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Selection: with tag modelling-uncertainty [97 articles] 

 

Fuzzy set theory for predicting the potential distribution and cost-effective monitoring of invasive species

  
Ecological Modelling, Vol. 316 (2015), pp. 122-132, https://doi.org/10.1016/j.ecolmodel.2015.07.034

Abstract

The presence of invasive species has been predicted using species distribution models (SDMs) and presence-only data to assist environmental management. However, SDMs include substantial uncertainty and the lack of absence data hampers the use of probabilistic predictions. A non-statistical theoretical basis able to deal with uncertainty on which to model invasive species distributions with presence-only data is thus needed. Fuzzy set theory satisfies these two requirements but has been little used. This paper proposes a fuzzy modelling approach for predicting invasive ...

 

Evaluating the performance of different empirical rainfall erosivity (R) factor formulas using sediment yield measurements

  
CATENA, Vol. 169 (October 2018), pp. 195-208, https://doi.org/10.1016/j.catena.2018.05.037

Abstract

[Highlights] [::] R-factor calculation method impact on soil erosion modeling [::] Comparative analysis (numerical, spatial) of 9 empirical R-factor formulas [::] RUSLE implementation on a typical mountainous Mediterranean catchment [::] Application on two time scales (annual, multi-annual) per R-factor approximation [::] Indirect validation (per R-factor method modelled against measured sediment yield) [Abstract] The study aims to evaluate the performance of nine empirical rainfall erosivity (R) factor formulas at the Venetikos River catchment, Northwestern Greece. The goal is to select the most appropriate one, for the accurate estimation of ...

 

Climate-vegetation-fire interactions and feedbacks: trivial detail or major barrier to projecting the future of the Earth system?

  
Wiley Interdisciplinary Reviews: Climate Change, Vol. 7, No. 6. (1 November 2016), pp. 910-931, https://doi.org/10.1002/wcc.428

Abstract

Fire is a complex process involving interactions and feedbacks between biological, socioeconomic, and physical drivers across multiple spatial and temporal scales. This complexity limits our ability to incorporate fire into Earth system models and project future fire activity under climate change. Conceptual, empirical, and process models have identified the mechanisms and processes driving fire regimes, and provide a useful basis to consider future fire activity. However, these models generally deal with only one component of fire regimes, fire frequency, and do ...

 

A projected decrease in lightning under climate change

  
Nature Climate Change, Vol. 8, No. 3. (12 February 2018), pp. 210-213, https://doi.org/10.1038/s41558-018-0072-6

Abstract

Lightning strongly influences atmospheric chemistry1,2,3, and impacts the frequency of natural wildfires4. Most previous studies project an increase in global lightning with climate change over the coming century1,5,6,7, but these typically use parameterizations of lightning that neglect cloud ice fluxes, a component generally considered to be fundamental to thunderstorm charging8. As such, the response of lightning to climate change is uncertain. Here, we compare lightning projections for 2100 using two parameterizations: the widely used cloud-top height (CTH) approach9, and a new ...

 

Maxent is not a presence-absence method: a comment on Thibaud et al

  
Methods in Ecology and Evolution, Vol. 5, No. 11. (November 2014), pp. 1192-1197, https://doi.org/10.1111/2041-210x.12252

Abstract

[Summary] [::1] Thibaud et al. (Methods in Ecology and Evolution 2014) present a framework for simulating species and evaluating the relative effects of factors affecting the predictions from species distribution models (SDMs). They demonstrate their approach by generating presence–absence data sets for different simulated species and analysing them using four modelling methods: three presence–absence methods and Maxent, which is a presence-background modelling tool. One of their results is striking: that their use of Maxent performs well in estimating occupancy probabilities and even ...

 

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

  
Proceedings of the National Academy of Sciences (22 January 2018), 201704665, https://doi.org/10.1073/pnas.1704665115

Abstract

[Significance] We increasingly rely on global models to project impacts of humans and climate on water resources. How reliable are these models? While past model intercomparison projects focused on water fluxes, we provide here the first comprehensive comparison of land total water storage trends from seven global models to trends from Gravity Recovery and Climate Experiment (GRACE) satellites, which have been likened to giant weighing scales in the sky. The models underestimate the large decadal (2002–2014) trends in water storage relative to ...

