Journal articles: 'Bioclimatic modelling'

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Heikkinen, Risto K., Miska Luoto, Miguel B. Araújo, Raimo Virkkala, Wilfried Thuiller, and Martin T. Sykes. "Methods and uncertainties in bioclimatic envelope modelling under climate change." Progress in Physical Geography: Earth and Environment 30, no. 6 (2006): 751–77. http://dx.doi.org/10.1177/0309133306071957.

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Potential impacts of projected climate change on biodiversity are often assessed using single-species bioclimatic ‘envelope’models. Such models are a special case of species distribution models in which the current geographical distribution of species is related to climatic variables so to enable projections of distributions under future climate change scenarios. This work reviews a number of critical methodological issues that may lead to uncertainty in predictions from bioclimatic modelling. Particular attention is paid to recent developments of bioclimatic modelling that address some of these issues as well as to the topics where more progress needs to be made. Developing and applying bioclimatic models in a informative way requires good understanding of a wide range of methodologies, including the choice of modelling technique, model validation, collinearity, autocorrelation, biased sampling of explanatory variables, scaling and impacts of non-climatic factors. A key challenge for future research is integrating factors such as land cover, direct CO2 effects, biotic interactions and dispersal mechanisms into species-climate models. We conclude that, although bioclimatic envelope models have a number of important advantages, they need to be applied only when users of models have a thorough understanding of their limitations and uncertainties.

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Barber, Xavier, David Conesa, Antonio López-Quílez, and Javier Morales. "Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach." Journal of Agricultural, Biological and Environmental Statistics 24, no. 2 (2019): 225–44. http://dx.doi.org/10.1007/s13253-018-00345-z.

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Braidwood, David, and Christopher J. Ellis. "Bioclimatic equilibrium for lichen distributions on disjunct continental landmasses." Botany 90, no. 12 (2012): 1316–25. http://dx.doi.org/10.1139/b2012-103.

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Bioclimatic models assume that species distributions reflect their sensitivity to macroclimate, the so-called bioclimatic equilibrium. This has proven to be a controversial assumption. Here we perform a new test in the hypothesis of climatic equilibrium by comparing species’ bioclimatic space between two independently derived spatial distributions in Britain and North America. A presence-only statistical model (MAXENT) was used to construct bioclimatic response surfaces for 25 lichens in North America. These models were then projected onto British climate space. We tested the following: (1) the statistical congruence between likelihood values for North American bioclimatic space projected onto Britain and species’ observed British distributions, and (2) the extent to which the projection for a species matched its observed British distribution pattern better than the distributions for an alternative suite of species. In general, there is good evidence for bioclimatic equilibrium when comparing species distributions in North America and Britain. However, bioclimatic test 1 (statistical congruence) and bioclimatic test 2 (spatial matching) were failed by six (24% of cases) and four (16% of cases) species, respectively. Although there is general support for bioclimatic modelling in lichens, the species that failed a test of equilibrium would have been difficult to predict based on prior knowledge; however it may be explained by taxonomic uncertainty and (or) the existence of multiple correlated environmental drivers.

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Gavin, Daniel G., and Feng Sheng Hu. "Bioclimatic modelling using Gaussian mixture distributions and multiscale segmentation." Global Ecology and Biogeography 14, no. 5 (2005): 491–501. http://dx.doi.org/10.1111/j.1466-822x.2005.00171.x.

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Metcalf, Jessica L., Stefan Prost, David Nogués-Bravo, et al. "Integrating multiple lines of evidence into historical biogeography hypothesis testing: a Bison bison case study." Proceedings of the Royal Society B: Biological Sciences 281, no. 1777 (2014): 20132782. http://dx.doi.org/10.1098/rspb.2013.2782.

