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opencc-by-4.0Mar 2024View details →

Applying innovative cloud computing technology for the effective management of Groundwater resources to promote SUStainable food security within the Sokoto Basin, Nigeria (AGSUS)

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opencc-zeroOct 2023View details →

Evaluation of the administrative management model in a municipality in Peru, incorporating the Intelligent Organization Theory

Background: This study begins with the analysis of the current management models and their degree of effectiveness in municipal administration. Its aim is to design an administrative management model that enables effective administration in the District Municipality of Nueva Cajamarca, Peru, based on the theory of intelligent organizations.Method: The research type employed in this study is diagnostic-propositional, utilizing both deductive and inductive methods, in alignment with a mixed-method approach and a non-experimental nature of the study. Data was collected from three distinct populations, including the 189 municipal employees engaged in administrative roles, who were subjected to a 50-question survey. This survey aimed to assess their perceptions regarding the current management model and its relationship with administrative effectiveness. Additionally, interviews were conducted with three experts to gain deeper insights into the behavior of the variables under investigation.Results: Finally, documentary information about the management models currently in use was collected. This facilitated the triangulation of data collection, processing, analysis, and inferences from three sources of information. The results reveal a positive, direct, and significant correlation between the management model and administrative effectiveness. It becomes evident that the current management model is deficient, resulting in a low level of administrative effectivenessConclusion: The management model based on the theory of intelligent organizations was validated using a rubric by experts in effective management. The main pillars of this model include transformational leadership, structural change, and cultural change.

opencc-by-4.0Dec 2020View details →

Kuhlia rupestris, juvenile. © E. Vigneux. Source: Keith et al., 1999. in Biology of jungle perch, Kuhlia rupestris, identification of threats and knowledge gaps to improve local and global management

Kuhlia rupestris, juvenile. © E. Vigneux. Source: Keith et al., 1999.

opencc-by-4.0Mar 2024View details →

Dataset for: Advancing projections of Crown-of-Thorns Starfish to support management interventions