 

On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

  
Climatic Change, Vol. 118, No. 3-4. (2013), pp. 827-840, https://doi.org/10.1007/s10584-012-0667-2

Abstract

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean ...

 

Forest fire danger extremes in Europe under climate change: variability and uncertainty

  
Keywords: adaptation   array-of-factors   biodiversity   biodiversity-impacts   burnt-area   climate-change   climate-extremes   communicating-uncertainty   data-transformation-modelling   data-uncertainty   downscaling   droughts   dynamic-system   ecosystem-resilience   emergent-property   euro-cordex   europe   extreme-events   extreme-weather   fire-damage   fire-danger-rating   fire-management   fire-weather-index   forest-fires   forest-management   forest-pests   forest-resources   free-scientific-software   geospatial   geospatial-semantic-array-programming   human-behaviour   humidity   ipcc-scenarios   mastrave-modelling-library   mitigation   modelling-uncertainty   no-analog-pattern   peseta-series   precipitation   rcp85   resilience   resilience-vs-resistance   review   robust-modelling   science-policy-interface   science-society-interface   scientific-communication   semantic-array-programming   spatial-pattern   species-richness   species-specific-effects   temperature   vegetation-changes   wildfires   wind  

Abstract

Forests cover over a third of the total land area of Europe. In recent years, large forest fires have repeatedly affected Europe, in particular the Mediterranean countries. Fire danger is influenced by weather in the short term, and by climate when considering longer time intervals. In this work, the emphasis is on the direct influence on fire danger of weather and climate. [\n] For climate analysis at the continental scale, a daily high-emission scenario (RCP 8.5) was considered up to the end ...

References

  1. de Rigo, D., Bosco, C., San-Miguel-Ayanz, J., Houston Durrant, T., Barredo, J. I., Strona, G., Caudullo, G., Di Leo, M., Boca, R., 2016. Forest resources in Europe: an integrated perspective on ecosystem services, disturbances and threats. In: San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant, T., Mauri, A. (Eds.), European Atlas of Forest Tree Species. Publ. Off. EU, Luxembourg, pp. e015b50+. https://w3id.org/mtv/FISE-Comm/v01/e015b50 .
  2. Alberdi Asensio, I., Baycheva-Merger, T., Bouvet, A., Bozzano,
 

The lack of a priori distinctions between learning algorithms

  
Neural Computation, Vol. 8, No. 7. (1 October 1996), pp. 1341-1390, https://doi.org/10.1162/neco.1996.8.7.1341

Abstract

This is the first of two papers that use off-training set (OTS) error to investigate the assumption-free relationship between learning algorithms. This first paper discusses the senses in which there are no a priori distinctions between learning algorithms. (The second paper discusses the senses in which there are such distinctions.) In this first paper it is shown, loosely speaking, that for any two algorithms A and B, there are “as many” targets (or priors over targets) for which A has lower ...

 

Greater future global warming inferred from Earth’s recent energy budget

  
Nature, Vol. 552, No. 7683. (6 December 2017), pp. 45-50, https://doi.org/10.1038/nature24672

Abstract

Climate models provide the principal means of projecting global warming over the remainder of the twenty-first century but modelled estimates of warming vary by a factor of approximately two even under the same radiative forcing scenarios. Across-model relationships between currently observable attributes of the climate system and the simulated magnitude of future warming have the potential to inform projections. Here we show that robust across-model relationships exist between the global spatial patterns of several fundamental attributes of Earth’s top-of-atmosphere energy budget ...

 

Rules of thumb for judging ecological theories

  
Trends in Ecology & Evolution, Vol. 19, No. 3. (March 2004), pp. 121-126, https://doi.org/10.1016/j.tree.2003.11.004

Abstract

An impressive fit to historical data suggests to biologists that a given ecological model is highly valid. Models often achieve this fit at the expense of exaggerated complexity that is not justified by empirical evidence. Because overfitted theories complement the traditional assumption that ecology is `messy', they generally remain unquestioned. Using predation theory as an example, we suggest that a fit-driven appraisal of model value is commonly misdirected; although fit to historical data can be important, the simplicity and generality of ...