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One of the grand goals of historical biogeography is to understand how and why species' population sizes and distributions change over time. Multiple types of data drawn from disparate fields, combined into a single modelling framework, are necessary to document changes in a species's demography and distribution, and to determine the drivers responsible for change. Yet truly integrated approaches are challenging and rarely performed. Here, we discuss a modelling framework that integrates spatio-temporal fossil data, ancient DNA, palaeoclimatological reconstructions, bioclimatic envelope modelling and coalescence models in order to statistically test alternative hypotheses of demographic and potential distributional changes for the iconic American bison ( Bison bison ). Using different assumptions about the evolution of the bioclimatic niche, we generate hypothetical distributional and demographic histories of the species. We then test these demographic models by comparing the genetic signature predicted by serial coalescence against sequence data derived from subfossils and modern populations. Our results supported demographic models that include both climate and human-associated drivers of population declines. This synthetic approach, integrating palaeoclimatology, bioclimatic envelopes, serial coalescence, spatio-temporal fossil data and heterochronous DNA sequences, improves understanding of species' historical biogeography by allowing consideration of both abiotic and biotic interactions at the population level.

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Back, Yannick, Peter Marcus Bach, Alrun Jasper-Tönnies, Wolfgang Rauch, and Manfred Kleidorfer. "A rapid fine-scale approach to modelling urban bioclimatic conditions." Science of The Total Environment 756 (February 2021): 143732. http://dx.doi.org/10.1016/j.scitotenv.2020.143732.

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Assis, Jorge, Lennert Tyberghein, Samuel Bosch, Heroen Verbruggen, Ester A. Serrão, and Olivier De Clerck. "Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling." Global Ecology and Biogeography 27, no. 3 (2017): 277–84. http://dx.doi.org/10.1111/geb.12693.

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Zhidekulova, G., Zh Mustafayev, and A. Kozykeyeva. "Regulation of irrigation: Modelling of bioclimatic coefficients of agricultural cultures." Research on Crops 19, no. 1 (2018): 132. http://dx.doi.org/10.5958/2348-7542.2018.00022.0.

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Tytar, V. M., and Ya R. Oksentyuk. "Modelling the Bioclimatic Niche of a Cohort of Selected Mite Species (Acari, Acariformes) Associated with the Infestation of Stored Products." Vestnik Zoologii 53, no. 5 (2019): 399–416. http://dx.doi.org/10.2478/vzoo-2019-0036.

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Abstract In this study an attempt is made to highlight important variables shaping the current bioclimatic niche of a number of mite species associated with the infestation of stored products by employing a species distribution modeling (SDM) approach. Using the ENVIREM dataset of bioclimatic variables, performance of the most robust models was mostly influenced by: 1) indices based on potential evapotranspiration, which characterize ambient energy and are mostly correlated with temperature variables, moisture regimes, and 2) strong fluctuations in temperature reflecting the severity of climate and/or extreme weather events. Although the considered mite species occupy man-made ecosystems, they remain more or less affected by the surrounding bioclimatic environment and therefore could be subjected to contemporary climate change. In this respect investigations are needed to see how this will affect future management targets concerning the safety of food storages.

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Boreux, J. J., C. Gadbin-Henry, J. Guiot, and L. Tessier. "Radial tree-growth modelling with fuzzy regression." Canadian Journal of Forest Research 28, no. 8 (1998): 1249–60. http://dx.doi.org/10.1139/x98-088.

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A so-called fuzzy linear regression is used in dendroecology to model empirically tree growth as a function of a bioclimatic index representing the water stress, i.e., the ratio of actual evapotranspiration to potential evapotranspiration. The response function predicts tree growth as (fuzzy) intervals, narrow in the domain where the bioclimatic index is most limiting and becoming progressively larger elsewhere. The method is tested with a population of Pinus pineaL. from the Provence region in France. It is shown that fuzzy linear regression gives results comparable with those obtained using a linear response function. The interval of credibility given by the fuzzy regression suggests that more precise expected growth is obtained for high water stress, which is typical of Mediterranean climate. Fuzzy linear regression can be also a method to test different hypotheses on several potential predictors when any further experimental approach is quite impossible as it is for trees in their natural environment. To sum up, fuzzy regression could be a first step before the construction of a kind of growth simulator adapted to different environments of a given species. In environmental sciences, the fuzzy response function thus appears to be an approach between the mechanistic and the statistical descriptive approaches.

