Find research datasets worth reusing

opencc-by-4.0Feb 2022View details →

Data supporting "Crop yield after 5 decades of contrasting residue management"

Data supporting the pubblication "Crop yield after 5 decades of contrasting residue management" by Piccoli et al. (2020). Nutr Cycl Agroecosyst (2020) 117:231–241. https://doi.org/10.1007/s10705-020-10067-9(0123456789().,-volV() 0123458697().,-volV)

opencc-by-4.0Feb 2022View details →

Herbal plants for RIFA management

This dataset is used to evaluate the feasibility of planting herbal species for RIFA control.

opencc-zeroFeb 2023View details →

Influence of tree hollow characteristics and forest structure on saproxylic beetle diversity in tree hollows in managed forests in a regional comparison

Tree hollows are among the rarest habitats in today's Central European managed forests but are considered key structures for high biodiversity in forests. To analyze and compare the effects of tree hollow characteristics and forest structure on diversity of saproxylic beetles in tree hollows in differently structured managed forests, we examined between 41 and 50 tree hollows in beech trees in each of three state forest management districts in Germany. During the two-year study, we collected 283 saproxylic beetle species (5880 individuals; 22% threatened species), using emergence traps. At small spatial scales, size of hollow entrance and number of surrounding microhabitat structures positively influenced beetle diversity, while stage of wood mould decomposition had a negative influence, across all three forest districts. We utilized forest inventory data to analyze the effects of forest structure in radii of 50 to 500 m around tree hollows on saproxylic beetle diversity in the hollows. At these larger spatial scales, the three forest management districts differed remarkably regarding the parameters that influenced saproxylic beetle diversity in tree hollows. In Ebrach, characterized by mostly deciduous trees, the amount of dead wood positively influenced beetle diversity. In the mostly coniferous Fichtelberg forest district, with highly isolated tree hollows, in contrast, only the proportion of beech trees around the focal tree hollows showed a positive influence on beetle diversity. In Kelheim, characterized by mixed forest stands, there were no significant relationships between forest structure and beetle diversity in tree hollows. In this study, the same local tree hollow parameters influenced saproxylic beetle diversity in all three study regions, while parameters of forest structure at larger spatial scales differed in their importance, depending on tree-species composition.

openother-openMar 2022View details →

NIOO-QingZ/Geertruidenberg_Mesocosms: Towards climate-robust water quality management: testing the efficacy of different eutrophication control measures during a heat

Data and Codes used in the following open-access publication:  https://www.sciencedirect.com/science/article/pii/S0048969722015145

opencc-zeroMar 2022View details →

From nature reserve to mosaic management: improving matrix survival, not permeability, benefits regional populations under habitat loss and fragmentation

Although matrix improvement in fragmented landscapes is a promising conservation measure, matrix permeability (willingness of an organism to enter the matrix) and movement survival in the matrix are usually aggregated. Consequently, it is unknown which matrix property needs to be improved. It also remains unclear whether matrix upgrading from dispersal passage to providing reproduction opportunities has large conservation benefits and whether there are interactive effects between habitat and matrix management. We examined matrix effects on regional populations across a gradient of habitat loss and fragmentation using simulation experiments that integrated demographic processes and movement modeling based on circuit theory. We separately modified the levels of matrix permeability and movement survival to evaluate their individual effects. We also altered the amount and configuration of not only habitat but also improved matrix to assess their effects on population vital rates (size, survival and density). In binary landscapes comprising habitat and unimproved matrix, matrix movement survival had larger effects on population vital rates than matrix permeability. Increasing movement survival increased vital rates, yet, increasing matrix permeability decreased vital rates. Increased permeability required corresponding increased movement survival to offset potential negative population outcomes. When subsets of the matrix functioning as dispersal passage only (where no reproduction opportunities existed) were improved, increasing matrix permeability but holding movement survival constant reduced all vital rates, especially with increasing habitat fragmentation. In contrast, when movement survival increased, vital rates increased given strong habitat fragmentation. The benefits of upgrading dispersal passage to provide reproduction opportunities for population survival were greatest when habitat amount was moderate. We also found synergetic effects between amounts of habitat and improved matrix, and the benefits of matrix improvement were promoted when improvement was achieved in a spatially aggregated manner. Synthesis and applications: Matrix improvement and connectivity modeling aimed at increasing movement survival will likely bring larger conservation benefits than those for improving permeability alone. Buffering and connecting habitat remnants with improved matrix could provide benefits as long as movement survival is increased. Simultaneous implementation of habitat management and matrix improvement would yield synergistic conservation benefits.