 

The strategy of model building in population biology

  
American Scientist, Vol. 54, No. 4. (1966), pp. 421-431

Abstract

[Excerpt: Cluster of models] A mathematical model is neither an hypothesis nor a theory. Unlike the scientific hypothesis, a model is not verifiable directly by experiment. For all models are both true and false. Almost any plausible proposed relation among aspects of nature is likely to be true in the sense that it occurs (although rarely and slightly). Yet all models leave out a lot and are in that sense false, incomplete, inadequate. The validation of a model is not that it ...

 

Bias correction in species distribution models: pooling survey and collection data for multiple species

  
Methods in Ecology and Evolution, Vol. 6, No. 4. (1 April 2015), pp. 424-438, https://doi.org/10.1111/2041-210x.12242

Abstract

[::] Presence-only records may provide data on the distributions of rare species, but commonly suffer from large, unknown biases due to their typically haphazard collection schemes. Presence–absence or count data collected in systematic, planned surveys are more reliable but typically less abundant. [::] We proposed a probabilistic model to allow for joint analysis of presence-only and survey data to exploit their complementary strengths. Our method pools presence-only and presence–absence data for many species and maximizes a joint likelihood, simultaneously estimating and adjusting ...

 

Point process models for presence-only analysis

  
Methods in Ecology and Evolution, Vol. 6, No. 4. (1 April 2015), pp. 366-379, https://doi.org/10.1111/2041-210x.12352

Abstract

[::] Presence-only data are widely used for species distribution modelling, and point process regression models are a flexible tool that has considerable potential for this problem, when data arise as point events. [::] In this paper, we review point process models, some of their advantages and some common methods of fitting them to presence-only data. [::] Advantages include (and are not limited to) clarification of what the response variable is that is modelled; a framework for choosing the number and location of quadrature ...

 

An empirical comparison of model validation techniques for defect prediction models

  
IEEE Transactions on Software Engineering, Vol. 43, No. 1. (1 January 2017), pp. 1-18, https://doi.org/10.1109/tse.2016.2584050

Abstract

Defect prediction models help software quality assurance teams to allocate their limited resources to the most defect-prone modules. Model validation techniques, such as k -fold cross-validation, use historical data to estimate how well a model will perform in the future. However, little is known about how accurate the estimates of model validation techniques tend to be. In this paper, we investigate the bias and variance of model validation techniques in the domain of defect prediction. Analysis of 101 public defect datasets ...

 

Resampling methods for meta-model validation with recommendations for evolutionary computation

  
Evolutionary Computation, Vol. 20, No. 2. (16 February 2012), pp. 249-275, https://doi.org/10.1162/evco_a_00069

Abstract

Meta-modeling has become a crucial tool in solving expensive optimization problems. Much of the work in the past has focused on finding a good regression method to model the fitness function. Examples include classical linear regression, splines, neural networks, Kriging and support vector regression. This paper specifically draws attention to the fact that assessing model accuracy is a crucial aspect in the meta-modeling framework. Resampling strategies such as cross-validation, subsampling, bootstrapping, and nested resampling are prominent methods for model validation and ...

 

Combining multiple classifiers: an application using spatial and remotely sensed information for land cover type mapping

  
Remote Sensing of Environment, Vol. 74, No. 3. (December 2000), pp. 545-556, https://doi.org/10.1016/s0034-4257(00)00145-0

Abstract

This article discusses two new methods for increasing the accuracy of classifiers used land cover mapping. The first method, called the product rule, is a simple and general method of combining two or more classification rules as a single rule. Stacked regression methods of combining classification rules are discussed and compared to the product rule. The second method of increasing classifier accuracy is a simple nonparametric classifier that uses spatial information for classification. Two data sets used for land cover mapping ...

 

Bagging ensemble selection for regression

  
In AI 2012: Advances in Artificial Intelligence, Vol. 7691 (2012), pp. 695-706, https://doi.org/10.1007/978-3-642-35101-3_59

Abstract

Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have shown that using random trees as base classifiers, BES-OOB (the most successful variant of BES) is competitive with (and in many cases, superior to) other ensemble learning strategies, for instance, the original ES algorithm, stacking with linear regression, random forests or boosting. Motivated by ...