<h3>Abstract</h3> <div> Regular outbreaks of corallivorous Crown of Thorns Starfish (Acanthaster spp; CoTS) occur on the Great Barrier Reef (GBR) and are one of the leading drivers of coral mortality. Understanding the disparities between real-world observations and model predictions of CoTS densities is crucial for refining population modelling and developing effective control strategies. Using a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR), we compare model predictions of CoTS densities to manta tow survey observations. We also incorporate a new zone-specific CoTS mortality rate to account for differences in predation of CoTS between fished and protected reefs. We found high congruence between predicted CoTS densities and observations: ~81% of categorical reef level CoTS densities were either the same density level or only differed by one level, however underpredictions increased as observed densities increased. The zone-specific CoTS mortality rate reduced severe underpredictions from 7.1% to 5.6%. Underpredictions are a key concern for reef managers as they indicate potential missing outbreaks where targeted culling efforts are necessary and may lead to an underestimation of the coral loss attributed to CoTS outbreaks. Reef protection status was an important driver of prediction accuracy, suggesting it plays a role in determining CoTS densities, emphasising the importance of further research on in situ CoTS mortality rates. The location of a reef inside or outside the “initiation box”, a speculative area of primary outbreaks on the GBR, was also important, with exact predictions more likely to occur outside the box. Accurately modelling initiation box dynamics is challenging owing to limitations of empirical data on CoTS outbreaks, but this highlights the need for focussed research on these dynamics to enhance overall predictive accuracy. Other spatial factors, such as region and shelf position, also contributed to the variance between observations and predictions, underscoring the importance of the spatial-temporal context of each observation. In conclusion, this study validates our CoTS population modelling efforts, showcasing a high congruence between CoTS density predictions and real-world observations. CoTS observations can help refine predictions and guide targeted control against CoTS populations and outbreaks, contributing to effective ecosystem management for long-term resilience of the GBR. </div> <h3>Methods</h3> <div> Data are mean CoTS density (per manta tow) observations and predictions for individual reefs and years on the Great Barrer Reef. Observations come from several sources (CCP, LTMP, FMP) and predictions come from a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR).  </div> <h3>Subject keywords</h3> Earth and related environmental sciences, adaptive management, coral reef, Great Barrier Reef, individual-based model, Marine Invertebrate, pest management, spatial simulations <h3>Funding</h3> <div> CoTS Control Innovation Program </div> <div> <h2>README: Dataset for: Advancing projections of Crown-of-Thorns Starfish to support management interventions</h2> <a href="https://doi.org/10.5061/dryad.31zcrjdtq">https://doi.org/10.5061/dryad.31zcrjdtq</a> This dataset is for a paper that compares CoTS density observations to predictions for individual reefs on the Great Barrier Reef in individual years. CoTS manta tow observations derive from the CoTS Control Program (CP), Field Management Program (FMP), and the AIMS Long Term Monitoring Program (LTMP). Where multiple observations exist from the same observation source, they are averaged at the reef-level in that year. If multiple observations exist from different sources, they are kept separate. Predictions are generated by a spatially explicit ecosystem model of the Great Barrier Reef (ReefMod-GBR). <h3>Description of the data and file structure</h3> Observed and predicted CoTS densities are compared to determine prediction accuracy of the ecosystem model. Both observed and predicted CoTS per tow values were categorised as follows: 0 = None (Level 1); ≤ 0.1 = No Outbreak (Level 2); 0.11 - 0.22 = Potential Outbreak (Level 3); 0.22 - 1.0 = Established Outbreak (Level 4); 1.0 - 3.0 = Severe Outbreak (Level 5); > 3.0 = Extreme Outbreak (Level 6). The level of each observation was then compared to the level of each prediction and the difference calculated to determine prediction accuracy. Different variables were extracted as potential predictors of CoTS prediction accuracy. As such, the dataset includes the following for each observation/prediction comparison: 1) RM_ID = an individual ID for each of the 3806 reefs that we model in our ecosystem model. 2) YEAR = year as an integer. 3) LAT and LON = the latitude and longitude of the reef. 4) GBRMPAID and GBR_NAME = identifiers for each reef from the Great Barrier Reef Marine Park Authority. 5) REGION: 1 = North, 2 = Central, 3 = South 6) SHELF: 1 = Inner, 2 = Middle, 3 = Outer 7) GZ = Whether a reef is protected (i.e., in a green zone = 1) or not (i.e., in a blue zone = 0). 8) IB = Whether a reef is inside the CoTS initiation box (1) or not (0). 9) GEOM_CH_KM2 = the area (km2) of coral habitat for that reef 10) OBS_SOURCE = the source of the CoTS observation (1 = LTMP, 2 = FMP, 3 = CP) 11) OBS_n = the number of observations that went into calculating the reef-level mean CoTS per tow for that year 12) OBS_COTS_CAT = observed CoTS density as a categorical level from GBRMPA 13) OBS_COTS = mean CoTS per tow, and OBS_COTS_1YB = mean COTS per tow at that reef in the preceding year 14) OBS_CC, OBS_CC_1YB = mean coral cover at that reef from that OBS_SOURCE, and OBS_CC_1YB = in the year preceding it. 15) PRED_COTS_CAT = predicted CoTS density as a categorical level from GBRMPA 16) PRED_COTS, PRED_COTS_1YB, PRED_COTS_2YB, PRED_COTS_3YB = predicted CoTS per tow densities at the current year, and in the one, two, and three years preceding it. 17) PRED_CC, PRED_CC_1YB, PRED_CC_2YB, PRED_CC_3YB = predicted coral cover (%) at the current year, and in the one, two, and three years preceding it. 18) PRED_ACRO, PRED_ACRO_1YB, PRED_ACRO_2YB, PRED_ACRO_3YB = predicted Acropora cover (%) at the current year, and in the one, two, and three years preceding it. Acropora is the preferred food of CoTS. 19) PRED_INSTR, PRED_INSTR_CUMU = incoming strength of CoTS larvae calculated as the CoTS larval input multipled by the size of the reef area. PRED_INSTR_CUMU is the sum of this value over the three years previous to the current year. 20) TOTAL_OBS = where data exist, the CoTS model ReefMod is forced with manta tow survey observations from the CP, FMP, and LTMP which override model predictions at individual reefs/years. This shows the total number of observations that have been used to force the CoTS predictions for this reef in all preceding years. 21) TIME_SINCE_OBS = similar to TOTAL_OBS, but gives the number of years since an observation last forced the CoTS prediction for this reef. 22) PRED_ERR_COTS = the difference in categorical CoTS density levels between observations and predictions. 23) PRED_ERR_CC = observed and predicted coral cover was categorised into AIMS coral cover categories: 0 = 0%, 1 = 0 - 10%, 2 = 10 - 30%, 3 = 30 - 50%, 4 = 50 - 75%, 5 = 75 - 100%. The difference in coral cover category between observations and predictions was then compared. 24) DIFF_CC = the difference in the % coral cover between the observations and predictions. 25) DIFF_CC_CUMU, DIFF_CC_CUMU_N = same as DIFF_CC except the cumulative % difference over the three preceding years, and the number of observations that went into calculating the %. </div>