opencc-by-4.0Mar 2022View details →

International Journal of Economics and Management Sciences

<table> <tbody> <tr> <td>International Journal of Economics and Management Sciences (IJEMS) is a double blinded reviewed open access journal published bimonthly. Our journal welcomes scientific productions in all areas of economics and management sciences, both theoretical and applied studies will be taken in consideration for evaluation and publication. All research methodologies are welcome. The main objective of our journal is to publish articles that have a significant managerial and theoretical contributions. Our journal receives contributions from both researchers and professionals in the following areas: - Management  - Economics   </td> </tr> </tbody> </table>

opencc-by-4.0Mar 2022View details →

Virtual Storage Plant (VSP) final demonstration of congestion management

This the dataset of final demostration of using distributed control with consensus algorithm for congestion management using a virtual storage plant. The dataset contains raw data from 1 experiment for 1 HLU5-UC4 scenarios: TC_5.04. The experiments were conducted at the University of Zagreb's Smart Grid Laboratory (SGLab).

Quantification of thermal impacts across freshwater life stages to improve temperature management for anadromous salmonids

Water temperature is the major controlling factor that shapes the physiology, behavior, and ultimately, survival of aquatic ectotherms. Here we examine temperature effects on the survival of Chinook salmon (Oncorhynchus tshawytscha), a species of high economic and conservation importance. We implement a framework to assess how incremental changes in temperature impact survival across populations that is based on thermal performance models for three freshwater life stages of Chinook salmon. These temperature-dependent models were combined with local spatial distribution and phenology data to translate spatial-temporal stream temperature data into maps of life stage-specific physiological performance in space and time. Specifically, we converted temperature-dependent performance (i.e., energy used by pre-spawned adults, mortality of incubating embryos, and juvenile growth rate) into a common currency that measures survival in order to compare thermal effects across life stages. Based on temperature data from two abnormally warm and dry years for three managed rivers in the Central Valley, California, temperature-dependent mortality during pre-spawning holding was higher than embryonic mortality or juvenile mortality prior to smolting. However, we found that local phenology and spatial distribution helped to mitigate negative thermal impacts. In a theoretical application, we showed that high temperatures may inhibit successful reintroduction of threatened Central Valley spring-run Chinook salmon to two rivers where they have been extirpated. To increase Chinook salmon population sizes, especially for the threatened and declining spring-run, our results indicate that adults may need more cold-water holding habitat than currently available in order to reduce pre-spawning mortality stemming from high temperatures. To conclude, our framework is an effective way to calculate thermal impacts on multiple salmonid populations and life stages within a river over time, providing local managers the information to minimize negative thermal impacts on salmonid populations, particularly important during years when cold-water resources are scarce.

opencc-by-4.0Apr 2022View details →

Managing for the unexpected: building resilient forest landscapes to cope with global change: Supporting data