 

Bagging ensemble selection

  
In AI 2011: Advances in Artificial Intelligence, Vol. 7106 (2011), pp. 251-260, https://doi.org/10.1007/978-3-642-25832-9_26

Abstract

Ensemble selection has recently appeared as a popular ensemble learning method, not only because its implementation is fairly straightforward, but also due to its excellent predictive performance on practical problems. The method has been highlighted in winning solutions of many data mining competitions, such as the Netflix competition, the KDD Cup 2009 and 2010, the UCSD FICO contest 2010, and a number of data mining competitions on the Kaggle platform. In this paper we present a novel variant: bagging ensemble selection. ...

 

Robust modelling of the impacts of climate change on the habitat suitability of forest tree species

  
Keywords: abies-alba   array-of-factors   artificial-neural-networks   bioclimatic-predictors   change-factor   climate-change   data-uncertainty   diversity   environmental-modelling   europe   extrapolation-uncertainty   featured-publication   forest-resources   free-scientific-knowledge   free-scientific-software   free-software   fuzzy   gdal   genetic-diversity   geospatial   geospatial-semantic-array-programming   gnu-bash   gnu-linux   gnu-octave   habitat-suitability   integration-techniques   mastrave-modelling-library   maximum-habitat-suitability   modelling-uncertainty   multiplicity   peseta-series   python   regional-climate-models   relative-distance-similarity   robust-modelling   semantic-array-programming   semantic-constraints   semantics   spatial-disaggregation   sres-a1b   supervised-training   unsupervised-training  

Abstract

[::] In Europe, forests play a strategic multifunctional role, serving economic, social and environmental purposes. However, their complex interaction with climate change is not yet well understood. [::] The JRC PESETA project series proposes a consistent multi-sectoral assessment of the impacts of climate change in Europe. [::] Within the PESETA II project, a robust methodology is introduced for modelling the habitat suitability of forest tree species (2071-2100 time horizon). [::] Abies alba (the silver fir) is selected as case study: a main European tree ...

References

  1. European Commission, 2013. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions - A new EU forest strategy: for forests and the forest based sector. No. COM(2013) 659 final. Communication from the Commission to the Council and the European Parliament. http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:52013DC0659 , INRMM-MiD:12642065 .
  2. European Commission, 2013. Commission staff working document accompanying the document: Communication from the commission to
 

Novel climates, no-analog communities, and ecological surprises

  
Frontiers in Ecology and the Environment, Vol. 5, No. 9. (November 2007), pp. 475-482, https://doi.org/10.1890/070037

Abstract

No-analog communities (communities that are compositionally unlike any found today) occurred frequently in the past and will develop in the greenhouse world of the future. The well documented no-analog plant communities of late-glacial North America are closely linked to “novel” climates also lacking modern analogs, characterized by high seasonality of temperature. In climate simulations for the Intergovernmental Panel on Climate Change A2 and B1 emission scenarios, novel climates arise by 2100 AD, primarily in tropical and subtropical regions. These future novel ...

 

Multispecies coalescent delimits structure, not species

  
Proceedings of the National Academy of Sciences, Vol. 114, No. 7. (14 February 2017), pp. 1607-1612, https://doi.org/10.1073/pnas.1607921114

Abstract

[Significance] Despite its widespread application to the species delimitation problem, our study demonstrates that what the multispecies coalescent actually delimits is structure. The current implementations of species delimitation under the multispecies coalescent do not provide any way for distinguishing between structure due to population-level processes and that due to species boundaries. The overinflation of species due to the misidentification of general genetic structure for species boundaries has profound implications for our understanding of the generation and dynamics of biodiversity, because any ecological ...

 

The ability of climate envelope models to predict the effect of climate change on species distributions

  
Global Change Biology, Vol. 12, No. 12. (1 December 2006), pp. 2272-2281, https://doi.org/10.1111/j.1365-2486.2006.01256.x

Abstract

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs ...

 

Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data

  
Ecological Applications, Vol. 19, No. 1. (January 2009), pp. 181-197, https://doi.org/10.1890/07-2153.1

Abstract

Most methods for modeling species distributions from occurrence records require additional data representing the range of environmental conditions in the modeled region. These data, called background or pseudo-absence data, are usually drawn at random from the entire region, whereas occurrence collection is often spatially biased toward easily accessed areas. Since the spatial bias generally results in environmental bias, the difference between occurrence collection and background sampling may lead to inaccurate models. To correct the estimation, we propose choosing background data with ...

