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The relationship between resource availability and wildlife movement patterns is pivotal to understanding species behavior and ecology. Movement response to landscape variables occurs at multiple temporal scales, from sub-diurnal to multiannual. Additionally, individuals may respond to both current and past conditions of resource availability. In this paper, we examine the temporal scale and variation of current and past resource variables that affect movement patterns of African elephants (Loxodonta africana) using sub-hourly movement data from GPS-GSM collared elephants in Etosha National Park, Namibia. We created detailed satellite-based spatiotemporal maps of vegetation biomass, as well as distance from surface water, road and fence. We used step selection functions to measure the relative importance of these landscape variables in determining elephants' local movement patterns. We also examined how elephants respond to information, in locations they have previously visited, on productivity integrated over different temporal scales: from current to historical conditions. Our results demonstrate that elephants choose patches with higher than average annual productivity and grass biomass, but lower tree biomass. Elephants also prefer to walk close to water, roads, and fences. These preferences vary with time of day and with season, thereby providing insights into diurnal and seasonal behavioral patterns and the ecological importance of the landscape variables examined. We also discovered that elephants respond more strongly to long-term patterns of productivity than to immediate forage conditions, in familiar locations. Our results illustrate how animals with high cognitive capacity and spatial memory integrate long-term information on landscape conditions. We illuminate the importance of long-term high temporal resolution satellite imagery to understanding the relationship between movement patterns and landscape structure.

Summary In species with complex life cycles, population dynamics result from a combination of intrinsic cycles arising from delays in the operation of negative density‐dependent processes (e.g. intraspecific competition) and extrinsic fluctuations arising from seasonal variation in the abiotic environment. Abiotic variation can affect species directly through their life‐history traits and indirectly by modulating the species’ interactions with resources or natural enemies. We investigate how the interplay between density‐dependent dynamics and abiotic variability affects population dynamics of the bordered plant bug (Largus californicus), a Hemipteran herbivore inhabiting the California coastal sage scrub community. Field data show a striking pattern in abundance: adults are extremely abundant or nearly absent during certain periods of the year, leading us to predict that seasonal forcing plays a role in driving observed dynamics. We develop a stage‐structured population model with variable developmental delays, in which fecundity is affected by both intraspecific competition and temporal variation in resource availability and all life‐history traits (reproduction, development, mortality) are temperature‐dependent. We parameterize the model with experimental data on temperature responses of life‐history and competitive traits and validate the model with independent field census data. We find that intraspecific competition is strongest at temperatures optimal for reproduction, which theory predicts leads to more complex population dynamics. Our model predicts that while temperature or resource variability interacts with development‐induced delays in self‐limitation to generate population fluctuations, it is the interplay between all three factors that drive the observed dynamics. Considering how multiple abiotic factors interact with density‐dependent processes is important both for understanding how species persist in variable environments and predicting species’ responses to perturbations in their typical environment. Lay Summary

ContextMovement is one of the key mechanisms for animals to deal with changes within their habitats. Therefore, resource variability can impact animals’ home range formation, especially in spatially and temporally highly dynamic landscapes, such as farmland. However, the movement response to resource variability might depend on the underlying landscape structure.ObjectivesWe investigated whether a given landscape structure affects the level of home range size adaptation in response to resource variability. We tested whether increasing resource variability forces herbivorous mammals to increase their home ranges.MethodsIn 2014 and 2015 we collared 40 European brown hares (Lepus europaeus) with GPS-tags to record hare movements in two regions in Germany with differing landscape structures. We examined hare home range sizes in relation to resource availability and variability by using the normalized difference vegetation index as a proxy.ResultsHares in simple landscapes showed increasing home range sizes with increasing resource variability, whereas hares in complex landscapes did not enlarge their home range.ConclusionsAnimals in complex landscapes have the possibility to include various landscape elements within their home ranges and are more resilient against resource variability. But animals in simple landscapes with few elements experience shortcomings when resource variability becomes high. The increase in home range size, the movement related increase in energy expenditure, and a decrease in hare abundances can have severe implications for conservation of mammals in anthropogenic landscapes. Hence, conservation management could benefit from a better knowledge about fine-scaled effects of resource variability on movement behaviour.