Input files and installers of the versions of LANDIS-II, PnET-Succession and other extensions used in the associated paper. They can be used to to reproduce results of the study. The model documentation is freely available at <a href="https://www.landis-ii.org/">https://www.landis-ii.org/</a> The LANDIS-II code is distributed under an open source license at <a href="https://github.com/LANDIS-II-Foundation">https://github.com/LANDIS-II-Foundation</a>. If interested in using this dataset for a research study or project, please contact <a href="https://www.marco-mina.com">Marco Mina</a> --------------------- Mina, M., Messier, C., Duveneck, M., Fortin, M. J., & Aquilué, N. (2022) Managing for the unexpected: building resilient forest landscapes to cope with global change. Global Change Biology 28, 4323– 4341 <a href="https://doi.org/10.1111/gcb.16197">https://doi.org/10.1111/gcb.16197</a> ABSTRACT. Natural disturbances exacerbated by novel climate regimes are increasing worldwide, threatening the ability of forest ecosystems to mitigate global warming through carbon sequestration and to provide other key ecosystem services. One way to cope with unknown disturbance events is to promote the ecological resilience of the forest by increasing both functional trait and structural diversity and by fostering functional connectivity of the landscape to ensure a rapid and efficient self-reorganization of the system. We investigated how expected and unexpected variations in climate and biotic disturbances affect ecological resilience and carbon storage in a forested region in southeastern Canada. Using a process-based forest landscape model (LANDIS-II), we simulated ecosystem responses to climate change and insect outbreaks under different forest policy scenarios – including a novel approach based on functional diversification and network analysis – and tested how the potentially most damaging insect pests interact with changes in forest composition and structure due to changing climate and management. We found that climate warming, lengthening the vegetation season, will increase forest productivity and carbon storage, but unexpected impacts of drought and insect outbreaks will drastically reduce such variables. Generalist, non-native insects feeding on hardwood are the most damaging biotic agents for our region, and their monitoring and early detection should be a priority for forest authorities. Higher forest diversity driven by climate-smart management and fostered by climate change that promotes warm-adapted species, might increase disturbance severity. However, alternative forest policy scenarios led to a higher functional and structural diversity as well as functional connectivity – and thus to higher ecological resilience – than conventional management. Our results demonstrate that adopting a landscape-scale perspective by planning interventions strategically in space and adopting a functional trait approach to diversify forests is promising for enhancing ecological resilience under unexpected global change stressors.

eDNA quantification to evaluate bullfrog management

Biological invasions contribute now more than ever to the global homogenization of fauna and flora. Large-scale monitoring programs are therefore needed to detect incipient invasions and to evaluate management interventions. As conventional monitoring methods are constrained by large costs, environmental DNA (eDNA)-based methods are increasingly recognized as valuable monitoring tools. However, accurately estimating species abundance from eDNA concentrations in natural systems remains challenging and consequently hinders their integration in management applications. Here, we used droplet digital PCR (ddPCR) in eDNA surveys to estimate the abundance of invasive American bullfrogs (Lithobates catesbeianus). We first introduced bullfrog tadpoles in natural ponds to assess the relationship between abundances and eDNA concentrations under field conditions. Next, we combined eDNA sampling with fyke netting in naturally colonized ponds to investigate whether bullfrog eDNA concentrations can estimate bullfrog capture success and conventional abundance measures obtained via depletion sampling. Finally, we evaluated eradication measures by comparing bullfrog eDNA concentrations before and after fyke netting. We found a strong linear relationship between the numbers of introduced tadpoles and eDNA concentrations (r2 = 0.988). Bullfrog eDNA concentrations were not only linearly related to the catch-per-unit-effort (r2 = 0.739), but also to conventional abundance estimates (r2 = 0.716), particularly when eDNA concentrations were standardized for pond area (r2 = 0.834) and volume (r2 = 0.888). Bullfrog tadpoles were only captured when eDNA concentrations exceeded 1.5 copies µL-1, indicating that quantitative eDNA analyses enable the localization of breeding ponds. We found a significant reduction in eDNA concentrations after fyke netting proportional to the number of captured bullfrogs. These results demonstrate that eDNA quantification is a reliable tool that accurately estimates bullfrog abundance in natural lentic systems. We show that quantitative eDNA analyses can complement the toolbox of natural resource managers and facilitate the coordination of eradication campaigns targeting alien invasive species.

Data for: Size spectrum model reveals importance of considering species interactions in a freshwater fisheries management context

Inland fisheries have significant cultural and economic value around the globe, providing dietary protein, income, and recreation. Consequently, methods for monitoring and managing these important fisheries are continually being refined. In marine systems, multi-species size spectrum models have been increasingly used to explore management scenarios of important fish stocks within an ecosystem-based fisheries management framework; however, these models have not been applied in freshwater systems. In this study, we developed a multi-species size spectrum model for the fish community of Lake Nipissing, a large, productive lake in Ontario, Canada. To the best of our knowledge, this is the first fully calibrated multi-species size spectrum model for an inland fishery. Using this model, we explored the impacts of different management scenarios on fish community dynamics while taking species interactions into account. Specifically, we examined how changes in fishing mortality affect: (1) species biomass; (2) community size structure; and (3) stock recovery times. We found that community dynamics following changes in fishing mortality were driven by complex interactions among species, including competition and predation. The greatest changes in biomass and community size structure were observed following changes in fishing mortality to top predators, with community size structure most strongly influenced by changes in mortality to the largest species in the community. Counter to predictions based on generation time, the smallest species in our model exhibited the longest time to recovery due to strong competition and predation. Our results demonstrate the importance of taking an ecosystem-based approach and considering species interactions in the management of inland fisheries and highlight the potential of size spectrum model use in freshwater systems.

