scholarly journals Predicting species and community responses to global change in Australian mountain ecosystems using structured expert judgement

2020 ◽  
Author(s):  
James S. Camac ◽  
Kate D.L. Umbers ◽  
John W. Morgan ◽  
Sonya R. Geange ◽  
Anca Hanea ◽  
...  
Keyword(s):  
Global Change ◽  
Empirical Data ◽  
Large Scale ◽  
Expert Knowledge ◽  
Rapid Change ◽  
Life Cycles ◽  
Expert Elicitation ◽  
Alpine Plants ◽  
Ecological Data ◽  
Australian Alps

AbstractConservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which has already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we used a structured expert elicitation method (the IDEA protocol) to estimate the abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands were predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species were predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles were expected to decline in abundance than other species. In the face of rapid change and a paucity of data, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management, although this approach does not diminish the importance of collecting long-term ecological data.Article Impact StatementExpert knowledge is used to quantify the adaptive capacity and thus, the risk posed by global change, to Australian mountain flora and fauna.

scholarly journals Expert elicitation as a method for exploring illegal harvest and trade of wild meat over large spatial scales

Oryx ◽  
2016 ◽  
Vol 51 (2) ◽  
pp. 298-304 ◽  
Author(s):  
Natalie Swan ◽  
Jos Barlow ◽  
Luke Parry
Keyword(s):  
Large Scale ◽  
Expert Knowledge ◽  
Spatial Scales ◽  
Cost Effective ◽  
Expert Elicitation ◽  
Field Validation ◽  
Cost Effective Technique ◽  
Wild Meat ◽  
Urban Consumption ◽  
New Evidence

AbstractNew evidence of commercialization and consumption of wild meat in Amazonian cities has exposed an alarming yet poorly understood threat to Neotropical biodiversity. In response to the limitations of field sampling for large-scale surveys, we sought to develop a method of rapidly assessing wildlife harvest and trade in multiple areas using expert knowledge. Using caiman as a model taxon, we surveyed experts across the Brazilian Amazon. Expert responses to a Likert-style questionnaire suggest that caiman hunting, generally considered a localized rural activity, is in fact common and geographically widespread. Contrary to previous assumptions we found evidence that urban demand is partly driving the harvest, including via interstate trafficking. We highlight the need for further field validation of wild-meat trade and urban consumption patterns in Amazonia. We conclude that expert elicitation is a simple, cost-effective technique that can be a valuable precursor to inform and direct applied conservation research, especially where there are significant knowledge gaps and at large spatial scales.

Multiple-source Record Linkage in a Rural Industrial Community, 1680–1820

1994 ◽  
Vol 6 (3) ◽  
pp. 133-142 ◽  
Author(s):  
Steve King
Keyword(s):  
Early Modern ◽  
Large Scale ◽  
Social Economic ◽  
Life Cycles ◽  
Multiple Source ◽  
Demographic Analysis ◽  
Ordinary People ◽  
Industrial Community ◽  
The Social ◽  
Broad Outline

Re-creating the social, economic and demographic life-cycles of ordinary people is one way in which historians might engage with the complex continuities and changes which underlay the development of early modern communities. Little, however, has been written on the ways in which historians might deploy computers, rather than card indexes, to the task of identifying such life cycles from the jumble of the sources generated by local and national administration. This article suggests that multiple-source linkage is central to historical and demographic analysis, and reviews, in broad outline, some of the procedures adopted in a study which aims at large scale life cycle reconstruction.

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

scholarly journals Response (minimum clinically relevant change) in ASD symptoms after an intervention according to CARS-2: consensus from an expert elicitation procedure

2021 ◽  
Author(s):  
Lucie Jurek ◽  
Matias Balthazar ◽  
Sheffali Gulati ◽  
Neda Novakovic ◽  
María Núñez ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Rating Scale ◽  
Expert Knowledge ◽  
Scientific Evidence ◽  
Autism Spectrum ◽  
Expert Elicitation ◽  
Spectrum Disorder ◽  
Initial Finding ◽  
Elicitation Process ◽  
Core Symptoms

AbstractThe lack of consensual measures to monitor core change in Autism Spectrum Disorder (ASD) or response to interventions leads to difficulty to prove intervention efficacy on ASD core symptoms. There are no universally accepted outcome measures developed for measuring changes in core symptoms. However, the CARS (Childhood Autism Rating Scale) is one of the outcomes recommended in the EMA Guideline on the clinical development of medicinal products for the treatment of ASD. Unfortunately, there is currently no consensus on the response definition for CARS among individuals with ASD. The aim of this elicitation process was to determine an appropriate definition of a response on the CARS2 scale for interventions in patients with Autism Spectrum Disorder (ASD). An elicitation process was conducted following the Sheffield Elicitation Framework (SHELF). Five experts in the field of ASD and two experts in expert knowledge elicitation participated in an 1-day elicitation workshop. Experts in ASD were previously trained in the SHELF elicitation process and received a dossier of scientific evidence concerning the topic. The response definition was set as the mean clinically relevant improvement averaged over all patients, levels of functioning, age groups ***and clinicians. Based on the scientific evidence and expert judgment, a normal probability distribution was agreed to represent the state of knowledge of this response with expected value 4.03 and standard deviation 0.664. Considering the remaining uncertainty of the estimation and the available literature, a CARS-2 improvement of 4.5 points has been defined as a threshold to conclude to a response after an intervention. A CARS-2 improvement of 4.5 points could be used to evaluate interventions' meaningfulness in indivudals. This initial finding represents an important new benchmark and may aid decision makers in evaluating the efficacy of interventions in ASD.