Figure 6 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 6: Percentage of maturity level of female swimming crabs

Figure 5 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 5. Percentage of spawning females Phase

Figure 4 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 4: Sex ratio distribution of swimming crab

Figure 1 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 1: Maturity level composition of swimming crab based on carapace width

Figure 3 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 3: Average weight of swimming crab

opencc-by-4.0Apr 2024View details →

Database to: Effectiveness of soil management strategies for mitigation of N2O emissions in European arable land: A meta-analysis

Database to a meta-analysis studing the effects of adding different organic matter inputs (crop residues, green manure, livestock manure, slurry, digestate, compost or biochar) to soils on N2O emissions. Database consists of over 50 field experiments conducted in 15 European countries. Diverse arable crops, mainly cereals, were cultivated in monoculture or in crop rotations on mineral soils.  Cumulative N2O emissions per unit land area were monitored during periods of 30 to 1,070 days in treatments, which received organic matter inputs, alone or in combination with mineral N fertiliser; and in controls fertilised with mineral N. The original results appeared in 46 articles published between 1993 and 2022 in peer-reviewed scientific journals, as well as a project report, and a PhD thesis.

Figure 2 in Analysis of Carapas Width and Weight on Maturity Level of Swimming Crab (Portunus pelagicus) as Basis for Sustainable Resource Management in the Eastern Waters of Surabaya

Figure 2: Average Carapace Width of Swimming Crab

Population genomics of flat-tailed horned lizards (Phrynosoma mcallii) informs conservation and management across a fragmented Colorado Desert landscape

Phrynosoma mcallii (flat-tailed horned lizards) is a species of conservation concern in the Colorado Desert of the United States and Mexico. We analyzed ddRADseq data from 45 lizards to estimate population structure, infer phylogeny, identify migration barriers, map genetic diversity hotspots, and model demography. We identified the Colorado River as the main geographic feature contributing to population structure, with the populations west of this barrier further subdivided by the Salton Sea. Phylogenetic analysis confirms that northwestern populations are nested within southeastern populations. The best-fit demographic model indicates Pleistocene divergence across the Colorado River, with significant bidirectional gene flow, and a severe Holocene population bottleneck. These patterns suggest that management strategies should focus on maintaining genetic diversity on both sides of the Colorado River and Salton Sea. We recommend additional lands in the U.S. and Mexico that should be considered for similar conservation goals as those in the Rangewide Management Strategy (RMS). We also recommend periodic rangewide genomic sampling to monitor ongoing attrition of diversity, hybridization, and changing structure due to habitat fragmentation, climate change and other long-term impacts.