opencc-by-4.0Jul 2021View details →

Resource Guide for State DOT's Maintenance Equipment Fleet Management Decisions

This research created a guide for state Departments of Transportation fleet management on utilizing equipment fleet management system data to make informed fleet management decisions. The research team took the historical equipment fleet data from the Oklahoma Department of Transportation and developed workflows, algorithms, and examples to demonstrate the use of historical equipment data for equipment decisions. Specifically, the research team demonstrated 1) the use of life cycle analysis and dynamic programming models for equipment replacement decisions; 2) developed algorithms to calculate equipment rental rates that can be used by the Department to forecast and allocate equipment operational budget among field districts and central office, 3) developed a procedure to make own-rent/lease decisions based on historical equipment management data. Using the two class codes of equipment (Class Code 5355 – 2 Yd. front-end loaders and Class Code 5385 – 1/2-ton fleetside pickup trucks) as examples, the research team presented the result of the equipment replacement models using both life cycle analysis and dynamic programming approaches and discussed the difference of those two methods. In addition, the impact of model input parameters (specifically depreciation cost estimation using both straight line and double declining balance depreciation calculation methods) on equipment replacement outcomes is discussed. The framework for deciding between on renting or owning for the two class codes of equipment was developed. Also, the equipment rental rates for the most frequently used equipment by ODOT were updated per class code.

opencc-by-4.0Nov 2021View details →

Smart Battery Management System for Electric Vehicles: Selflearning Algorithms for Simultaneous State and Parameter Estimation, and Stress Detection

The project proposes to develop parameter-varying SOH-coupled models for lithium-ion battery and self-learning algorithms to learn the model for simultaneous state and parameter estimation and fault detection. The traditional battery models use constant parameters, limiting their accuracy for predicting the state of the charge and health over the complete life-cycle. In practice, the battery parameters vary with the change in the state of charge and state of health. SOH-coupled models can be used to estimate the state of charge and health accurately. Further, obtaining the model parameters is also a challenging task for designing filters or observers for state estimation. A self-learning algorithm can eliminate the requirement of the model parameters. In this project, three SOH-coupled models are proposed and validated experimentally. The models are also used to design extended Kalman filters (EKF) for the state of charge, state of health, core and surface temperature, and internal resistance estimation. The results showed that the SOHcoupled models are more effective when compared to the uncoupled models in the literature. Further, it was found that EKFs based state estimation errors were within 1%. The self-learning algorithm using a two-layer neural network showed the ability to learn the models in real-time. However, the state estimation errors are higher for the self-learning scheme compared to the EKF based approaches. This is due to the limited measurement and online training schemes utilized to train neural networks. This requires further investigation in hyper-parameter tuning for implementation. Finally, a model-based fault detection scheme was proposed to detect internal thermal fault at its onset. The SOHcoupled model is reformulated to incorporate the internal resistance as a state. The EKF is used as a fault detection observer. The proposed fault detection scheme is validated using numerical simulation. It was observed that the fault detection scheme with SOH coupled electro-thermal-aging model could effectively detect a thermal fault at its incipient state.

opencc-by-4.0Feb 2022View details →

Integrating REBT and ACT : An intervention study for managing academic self-handicapping behaviour among young adults

The data consists of pre and post interventions scores of 25 participants who were selected based on their ratings on Academic self -handicapping scale (Geetika & Gupta, 2020) . Thirteen participants were randomly assigned to the experimental group which was exposed to 8 hours of intervention that combined REBT and ACT. Twelve participants were randomly assigned to the control group and did not receive any intervention. The pre-intervention scores on Academic self -handicapping scale (Geetika & Gupta, 2020) were assessed at the beginning of the intervention and at two weeks since the beginning of the intervention. Sub scale scores on Behavioural and Claimed self -handicapping were recorded and overall score by adding the two were also obtained.