 

Model-based uncertainty in species range prediction

  
Journal of Biogeography, Vol. 33, No. 10. (October 2006), pp. 1704-1711, https://doi.org/10.1111/j.1365-2699.2006.01460.x

Abstract

[Aim]  Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. [Location]  The Western Cape of South Africa. [Methods]  We applied nine of the most widely used modelling techniques to model potential ...

 

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

  
Global Ecology and Biogeography, Vol. 12, No. 5. (1 September 2003), pp. 361-371, https://doi.org/10.1046/j.1466-822x.2003.00042.x

Abstract

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate ...

 

Observational evidence for cloud cover enhancement over western European forests

  
Nature Communications, Vol. 8 (11 January 2017), 14065, https://doi.org/10.1038/ncomms14065

Abstract

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, ...

Visual summary

 

Soil erosion assessment - Mind the gap

  
Geophys. Res. Lett., Vol. 43, No. 24. (28 December 2016), 2016GL071480, https://doi.org/10.1002/2016gl071480

Abstract

Accurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors—long studied and referred to as “geomorphic external variability”, and microscale effects, introduced as “geomorphic internal variability.” The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at ...

 

Fire behaviour knowledge in Australia: a synthesis of disciplinary and stakeholder knowledge on fire spread prediction capability and application

  
(2014)

Abstract

[Executive summary] This project undertook a survey of the fire behaviour knowledge currently used by operational fire behaviour analysts (FBANs) in Australia and New Zealand for the purpose of predicting the behaviour and spread of bushfires. This included a review of the science, applicability and validation of current fire behaviour models, an examination of the fire perimeter propagation software currently being used by FBANs, and a survey of those FBANs to determine current work practices when carrying out fire behaviour predictions. ...

 

More accountability for big-data algorithms

  
Nature, Vol. 537, No. 7621. (21 September 2016), pp. 449-449, https://doi.org/10.1038/537449a

Abstract

To avoid bias and improve transparency, algorithm designers must make data sources and profiles public. [Excerpt] [...] Algorithms, from the simplest to the most complex, follow sets of instructions or learn to accomplish a goal. In principle, they could help to make impartial analyses and decisions by reducing human biases and prejudices. But there is growing concern that they risk doing the opposite, and will replicate and exacerbate human failings [...]. And in an era of powerful computers, machine learning and big data, ...

 

The precision problem in conservation and restoration

  
Trends in Ecology & Evolution (2016), https://doi.org/10.1016/j.tree.2016.08.001

Abstract

Within the varied contexts of environmental policy, conservation of imperilled species populations, and restoration of damaged habitats, an emphasis on idealized optimal conditions has led to increasingly specific targets for management. Overly-precise conservation targets can reduce habitat variability at multiple scales, with unintended consequences for future ecological resilience. We describe this dilemma in the context of endangered species management, stream restoration, and climate-change adaptation. Inappropriate application of conservation targets can be expensive, with marginal conservation benefit. Reduced habitat variability can limit ...

 

Climate change and the eco-hydrology of fire: will area burned increase in a warming western U.S.?

  
Ecological Applications (August 2016), https://doi.org/10.1002/eap.1420

Abstract

Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong, such as mesic and arid forests and shrublands with substantial biomass such as chaparral. We examine the drought-fire relationship, specifically the correlations between water-balance deficit and annual area burned, across ...

 

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

  
Proceedings of the National Academy of Sciences, Vol. 113, No. 36. (06 September 2016), pp. 10019-10024, https://doi.org/10.1073/pnas.1604581113

Abstract

[Significance] We show that the water savings that plants experience under high CO2 conditions compensate for much of the effect of warmer temperatures, keeping the amount of water on land, on average, higher than we would predict with common drought metrics, and with a different spatial pattern. The implications of plants needing less water under high CO2 reaches beyond drought prediction to the assessment of climate change impacts on agriculture, water resources, wildfire risk, and vegetation dynamics. [Abstract] Rising atmospheric CO2 will make Earth ...