The potential of using different legume species in a push-pull approach to manage Spodoptera frugiperda in maize in China

Fall armyworm (Spodoptera frugiperda) is a notorious pest on crops, especially on maize. The push-pull strategy based on the intercropping system has been reported to effectively reduce the damage of S. frugiperda. However, the suitable mode for S. frugiperda management in maize-based intercropping systems in China has not been reported thoroughly. In this study, the adaptability, feeding, and oviposition preferences of S. frugiperda on maize (Zea mays L.), mung bean (Vigna radiata L.), soybean (Glycine max L.), kidney bean (Phaseolus vulgaris L.), red bean (Vigna angularis Willd.) and cowpea (Vigna unguiculata L. Walp), were firstly compared through lift table analysis and indoor cage tests. Subsequently, based on the results from the laboratory tests, mung bean –cowpea was selected as the push-pull system for S. frugiperda occurrence studied in the field. Results showed that maize is the most suitable host for S. frugiperda, as indicated by the shortest developmental duration and the highest pupal weight. However, among all the tested bean plants, the cowpea is the best for S. frugiperda, on which the larval duration, pre-adults, and adult durations were significantly shorter than others. Meanwhile, the feeding and oviposition preference tests revealed that S. frugiperda had a strong preference for maize and cowpea, while the opposite was true for mung bean. Compared to maize monoculture, the number of eggs of S. frugiperda laid in maize-mung decreased by 67.25%, and that in maize-cowpea significantly increased to 2.04 times. In a randomized block experiment in the field, it was found the incidence of maize in the mung bean-cowpea system was significantly lower than that of maize monocropping and maize only surrounded by cowpea. This study indicated that mung bean and cowpea are promising candidates as a repellent plant (push) and attractant plants (pull) to be intercropped with maize using the push-pull strategy to lessen the damage caused by S. frugiperda in maize-based intercropping systems.

opencc-by-4.0Dec 2023View details →

Aligning Data Management Plans with Community Standards using FAIR Implementation Profiles

Here you can find the files corresponding to our submission titled 'Aligning DMPs with Community Standards using FIPs'. - VU DMP template and the mapping is included in the folder /VU-DMP-template-and-mapping - All the FAIR Implementation Profiles are included in the folder /FIPs. - The knowledge model we created for the project, and a small demo of the interface are in the folder /KM-and-demo. - The folder /user-study consists of the following:   a) The mock DMPs we provided to the participants of this research are in /mock_DMPs.   b) We downloaded the resulting DMPs after participants completed their DMPs, they are in the folder /resulting_DMPs.   c) Survey results can be found in the folder /survey_results.   d) Some Python scripts were used for the analysis of the survey results. They are in the folder /Python_script_for_analysis. The project is open source under the license CC-BY 4.0. Contact: Shuai Wang (shuai.wang@vu.nl)

Data from: forest stand dynamics of a short-stature tree species: ecological knowledge for sustainable forest management

This data set is a forest inventory of Nothofagus antarctica in southern Chile. More than 20 sites were selected. In each site, parallel transects were set and every 30 m a sampling point was set where the distance to the nearest four trees (in accordance with the cardinal points) were measured.

opencc-by-4.0Oct 2023View details →

Cultivating Leadership and Team Management Skills for Business Success

In today's dynamic and competitive business landscape, effective leadership and proficient team management are fundamental pillars driving organizational success (Rahman, R. (2023). Leadership encompasses not only setting the vision and goals of an organization but also inspiring and empowering employees to achieve them (Rahman, R. (2023). Similarly, adept team management is crucial for harnessing the collective potential of individuals toward common objectives (Rahman, R. (2023). This introduction sets the stage for exploring the significance of honing leadership and team management capabilities in driving business success, drawing insights from scholarly literature on the subject.   In the face of rapid technological advancements, evolving consumer preferences, and global market dynamics, businesses must navigate increasingly complex challenges. Effective leadership serves as the guiding force that steers organizations through uncertainty and change, while adept team management ensures that resources are optimally utilized and diverse talents are leveraged for maximum impact (Rahman, R. (2023). Moreover, in an era where employee engagement and retention are critical for sustained growth, leadership that fosters a culture of trust, collaboration, and innovation is indispensable ( Donaldson, G. (2006).).