A lack of natural resources drives the oil dependency in Pacific Island Countries and Territories (PICTs), hampering energy security and imposing high electricity tariffs in the region. Nevertheless, the Western Equatorial Pacific is known for its large Sea Surface Temperature (SST) and deep-sea water (DSW) temperature difference favorable for harvesting thermal energy. In this study, we selected 18 PICTs in the western Equatorial Pacific to estimate Annual Energy Production (AEP) for a 1 MW class Ocean Thermal Energy Conversion (OTEC) plant. We combined the DSW temperature from the mean in situ Argo profiles and 1 km resolution satellite SST data to estimate the thermal energy resource resolving the fine features of the island coastline. Furthermore, the twenty-year-long SST dataset was used to analyze the SST variability. The analysis showed that Equatorial islands and Southern islands have the highest inter-annual variability due to El Nino Southern Oscillation (ENSO). The power density varied from 0.26 to 0.32 W/m2 among the islands, with the lowest values found for the southernmost islands near the South Equatorial Countercurrent. Islands within the South Equatorial Current, Equatorial Undercurrent, and North Equatorial Countercurrent showed the highest values for both power density and gross power. Considering a 1 MW class OTEC plant, Annual Energy Production (AEP) in 2022 varied from 7 GWh to 8 GWh, with relatively low variability among islands near the Equator and in low latitudes. Considering the three variables, AEP, SST variability, and distance from the shore, Nauru is a potential candidate for OTEC, with a net power of 1.14 MW within 1 km from the shore.

The operational quality and reliability of a manufacturing system is greatly influenced by uncertain or variable environments, therefore robustness is one of the most important indicators for measuring the operational quality of the non-repetitive dynamic manufacturing system. Controlling the order release to limit work in process at a stable level and protect throughput from variation is crucial to achieving robustness of manufacturing system performance. To deal with the influences of bottleneck severity and variable resource on system performance, a refined order release method is presented, which releases order periodically based on the corrected aggregate load and continuously based on the bottleneck buffer load. The operational quality of this method with the classical order release method under non-repetitive dynamic manufacturing system is compared by modeling and simulation. The results show that the refined order release method is more robust for general flow shop with higher protective capacity and resource variability.

Ectotherms exhibit considerable plasticity in their life-history traits. This plasticity can reflect variability in environmental and social factors, but the causes of observed patterns are often obscured with increasing spatial scales. We surveyed dichromatic parrotfishes across the northern Great Barrier Reef to examine variation in body size distributions and concomitant size at sex change (L Δ50) against hypotheses of directional influence from biotic and abiotic factors known to affect demography. By integrating top-down, horizontal, and bottom-up processes, we demonstrate a strong association between exposure regimes (which are known to influence nutritional ecology and mating systems) and both body size distribution and L Δ50 (median length at female-to-male sex change), with an accompanying lack of strong empirical support for other biotic drivers previously hypothesized to affect body size distributions. Across sites, body size was predictably linked to variation in temperature and productivity, but the strongest predictor was whether subpopulations occurred at sheltered mid and inner shelf reefs or at wave-exposed outer shelf reef systems. Upon accounting for the underlying influence of body size distribution, this habitat-exposure gradient was highly associated with further L Δ50 variation across species, demonstrating that differences in mating systems across exposure gradients affect the timing of sex change beyond variation concomitant with differing overall body sizes. We posit that exposure-driven differences in habitat disturbance regimes have marked effects on the nutritional ecology of parrotfishes, leading to size-related variation in mating systems, which underpin the observed patterns. Our results call for better integration of life-history, social factors, and ecosystem processes to foster an improved understanding of complex ecosystems such as coral reefs.