 

Intercomparison of MODIS albedo retrievals and in situ measurements across the global FLUXNET network

  
Remote Sensing of Environment, Vol. 121 (June 2012), pp. 323-334, https://doi.org/10.1016/j.rse.2012.02.019

Abstract

[Abstract] Surface albedo is a key parameter in the Earth's energy balance since it affects the amount of solar radiation directly absorbed at the planet surface. Its variability in time and space can be globally retrieved through the use of remote sensing products. To evaluate and improve the quality of satellite retrievals, careful intercomparisons with in situ measurements of surface albedo are crucial. For this purpose we compared MODIS albedo retrievals with surface measurements taken at 53 FLUXNET sites that met strict ...

 

Comparison of model predictions with measurements: a novel model-assessment method

  
Journal of Dairy Science, Vol. 99, No. 6. (June 2016), pp. 4907-4927, https://doi.org/10.3168/jds.2015-10032

Abstract

Frequently, scientific findings are aggregated using mathematical models. Because models are simplifications of the complex reality, it is necessary to assess whether they capture the relevant features of reality for a given application. An ideal assessment method should (1) account for the stochastic nature of observations and model predictions, (2) set a correct null hypothesis, (3) treat model predictions and observations interchangeably, and (4) provide quantitatively interpretable statistics relative to precision and accuracy. Current assessment methods show deficiencies in regards to ...

 

Influence of different species range types on the perception of macroecological patterns

  
Systematics and Biodiversity, Vol. 9, No. 2. (1 June 2011), pp. 159-170, https://doi.org/10.1080/14772000.2011.588726

Abstract

In the face of increasing availability and use of distribution data, large-scale approaches of mapping species distribution patterns have become a central component of development of large-scale conservation policies. Particularly in tropical regions and for non-vertebrate taxa, knowledge on distribution patterns at large spatial extents remains woefully limited. Datasets are often geographically and taxonomically incomplete, have presence-only character and lack abundance information. One intermediate step for the application of such data common to most approaches is the construction of species geographic ...

 

Effects of incorporating spatial autocorrelation into the analysis of species distribution data

  
Global Ecology and Biogeography, Vol. 16, No. 2. (March 2007), pp. 129-138, https://doi.org/10.1111/j.1466-8238.2006.00279.x

Abstract

[Aim]  Spatial autocorrelation (SAC) in data, i.e. the higher similarity of closer samples, is a common phenomenon in ecology. SAC is starting to be considered in the analysis of species distribution data, and over the last 10 years several studies have incorporated SAC into statistical models (here termed ‘spatial models’). Here, I address the question of whether incorporating SAC affects estimates of model coefficients and inference from statistical models. [Methods]  I review ecological studies that compare spatial and non-spatial models. [Results]  In all ...

 

Calibration of remotely sensed proportion or area estimates for misclassification error

  
Remote Sensing of Environment, Vol. 39, No. 1. (January 1992), pp. 29-43, https://doi.org/10.1016/0034-4257(92)90138-a

Abstract

Classifications of remotely sensed data contain misclassification errors that bias areal estimates. Monte Carlo techniques were used to compare two statistical methods that correct or calibrate remotely sensed areal estimates for misclassification bias using reference data from an error matrix. The inverse calibration estimator was consistently superior to the classical estimator using a simple random sample of reference plots. The effects of sample size of reference plots, detail of the classification system, and classification accuracy on the precision of the inverse ...

 

Comparison between the USLE, the USLE-M and replicate plots to model rainfall erosion on bare fallow areas

  
CATENA, Vol. 145 (October 2016), pp. 39-46, https://doi.org/10.1016/j.catena.2016.05.017

Abstract

[Highlights] [::] Examines ability of soil losses from a plot to predict those from another [::] Stochastic and systemic variations observed when replicate model used [::] Replicate model tends to perform better that USLE-M when runoff known. [Abstract] It has been proposed that the best physical model of erosion from a plot is provided by a replicate plot (Nearing, 1998). Event data from paired bare fallow plots in the USLE database were used to examine the abilities of replicate plots, the USLE and the USLE-M to ...