Future-proofing the koala: synergizing genomic and environmental data for effective species management

Climatic and evolutionary processes are inextricably linked to conservation. Avoiding extinction in rapidly changing environments often depends upon a species' capacity to adapt in the face of extreme selective pressures. Here, we employed exon capture and high-throughput next-generation sequencing to investigate the mechanisms underlying population structure and adaptive genetic variation in the koala (Phascolarctos cinereus), an iconic Australian marsupial that represents a unique conservation challenge because it is not uniformly threatened across its range. An examination of 250 specimens representing 91 wild source locations revealed that five major genetic clusters currently exist on a continental scale. The initial divergence of these clusters appears to have been concordant with the Mid-Brunhes Transition (∼ 430–300 kya), a major climatic reorganization that increased the amplitude of Pleistocene glacial-interglacial cycles. While signatures of polygenic selection and environmental adaptation were detected, strong evidence for repeated, climate-associated range contractions and demographic bottleneck events suggests that geographically isolated refugia may have played a more significant role in the survival of the koala through the Pleistocene glaciation than in situ adaptation. Consequently, the conservation of genome-wide genetic variation must be aligned with the protection of core koala habitat to increase the resilience of threatened populations to accelerating anthropogenic threats. Finally, we propose that the five major genetic clusters identified in this study should be accounted for in future koala conservation efforts (e.g. guiding translocations), as existing management divisions in the states of Queensland and New South Wales do not reflect historic or contemporary population structure.

Case study data of the paper: A methodological guide to observe local-scale geodiversity for biodiversity research and management

Current global environmental change calls for comprehensive and complementing approaches for biodiversity conservation. According to recent research, consideration of the diversity of Earth's abiotic features (i.e., geodiversity) could provide new insights and applications into the investigation and management of biodiversity. However, methods to map and quantify geodiversity at local scale have not been developed although this scale is important for conservation planning. Here, we introduce a field methodology for observing plot-scale geodiversity, pilot the method in an Arctic-alpine tundra environment, provide empirical evidence on the plot-scale biodiversity-geodiversity relationship and give guidance for practitioners on the implementation of the method. The field method is based on observation of geofeatures, i.e., elements of geology, geomorphology, and hydrology, from a given area surrounding a location of species observations. As a result, the method provides novel information on the variation of abiotic nature for biodiversity research and management. The method was piloted in northern Norway and Finland by observing geofeatures from 76 sites at three scales (5, 10 and 25 m radii). To explore the relationship between measures of biodiversity and geodiversity, the occurrence of vascular plant species was recorded from 2 m x 2 m plots at the same sites. According to the results, vascular plant species richness was positively correlated with the richness of geofeatures (Rs = 0.18–0.59). The connection was strongest in habitats characterized by deciduous shrubs. The method has a high potential for observing geofeatures without extensive geological or geomorphological training or field survey experience and could be applied by conservation practitioners. Consideration of geodiversity in understanding, analysing and conserving biodiversity could facilitate environmental management and ensure the long-term sustainability of ecosystem functions. With the developed method, it is possible to cost-efficiently observe the elements of geodiversity that are useful in ecology and biodiversity conservation. Our approach can be adapted in different ecosystems and biodiversity investigations. The method can be adjusted depending on the abiotic conditions, expertise of the observer(s), and the equipment available.

opencc-by-4.0Mar 2022View details →

IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review

Data collected from primary studies. We 1) identified the main approaches and services that are applied in the city and SGB-level SWM systems, 2) listed sensors and actuators and analyzed their application in various types of SWM systems, 3) listed the direct and indirect stakeholders of the SWM systems, 4) identified the types of data shared between the SWM systems and stakeholders, and 5) identified the main promising directions and research gaps in the field of SWM systems.

opencc-zeroMay 2022View details →

Reducing risky interactions: Identifying barriers to the successful management of human-wildlife conflict in an urban parkland