A High-Fidelity Model to Predict Length of Stay in the Neonatal Intensive Care Unit

2021 ◽  
Author(s):  
Kanix Wang ◽  
Walid Hussain ◽  
John R. Birge ◽  
Michael D. Schreiber ◽  
Daniel Adelman
Keyword(s):  
Length Of Stay ◽  
Clinical Data ◽  
Neonatal Intensive Care ◽  
Large Scale ◽  
Expert Knowledge ◽  
Clinical Analysis ◽  
Healthcare Operations ◽  
Lengths Of Stay ◽  
Health Trajectories ◽  
Widespread Implementation

Having an interpretable, dynamic length-of-stay model can help hospital administrators and clinicians make better decisions and improve the quality of care. The widespread implementation of electronic medical record (EMR) systems has enabled hospitals to collect massive amounts of health data. However, how to integrate this deluge of data into healthcare operations remains unclear. We propose a framework grounded in established clinical knowledge to model patients’ lengths of stay. In particular, we impose expert knowledge when grouping raw clinical data into medically meaningful variables that summarize patients’ health trajectories. We use dynamic, predictive models to output patients’ remaining lengths of stay, future discharges, and census probability distributions based on their health trajectories up to the current stay. Evaluated with large-scale EMR data, the dynamic model significantly improves predictive power over the performance of any model in previous literature and remains medically interpretable. Summary of Contribution: The widespread implementation of electronic health systems has created opportunities and challenges to best utilize mounting clinical data for healthcare operations. In this study, we propose a new approach that integrates clinical analysis in generating variables and implementations of computational methods. This approach allows our model to remain interpretable to the medical professionals while being accurate. We believe our study has broader relevance to researchers and practitioners of healthcare operations.

scholarly journals Enhancing ecosystem restoration efficiency through spatial and temporal coordination

2015 ◽  
Vol 112 (19) ◽  
pp. 6236-6241 ◽  
Author(s):  
Thomas M. Neeson ◽  
Michael C. Ferris ◽  
Matthew W. Diebel ◽  
Patrick J. Doran ◽  
Jesse R. O’Hanley ◽  
...  
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Expert Knowledge ◽  
Spatial Scales ◽  
Small Scale ◽  
Space And Time ◽  
Ecosystem Connectivity ◽  
Breeding Grounds ◽  
Local Expert ◽  
Conservation Projects

In many large ecosystems, conservation projects are selected by a diverse set of actors operating independently at spatial scales ranging from local to international. Although small-scale decision making can leverage local expert knowledge, it also may be an inefficient means of achieving large-scale objectives if piecemeal efforts are poorly coordinated. Here, we assess the value of coordinating efforts in both space and time to maximize the restoration of aquatic ecosystem connectivity. Habitat fragmentation is a leading driver of declining biodiversity and ecosystem services in rivers worldwide, and we simultaneously evaluate optimal barrier removal strategies for 661 tributary rivers of the Laurentian Great Lakes, which are fragmented by at least 6,692 dams and 232,068 road crossings. We find that coordinating barrier removals across the entire basin is nine times more efficient at reconnecting fish to headwater breeding grounds than optimizing independently for each watershed. Similarly, a one-time pulse of restoration investment is up to 10 times more efficient than annual allocations totaling the same amount. Despite widespread emphasis on dams as key barriers in river networks, improving road culvert passability is also essential for efficiently restoring connectivity to the Great Lakes. Our results highlight the dramatic economic and ecological advantages of coordinating efforts in both space and time during restoration of large ecosystems.

scholarly journals Fungarium specimens: a largely untapped source in global change biology and beyond

2018 ◽  
Vol 374 (1763) ◽  
pp. 20170392 ◽  
Author(s):  
Carrie Andrew ◽  
Jeffrey Diez ◽  
Timothy Y. James ◽  
Håvard Kauserud
Keyword(s):  
Global Change ◽  
Dna Sequences ◽  
Large Scale ◽  
Dna Analysis ◽  
Sampling Location ◽  
Sources Of Information ◽  
Dispersal Patterns ◽  
Global Change Biology ◽  
Richness Patterns ◽  
Collection Date