 

An assessment of methods and remote-sensing derived covariates for regional predictions of 1 km daily maximum air temperature

  
Remote Sensing, Vol. 6, No. 9. (16 September 2014), pp. 8639-8670, https://doi.org/10.3390/rs6098639

Abstract

The monitoring and prediction of biodiversity and environmental changes is constrained by the availability of accurate and spatially contiguous climatic variables at fine temporal and spatial grains. In this study, we evaluate best practices for generating gridded, one-kilometer resolution, daily maximum air temperature surfaces in a regional context, the state of Oregon, USA. Covariates used in the interpolation include remote sensing derived elevation, aspect, canopy height, percent forest cover and MODIS Land Surface Temperature (LST). Because of missing values, ...

 

Modelling as a discipline

  
International Journal of General Systems, Vol. 30, No. 3. (1 January 2001), pp. 261-282, https://doi.org/10.1080/03081070108960709

Abstract

Modelling is an essential and inseparable part of all scientific, and indeed all intellectual, activity. How then can we treat it as a separate discipline? The answer is that the professional modeller brings special skills and techniques to bear in order to produce results that are insightful, reliable, and useful. Many of these techniques can be taught formally, such as sophisticated statistical methods, computer simulation, systems identification, and sensitivity analysis. These are valuable tools, but they are not as important as ...

 

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

  
Int. J. Climatol., Vol. 37, No. 1. (1 March 2017), pp. 305-327, https://doi.org/10.1002/joc.4706

Abstract

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution ...

 

(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 25

  
(February 2014)
Keywords: inrmm-list-of-tags   miocene   mires   miridae   missing-full-author-list   mistletoe   misuse-of-modelling-tools-by-nonexperts   mitigation   mitochondrial-dna   mixed-forest   mixed-models   mixed-species-stand   mobile-communication   mobility   mode   model   model-assessment   model-comparison   model-drift   modelling   modelling-uncertainty   modelling-vs-management   moderate-floods   modern-analogue   modis   modularization   moist-convection   molinia-caerulea   molluscs   monetarisation   mongolia   monitoring   monochamus-galloprovincialis   monochamus-spp   monography   monoterpenes   monsoon   montane-belt   monte-carlo   monte-carlo-trajectory   monumental-trees   moorland   mordwilkoja-vagabundus   morinda-citrifolia   moringa-oleifera   morocco   morphological-adaptations   morphological-traits   morphology   mortality   morus-alba   morus-nigra   morus-spp   motor-vehicles   mountainous-areas   mozambique   muddy-floods   multi-criteria-decision-analysis   multi-objective-planning   multi-scale   multi-stakeholder-decision-making   multiauthor   multiple-adaptive-regression-splines   multiplicative-structure   multiplicity   mushrooms   mutualism   mycorrhizal-fungi   mycosphaerella-dearnessii   mycosphaerella-pini   myopic-heuristics   myrica-cerifera   myrica-gale   myricaria-germanica   myristica-fragrans   myrrhoides-nodosa   myrtus-communis   myths   mytilus-edulis   myzocallis-coryli   nanoparticles   nasa   natech   national-fire-danger-rating-system   native-vegetation   natura-2000   natural-disaster   natural-disasters   natural-disturbance   natural-ecosystems   natural-hazard-triggering-technological-disasters   natural-hazards   natural-loss   natural-product-herbicides   natural-resources-interactions   naturalised-species   nauclea-diderichii   ndvi   neanderthals   near-surface-flowpaths  

Abstract

List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( http://mfkp.org/INRMM/tag/inrmm-list-of-tags ). ...

 

European atlas of forest tree species

  
Keywords: bioeconomy   chorology   classification   climate   constrained-spatial-multi-frequency-analysis   data-heterogeneity   data-integration   data-uncertainty   disasters   disturbances   ecological-zones   ecology   ecosystem-services   europe   floods   forest-fires   forest-pests   forest-resources   free-software   geospatial   geospatial-semantic-array-programming   gis   gnu-bash   gnu-linux   gnu-octave   habitat-suitability   integrated-modelling   integrated-natural-resources-modelling-and-management   integration-techniques   knowledge-integration   landslides   mastrave-modelling-library   modelling-uncertainty   open-data   paleoecology   relative-distance-similarity   reproducible-research   review   science-policy-interface   science-society-interface   semantic-array-programming   semantic-constraints   semantics   semap   software-uncertainty   soil-erosion   soil-resources   species-distribution   tree-species   uncertainty   water-resources   windstorm  

Abstract

[Excerpt] The European Atlas of Forest Tree Species is the first comprehensive publication of such a unique and essential environmental resource, that is, our trees. Leading scientists and forestry professionals have contributed in the many stages of the production of this atlas, through the collection of ground data on the location of tree species, elaboration of the distribution and suitability maps, production of the photographic material and compilation of the different chapters. The European Atlas of Forest Tree Species is both ...