The extraction of tidal energy from head differences represents a predictable and flexible option for generating electricity. Here, we investigate the generation potential of prospective tidal power plants in the UK. Originally conceived as separate projects, operating these schemes as a cooperative system could prove beneficial. Combined with the inherent operational flexibility of tidal range-based schemes, a notable tidal phase difference in selected sites allows for the system to spread power generation over a larger proportion of the day. Using depth-averaged modelling and gradient-based optimisation techniques, we explore how a flexible cumulative operation schedule could be applied to provide a degree of continuous supply if desirable. While fully continuous operation is not achieved, a number of different optimisation schedules deliver cumulative continuous supply for over half of the year. The average minimum cumulative power output on these days is consistently over 500 MW out of a total installed capacity of 6195.3 MW. Furthermore, by introducing financial incentives associated with reliable, baseload supply, we provide an economic assessment of the tidal power plant system. The daily minimum cumulative power output determines income in the modelled idealised baseload market, while excess supply is traded in an hourly variable wholesale energy market. Results indicate that subsidies would be required in order to make a pursuit of continuous generation financially advantageous over energy maximisation strategies.

Wave characteristic assessments of wave energy test sites provide a greater understanding of prevailing wave conditions and are therefore extremely important to both wave energy test site operators and clients as they can inform wave energy converter design, optimisation, deployment, operation and maintenance. This research presents an assessment of the wave resource at the Atlantic Marine Energy Test Site (AMETS) on the west coast of Ireland based on 12-years of modelled data from January 2004 to December 2015. The primary aim is to provide an assessment of annual and seasonal wave characteristics and resource variability at the two deployment berths which comprise the site. A nested model has been developed using Simulating WAves Nearshore (SWAN) to replicate wave propagations from regional to local scale with a 0.05° resolution model covering the northeast Atlantic and a 0.0027° resolution model covering AMETS. The coarse and fine models have been extensively validated against available measured data within Irish waters. 12-year model outputs from the high resolution model were analysed to determine mean and maximum conditions and operational, high and extreme event conditions for significant wave height, energy period and power. Annual and seasonal analyses are presented. The 12-year annual mean P were 68 kW/m at Berth A (BA) and 57 kW/m at Berth B (BB). The resource shows strong seasonal and annual variations and the winter mean power levels were found to be strongly correlated with the North Atlantic Oscillation (NAO).

The size of organisms may result from various, sometimes antagonistic forces operating on distinct traits, within an evolutionary framework that may also be constraining. Morphological allometry, referring to the way trait size scales with body size, has been shown to reflect ecological adaptation to the mean size of the resource exploited. We examined the allometric relationships between rostrum and body size among four insect (Curculio spp.) specialists of oak acorns. In all four species, weevil females drill a hole with their rostrum prior depositing one or a few eggs inside the seed. The four weevil species, that coexist on the same individual trees, displayed partitioned egg-laying periods in the year, thereby encountering acorns of different size and maturation stage. We found marked differences in the allometric slope among females: species laying eggs late in the season had a steeper slope, leading to increasingly longer rostrum relative to body length, along with the mean size of the growing acorns. Females of the smallest species had the longest oviposition period and also had the steepest slope, which provided them with the most variable rostrum length, thereby matching the variable size of the resource through time. Our work highlights the need to consider not only the average size but also the degree of variability in resource size to understand the adaptive value of allometric relationships.

Human resources have played an important role in the production systems of manufacturing enterprises. At the same time, human resource allocation, as a scheduling problem, has attracted more and more attention from the industry and academia, with the increasing complexity of technology and the rising cost of workforce. However, the existing scheduling methods fail to fully consider the relationship between tasks and employees. In this paper we consider a single workgroup scheduling problem with the assumption of human resources variability. Jobs must be assigned to employees, where the number of processing personnel and the processing time are variable for one job. We model the problem as a combinatorial optimization problem and the objective considered is to minimize the maximum finish time which is called makespan. This problem is transformed into a two-dimension rectangle strip packing problem and we propose a hybrid optimization algorithm which combines scheduling algorithm with packing algorithm. Finally, different size cases are adopted to test the model. Results show the proposed strategy and algorithm are suitable for solving single workgroup scheduling very well.