal refining in the experimental and controlled settlements. The study recommends the intensification of efforts to implement existing laws on environmental protection and provision of employment for teeming population. 
 Keywords: Artisanal Refineries, Occupational structure, Environmental degradation, Niger Delta.

Promoter G-quadruplex favours epigenetic reprogramming-induced atypical expression of ZEB1 in cancer cells

BackgroundAberrant expression of Zinc-finger E-box binding homeobox 1 (ZEB1), which remains repressed in normal cells, is frequently associated with cancer aggressiveness. However, transcriptional mechanism underlying such atypical ZEB1 expression in cancer is not yet well-understood. MethodsZEB1 promoter G-quadruplexes were studied and modeled extensively using circular dichroism, fluorescence spectroscopy, ITC and DMS protection assay. Luciferase assay, qPCR, FAIRE, ChIP, western blotting, confocal microscopy was used to access the regulation of ZEB1 transcription. ResultsOur study unravels the occupancy of nucleolin to ZEB1 promoter as a crucial determinant which facilitates the binding of SP1 transcription factor to chromatin, by locally remodelling the region. SP1, subsequently, recruits P300 acetyl transferase leading to enriched acetyl-histone H3 at promoter and activates ZEB1 transcription. ZEB1 promoter analysis identifies presence of four putative G-quadruplex (G4) forming motifs within 700 bp of TSS; each quadruplex is characterized structurally in details with an array of biophysical techniques. Surprisingly, stabilization of G4 with cationic porphyrin TMPyP4 represses its transcription and eventually impedes cell invasiveness. ConclusionsTMPyP4 binding to a selected G4 motif (5′ -534/−511–3′ from TSS), where nucleolin/SP1/P300 co-occupies, prevents the association of nucleolin which consequently hinders SP1 binding, leading to chromatin compactness and transcriptional repression. General significanceOur findings demonstrate an epigenetic mechanism of ZEB1 reactivation where dynamic occupancy of transcription regulators encompassing a G4 motif is crucial and thus, small molecule induced G-quadruplex stabilization may act as a potential molecular switch to turn-off gene expression.