opencc-by-4.0Apr 2024View details →

Conservation opportunities through improved management of recently established protected areas in Southeast Asia

<ul> <li>The 'Table_PA_info' contains information on all 80 Protected Areas analyzed in this study.</li> <li>The 'Synth_plots' includes synthetic control model fits for all 80 Protected Areas analyzed in this study. The number displayed on the top-left of each plot corresponds to the WDPA-ID of the respective protected area. For further details on each protected area, please refer to the 'Table_PA_info' document.</li> <li>The 'placebos' document consists of placebo test plots. The number on the top-left of each plot indicates the WDPA-ID of the protected area. Refer to the 'Table_PA_info' document for more information on each protected area.</li> </ul>

Data from: Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape - patterns of genetic diversity, population structure and gene flow

Red deer (Cervus elaphus) throughout central Europe are impacted by different anthropogenic activities including habitat fragmentation, selective hunting, and translocations. This has substantial influences on genetic diversity and the long-term conservation of local populations of this species. Here we use genetic samples from 480 red deer individuals to assess the genetic diversity and differentiation of the 12 administrative management units located in Schleswig Holstein, the northernmost federal state in Germany. We applied multiple analytical approaches and show that the history of local populations (i.e., translocations, culling of individuals outside of designated red deer zones, and anthropogenic infrastructures) has led to comparably low levels of genetic diversity. The mean expected heterozygosity was below 0.6 and we observed on average 4.2 alleles across 12 microsatellite loci. Effective population sizes below the recommended level of 50 were estimated for multiple local populations. Our estimates of genetic structure and gene flow show that red deer in northern Germany are best described as a complex network of asymmetrically connected subpopulations, with high genetic exchange among some local populations and reduced connectivity of others. Genetic diversity was also correlated with population densities of neighboring management units. Based on these findings, we suggest that connectivity among existing management units needs to be considered in the practical management of the species, which means that some administrative management units should be managed together, while the effective isolation of other units needs to be mitigated.

opencc-by-4.0Apr 2024View details →

Evaluation of comparative efficacy of Trayodashang Guggul versus Asitaka Churna Vati in the management of Katigraha (Stiffness in Lumbar Region): A randomized controlled trial protocol

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The decline of ground-nesting birds in Europe: do we need to manage predation in addition to habitat?

Bird populations are declining globally with losses recorded in many European breeding birds. Habitat management measures have not resulted in a widespread reversal of these declines. We analysed national bird population trends from ten European countries (France, Hungary, Ireland, the Netherlands, Poland, Portugal, Spain, Sweden, Switzerland, and the UK) in relation to the species' nesting strategy ('ground-nesting' or 'other'), Annex I designation ('designated' or 'not designated') and association with agricultural habitats for breeding ('associated' or 'not associated'). For each country in our dataset, we also defined the following factors: farming intensity; predator community complexity; and predator control effort. Our results showed additive effects of nesting strategy, designation, and breeding habitats on the likelihood of population decline. Ground-nesting birds were 86% more likely to decline than birds with other nesting strategies. Annex I designated species of the Birds Directive were 50% less likely to decline than non-designated birds. Birds breeding primarily in agricultural habitats were more likely to decline than birds breeding in other habitats, interactively with farming intensity. Homogenous trends across Europe (i.e., trends in two or more countries that were either not declining in all countries or declining in all countries) indicate that the probability of population decline was related to nesting strategy and breeding habitat, with ground-nesting birds being 15.6 times more likely than other birds to have a declining trend across Europe, and birds nesting in agricultural habitat being 17.8 times more likely than birds nesting in other habitats to have a declining trend across Europe. Our results highlight a widespread challenge, therefore widespread instruments (e.g. legislation, economic policies, agri-environment schemes) will be required to reserve these declines. Ground-nesting species requirements can be complex and multiple strategies will be needed to restore populations including the development of predation management tools.