Managing activities that result in human-wildlife conflict is a challenging goal for modern scientists and managers. In recent years, the self-motivated feeding of wildlife by humans has garnered popularity but with consequent risks for the health and safety of both parties. This has resulted in calls for management in areas of high contact, e.g., parklands. Traditional controls are typically utilised (i.e., signage, patrols), yet their success is varied, leading to a rise in research aiming to improve them. This research has primarily focused on language and design, with little attention paid to the role that audience type (i.e., international tourists versus locals/residents) may play in their success. Proportions in audience type present can vary both between parks and spatially within a single park, however, controls are usually applied homogeneously with no consideration for how response may vary between these groups. Here, we performed a robust before-after study across two summers using a wild fallow deer population in a public park that are commonly fed by visitors as our model. We deployed controls, following best practices as outlined by the literature, and tested their overall effectiveness. We then identified key areas with differences in visitor type proportions and tested for variation in success between them. We found that the number of visitors feeding the deer significantly decreased overall after the introduction of controls, although interactions were not eliminated entirely. We discovered that the effectiveness of these controls varied with changes in visitor type, with the most positive effects occurring in areas with more international tourists and no significant effect occurring in areas dominated by resident visitors. Notably, of the food offerings remaining, the proportion of foods that could be perceived as 'nutritionally beneficial' increased in both sites, marking overall changes in the behaviours of even those visitors who refused to stop feeding. These findings highlight the importance of target audience research in human-wildlife conflict management. We recommend that authorities aiming to reduce these interactions perform systematic surveys to identify the audience type present and cater controls accordingly to maximise their success.

opencc-zeroMay 2022View details →

Evaluating how management policies affect red wolf mortality and disappearance (1987-2020)

We analyzed data acquired from the USFWS Red Wolf Recovery Program (hereafter 'Recovery Program') on radio-marked (hereafter collared), monitored red wolves (i.e., within the NC recovery area). The Recovery Program data include the monitoring history for all collared and monitored adult red wolves released to the wild since the beginning of releases in 1987 to March 1, 2020; n=526. The Recovery Program survival dataset contains the following individual covariates employed in our analyses: endpoint (i.e., final wolf fate by cause of death or disappearance [lost-to-follow-up, LTF]), capture date (beginning of monitoring), and date of endpoint (end of monitoring). The dataset also provided data on sex and other individual covariates not used for our study and hence not described. For recovered wolf carcasses, cause of death was estimated by USFWS using standard methods following necropsy and radiography. Agency removal occurred when a red wolf was captured and removed permanently (lethally or not) from the NC population, generally because the wolf was considered a problem animal by USFWS but also some wolves were removed to supplement other wild populations (n=5). The LTF endpoint occurred when a wolf in the wild disappeared from monitoring because the affixed radio-collar stopped functioning due to either mechanical/battery failure or tampering/destruction by external causes including humans. We reclassified the marked animals' fates obtained from the Recovery Program survival data into the following mutually-exclusive endpoints, following previous studies: agency removals (lethal or not, by agency personnel; n=40, 7.6%), collision (trauma by vehicle(s); n=68, 12.9%), reported poached (n=150, 28.5%), nonhuman (unrelated to humans; e.g., disease, intraspecific strife, n=66, 12.5%), and unknown (unable to discern cause of death in necropsy; n=82, 15.6%). We include LTF (disappeared individuals; n=117, 22.2%) as one of multiple mutually-exclusive endpoints. We estimated the time between collaring (capture date) and endpoint in days (t) for each red wolf (n=526) in our dataset. We calculated time collared (t) differently for surviving, dead, removed to captivity and LTF endpoints, following previous studies. For our mortality endpoints, we estimated t for wolves monitored by telemetry until death. For wolves relocated to captivity, we used the date of final removal to captivity by agency action. For LTF wolves, we used the last date of telemetry contact. We censored any wolves who were alive at the end of our study period (March 1, 2020, n=3 wolves). In our study, we exploit the complementarity of both models: our joint stratified Cox model allowed us to test the hypothesis that our management covariates affected the rate of occurrence (i.e., hazard) of specific endpoints, and endpoint-specific FG models allowed us to test if and how much these same covariates affected the probability and incidence of said endpoints.