For several hundred years, millions of fungal sporocarps have been collected and deposited in worldwide collections (fungaria) to support fungal taxonomy. Owing to large-scale digitization programs, metadata associated with the records are now becoming publicly available, including information on taxonomy, sampling location, collection date and habitat/substrate information. This metadata, as well as data extracted from the physical fungarium specimens themselves, such as DNA sequences and biochemical characteristics, provide a rich source of information not only for taxonomy but also for other lines of biological inquiry. Here, we highlight and discuss how this information can be used to investigate emerging topics in fungal global change biology and beyond. Fungarium data are a prime source of knowledge on fungal distributions and richness patterns, and for assessing red-listed and invasive species. Information on collection dates has been used to investigate shifts in fungal distributions as well as phenology of sporocarp emergence in response to climate change. In addition to providing material for taxonomy and systematics, DNA sequences derived from the physical specimens provide information about fungal demography, dispersal patterns, and are emerging as a source of genomic data. As DNA analysis technologies develop further, the importance of fungarium specimens as easily accessible sources of information will likely continue to grow. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.

scholarly journals Large-Scale Systems Control Design via LMI Optimization

2015 ◽  
Vol 44 (3) ◽  
pp. 247-253
Author(s):  
Branislav Rehak
Keyword(s):  
Decentralized Control ◽  
Large Scale ◽  
Expert Knowledge ◽  
Control Design ◽  
Large Scale Systems ◽  
Large Scale System ◽  
Lmi Optimization ◽  
Control Gain ◽  
Systems Control

A control design for a large-scale system using LMI optimization is proposed. The control is designed in a way such that the LQ cost in the case of the decentralized control  does not exceed a certain limit. The optimized quantity are the values of the control gain matrices. The methodology is useful even for finding a decomposition of the system, however, some expert knowledge is necessary in this case. The capabilities of the algorithm are illustrated by two examples.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.6464

scholarly journals Citizen ownership of the state: A measure using election promise implementation score

2020 ◽  
Author(s):  
Abul Azad
Keyword(s):  
Empirical Data ◽  
Large Scale ◽  
Methodological Approach ◽  
Barack Obama ◽  
The State ◽  
Representative Government ◽  
Power Of Attorney ◽  
The Usa

<p><i>This paper introduces a measure of citizen ownership of the state, which works with empirical data. The paper defines citizen ownership of the state as a condition where whatever the majority of citizens want is implemented. In the present-day large scale state, whatever the majority of citizens want is expressed in the election promises of the winning party, alliance or individuals. The paper argues that the level of implementation of election promises is a measurement of citizen ownership of the state. It models the authority of a representative government to a power of attorney. The citizen as principal awards a power of attorney to the winning party, alliance or individuals as an agent in their election. In the election, the set of election promises of the agent becomes the only written part of the power of attorney. The 2008-2012 tenure of US President Barack Obama is used to test how the methodological approach works with empirical data. The test finds the citizen ownership of the state in the USA at 70.7 percent and the party intrusion into the ownership at 29.3 percent during the tenure.</i>.</p>

scholarly journals DNA screening of Drosophila suzukii predators in berry field orchards shows new predatory taxonomical groups

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249673
Author(s):  
Sara Sario ◽  
Conceição Santos ◽  
Fátima Gonçalves ◽  
Laura Torres
Keyword(s):  
Large Scale ◽  
Field Studies ◽  
Life Cycles ◽  
Gut Content ◽  
Drosophila Suzukii ◽  
Potential Predator ◽  
The Family ◽  
First Time ◽  
South Europe ◽  
New Habitats

Drosophila suzukii (spotted wing drosophila, SWD) is a pandemic quarantine pest that attacks mostly red fruits. The high number of life cycles per year, its ability to rapidly invade and spread across new habitats, and highly polyphagous nature, makes this a particularly aggressive invasive species, for which efficient control methods are currently lacking. The use of native natural predators is particularly promising to anchor sustainable and efficient measures to control SWD. While several field studies have suggested the presence of potential predatory species in infested orchards, only a few confirmed the presence of SWD DNA in predators’ gut content. Here, we use a DNA-based approach to identify SWD predators among the arthropod diversity in South Europe, by examining the gut content of potential predator specimens collected in SWD-infested berry fields in North Portugal. These specimens were morphologically identified to the family/order, and their gut content was screened for the presence of SWD DNA using PCR. New SWD predatory taxonomical groups were identified, as Opiliones and Hemerobiidae, in addition to known SWD predators, such as Hemerobiidae, Chrysopidae, Miridae, Carabidae, Formicidae and Araneae. Additionally, the presence of a spider family, Uloboridae, in the orchards was recorded for the first time, posing this family as another SWD-candidate predator. This study sets important bases to further investigate the potential large-scale use of some of these confirmed predator taxa for SWD control in South Europe.

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