 

Climate science: where climate models fall short

  
Nature, Vol. 531, No. 7592. (2 March 2016), pp. 10-10, https://doi.org/10.1038/531010d

Abstract

Climate models tend to overestimate the extent to which climate change contributes to weather events such as extreme heat and rain. [\n] Omar Bellprat and Francisco Doblas-Reyes at the Catalan Institute of Climate Sciences in Barcelona, Spain, used an idealized statistical model to compare the frequency of weather extremes in simulations [...] ...

 

Europe’s forest management did not mitigate climate warming

  
Science, Vol. 351, No. 6273. (2016), pp. 597-600, https://doi.org/10.1126/science.aad7270

Abstract

[Europe's managed forests contribute to warming] For most of the past 250 years, surprisingly it seems that Europe's managed forests have been a net source of carbon, contributing to climate warming rather than mitigating it. Naudts et al. reconstructed the history of forest management in Europe in the context of a land-atmosphere model. The release of carbon otherwise stored in litter, dead wood, and soil carbon pools in managed forests was one key factor contributing to climate warming. Second, the conversion of ...

 

The true loss caused by biodiversity offsets

  
Biological Conservation, Vol. 192 (December 2015), pp. 552-559, https://doi.org/10.1016/j.biocon.2015.08.016

Abstract

Biodiversity offsets aim to achieve a “no-net-loss” of biodiversity, ecosystem functions and services due to development. The “no-net-less” objective assumes that the multi-dimensional values of biodiversity in complex ecosystems can be isolated from their spatial, evolutionary, historical, social, and moral context. We examine the irreplaceability of ecosystems, the limits of restoration, and the environmental values that claim to be compensated through ecosystem restoration. We discuss multiple ecological, instrumental, and non-instrumental values of ecosystems that should be considered in offsetting calculations. Considering ...

 

An indicator framework for assessing ecosystem services in support of the EU Biodiversity Strategy to 2020

  
Ecosystem Services, Vol. 17 (February 2016), pp. 14-23, https://doi.org/10.1016/j.ecoser.2015.10.023

Abstract

[Highlights] [::] EU Member states have to map and assess ecosystems and their services (MAES). [::] We present the MAES conceptual model which links biodiversity to human wellbeing. [::] Typologies of ecosystems and their services ensure comparability across countries. [::] We present a list of indicators that can be used for national MAES assessments. [::] We critically discuss the data gaps and challenges of the MAES typologies. [Abstract] In the EU, the mapping and assessment of ecosystems and their services, abbreviated to MAES, is seen as a key ...

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On the extinction of craft skills with numbers - The case of “Overall, 7.9% of species are predicted to become extinct from climate change.”

  
(December 2015)

Abstract

[Excerpt: Introduction] [\n] This paper is about craft skills with numbers and, in particular, about problems with the use of numbers of unknown pedigree. As an example, I will discuss a very striking number that appeared in the mainstream press in early May 20152: a new scientific study was reported to have found that 7.9% of species would become extinct as a result of climate change. What was quite remarkable about this number is that it had two digits: not 10%, not ...

 

Consistent and clear reporting of results from diverse modeling techniques: the A3 method

  
Journal of Statistical Software, Vol. 66, No. 7. (2015), https://doi.org/10.18637/jss.v066.i07

Abstract

The measurement and reporting of model error is of basic importance when constructing models. Here, a general method and an R package, A3, are presented to support the assessment and communication of the quality of a model fit along with metrics of variable importance. The presented method is accurate, robust, and adaptable to a wide range of predictive modeling algorithms. The method is described along with case studies and a usage guide. It is shown how the method can be used ...

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Integrated Natural Resources Modelling and Management - Meta-information Database. http://mfkp.org/INRMM/tag/modelling-uncertainty

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Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
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INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.