Exploring Expert Knowledge of Forest Succession: An Assessment of Uncertainty and a Comparison with Empirical Data

2011 ◽  
pp. 173-188
Author(s):  
Michael Drescher ◽  
Ajith H. Perera
Keyword(s):  
Empirical Data ◽  
Expert Knowledge ◽  
Forest Succession

scholarly journals Die Kastanie im Engadin – oder was halten Baumarten von modellierten Potenzialgebieten? Chestnut in the Engadine – what do tree species think about model predictions?

2008 ◽  
Vol 159 (10) ◽  
pp. 326-335 ◽  
Author(s):  
Niklaus E. Zimmermann ◽  
Harald Bugmann
Keyword(s):  
Tree Species ◽  
Expert Knowledge ◽  
Forest Succession ◽  
Future Climate ◽  
Sensitivity Analyses ◽  
Climate Projections ◽  
Distribution Models ◽  
Modeling Approaches ◽  
Model Predictions ◽  
National Analysis

New IPCC climate projections suggest drastic changes in future climate. We discuss two commonly used modeling approaches, statistical distribution models and dynamic forest succession models, as they are suitable for assessing expected effects of climate change on the tree species distribution in Switzerland and for assisting management decisions in forestry. We discuss the basic assumptions and the strengths and weaknesses of the two approaches, without an understanding of which it is impossible to fully judge the outcome of modeling exercises. We give an overview of results from applying these two modeling approaches in Switzerland and in the Alps and discuss their appropriate use. We believe that these models are an important basis for decision making in the face of highly uncertain development of future climate. Nonetheless, models do not represent an exact copy of reality. Plausibility analyses are necessary in order to assess the results' usefulness and precision. Sensitivity analyses and a critical comparison of model results with expert knowledge of current forests, long measurement time series and other data are important. Also, dialog with practitioners and managers is not only important for checking the plausibility of model predictions under current conditions, but may also serve to improve the evaluation of future projections. We propose to apply models to the whole of Switzerland and to many tree species. Such a concerted national analysis may serve the adaptive management of forests and may strengthen dialog between researchers and practitioners.

scholarly journals Developing an improved biomonitoring tool for fine sediment: Combining expert knowledge and empirical data

2015 ◽  
Vol 54 ◽  
pp. 82-86 ◽  
Author(s):  
Matt D. Turley ◽  
Gary S. Bilotta ◽  
Tobias Krueger ◽  
Richard E. Brazier ◽  
Chris A. Extence
Keyword(s):  
Empirical Data ◽  
Expert Knowledge ◽  
Fine Sediment ◽  
Biomonitoring Tool

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 Learning from Both Experts and Data

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1208
Author(s):  
Rémi Besson ◽  
Erwan Le Pennec ◽  
Stéphanie Allassonnière
Keyword(s):  
Probability Distribution ◽  
Data Acquisition ◽  
Empirical Data ◽  
Domain Knowledge ◽  
Expert Knowledge ◽  
A Priori ◽  
Online Data ◽  
Discrete Probability ◽  
Intermediate Regime ◽  
Initial Domain

In this work, we study the problem of inferring a discrete probability distribution using both expert knowledge and empirical data. This is an important issue for many applications where the scarcity of data prevents a purely empirical approach. In this context, it is common to rely first on an a priori from initial domain knowledge before proceeding to an online data acquisition. We are particularly interested in the intermediate regime, where we do not have enough data to do without the initial a priori of the experts, but enough to correct it if necessary. We present here a novel way to tackle this issue, with a method providing an objective way to choose the weight to be given to experts compared to data. We show, both empirically and theoretically, that our proposed estimator is always more efficient than the best of the two models (expert or data) within a constant.

The Influence of Think Tanks in the Chinese Policy Process: Different Ways and Mechanisms

Asian Survey ◽  
2009 ◽  
Vol 49 (2) ◽  
pp. 333-357 ◽  
Author(s):  
Zhu Xufeng
Keyword(s):  
Empirical Data ◽  
Policy Process ◽  
Expert Knowledge ◽  
Nationwide Survey ◽  
Think Tanks ◽  
Different Types ◽  
Chinese Policy

This article argues that expert knowledge, governmental linkage, and personal ties are the factors that determine think tanks' influence in the Chinese policy process. Moreover, different types of think tanks exert influence through different mechanisms. Empirical data are from a 2004 nationwide survey of 301 of China's think tanks.

Uncertainty in expert knowledge of forest succession: A case study from boreal Ontario

2008 ◽  
Vol 84 (2) ◽  
pp. 194-209 ◽  
Author(s):  
M. Drescher ◽  
A H Perera ◽  
L J Buse ◽  
K. Ride ◽  
S. Vasiliauskas
Keyword(s):  
Forest Management ◽  
Expert Knowledge ◽  
Forest Succession ◽  
Coniferous Forest ◽  
Mixed Forest ◽  
Management Decision ◽  
Forest Types ◽  
Complex Species ◽  
Forest Management Planning ◽  
Environmental Controls

Expert knowledge of forest succession is used widely in forest management planning, but its level of uncertainty is unknown. Using boreal Ontario as an example, we examined the level of uncertainty in expert knowledge of forest succession and explored possible sources of this uncertainty. Overall, the level of uncertainty associated with expert knowledge was high for all aspects of forest succession, except for post-fire species establishment. Higher levels of uncertainty were associated with knowledge of forest succession for mixed forest types and moderate site conditions, as opposed to coniferous or non-coniferous forest types and extreme dry/wet or poor/rich sites. We hypothesize that uncertainty in expert knowledge is highest when vegetation dynamics are highly stochastic as with complex species assemblages, environmental controls on succession are weak, and effects of disturbances are less drastic. Awareness about the degree of uncertainty in expert knowledge of forest succession could be incorporated into forest management decision processes. It could also help researchers to identify critical knowledge gaps to guide further studies. Key words: uncertainty assessment, post-fire establishment, natural succession, knowledge elicitation

An empirical review of gambling expansion and gambling-related harm

2018 ◽  
Vol 64 (5-6) ◽  
pp. 295-306 ◽  
Author(s):  
Debi A. LaPlante ◽  
Heather M. Gray ◽  
Pat M. Williams ◽  
Sarah E. Nelson
Keyword(s):  
Literature Review ◽  
Peer Review ◽  
Empirical Data ◽  
Empirical Studies ◽  
Expansion Method ◽  
Responsible Gambling ◽  
Review Literature ◽  
Evidence Based ◽  
Empirical Comparison ◽  
Related Harm

Abstract. Aims: To discuss and review the latest research related to gambling expansion. Method: We completed a literature review and empirical comparison of peer reviewed findings related to gambling expansion and subsequent gambling-related changes among the population. Results: Although gambling expansion is associated with changes in gambling and gambling-related problems, empirical studies suggest that these effects are mixed and the available literature is limited. For example, the peer review literature suggests that most post-expansion gambling outcomes (i. e., 22 of 34 possible expansion outcomes; 64.7 %) indicate no observable change or a decrease in gambling outcomes, and a minority (i. e., 12 of 34 possible expansion outcomes; 35.3 %) indicate an increase in gambling outcomes. Conclusions: Empirical data related to gambling expansion suggests that its effects are more complex than frequently considered; however, evidence-based intervention might help prepare jurisdictions to deal with potential consequences. Jurisdictions can develop and evaluate responsible gambling programs to try to mitigate the impacts of expanded gambling.

Under- and Over-Estimation

2011 ◽  
Vol 58 (1) ◽  
pp. 39-49 ◽  
Author(s):  
Virginie Crollen ◽  
Julie Castronovo ◽  
Xavier Seron
Keyword(s):  
Empirical Data ◽  
Accurate Estimation ◽  
Numerical Estimation ◽  
Production Task ◽  
Estimation Task ◽  
Reproduction Task ◽  
Perception Task ◽  
Adult Participants ◽  
Mapping Hypothesis ◽  
Task Perception

Over the last 30 years, numerical estimation has been largely studied. Recently, Castronovo and Seron (2007) proposed the bi-directional mapping hypothesis in order to account for the finding that dependent on the type of estimation task (perception vs. production of numerosities), reverse patterns of performance are found (i.e., under- and over-estimation, respectively). Here, we further investigated this hypothesis by submitting adult participants to three types of numerical estimation task: (1) a perception task, in which participants had to estimate the numerosity of a non-symbolic collection; (2) a production task, in which participants had to approximately produce the numerosity of a symbolic numerical input; and (3) a reproduction task, in which participants had to reproduce the numerosity of a non-symbolic numerical input. Our results gave further support to the finding that different patterns of performance are found according to the type of estimation task: (1) under-estimation in the perception task; (2) over-estimation in the production task; and (3) accurate estimation in the reproduction task. Moreover, correlation analyses revealed that the more a participant under-estimated in the perception task, the more he/she over-estimated in the production task. We discussed these empirical data by showing how they can be accounted by the bi-directional mapping hypothesis ( Castronovo & Seron, 2007 ).

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