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TAN, MING KAI, SIGFRID INGRISCH, and RODZAY BIN HAJI ABDUL WAHAB. "First Velarifictorus (Orthoptera: Gryllidae, Gryllinae) cricket described from Borneo (Southeast Asia) and notes on a co-occurring congener." Zootaxa 4282, no. 2 (2017): 374. http://dx.doi.org/10.11646/zootaxa.4282.2.10.

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Based on newly collected specimens from Brunei, a new species of Velarifictorus Randell, 1964 is described: Velarifictorus temburongensis sp. nov. This represents the first species of the genus Velarifictorus to be described from Borneo. Unexpectedly, the more widespread species Velarifictorus aspersus aspersus (Walker, 1869) was found together with the new species in the same locality, representing a new locality record for V. aspersus in Brunei. We used MaxEnt modelling to test if it was likely that this species occurs in Ulu Temburong and Borneo based on a set of bioclimatic predictors. While MaxEnt modelling showed that V. aspersus can occur in Borneo, it did not convincingly predict its occurrence in Ulu Temburong where it was found. Based on the model, maximum temperature of warmest month, minimum temperature of coldest month and annual precipitation are important bioclimatic variables to predict the distribution.

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Blank, Lior, Miska Luoto, and Juha Merilä. "Potential effects of climate change on the distribution of the common frog Rana temporaria at its northern range margin." Israel Journal of Ecology and Evolution 59, no. 3 (2013): 130–40. http://dx.doi.org/10.1080/15659801.2014.888825.

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Climate change is projected to be particularly strong in northern latitudes, and subarctic species are thus likely to be especially susceptible to the effects of climate warming. We forecast potential effects of climate change on the extent of the suitable habitat of the common frog,Rana temporaria,at the margin of its northern range. We investigated 179 potential breeding sites in subarctic Finland and subjected the data to detailed bioclimate envelope modelling using three state-of-the-art techniques: generalized additive models, maximum entropy and generalized boosting methods. Moreover, we included local environmental factors in the models to investigate whether they improve model performance. Under all tested climate change projections and irrespective of the modelling method, the suitable habitat forR. temporariaincreased in warming climate. The inclusion of local abiotic variables significantly improved the performance of the models. However, June temperature appeared to be the most informative variable in all modelling approaches: a major increase in the extent of suitable habitat occurred when it increased by 1°C. Overall, the modelling results indicate that the distribution of northernR. temporariais likely to be very sensitive to climate warming. The results also highlight the fact that overlooking local abiotic variation can significantly bias bioclimatic modelling results.

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Wang, H., I. C. Prentice, and J. Ni. "Data-based modelling and environmental sensitivity of vegetation in China." Biogeosciences 10, no. 9 (2013): 5817–30. http://dx.doi.org/10.5194/bg-10-5817-2013.

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Abstract. A process-oriented niche specification (PONS) model was constructed to quantify climatic controls on the distribution of ecosystems, based on the vegetation map of China. PONS uses general hypotheses about bioclimatic controls to provide a "bridge" between statistical niche models and more complex process-based models. Canonical correspondence analysis provided an overview of relationships between the abundances of 55 plant communities in 0.1° grid cells and associated mean values of 20 predictor variables. Of these, GDD0 (accumulated degree days above 0 °C), Cramer–Prentice α (an estimate of the ratio of actual to equilibrium evapotranspiration) and mGDD5 (mean temperature during the period above 5 °C) showed the greatest predictive power. These three variables were used to develop generalized linear models for the probability of occurrence of 16 vegetation classes, aggregated from the original 55 types by k-means clustering according to bioclimatic similarity. Each class was hypothesized to possess a unimodal relationship to each bioclimate variable, independently of the other variables. A simple calibration was used to generate vegetation maps from the predicted probabilities of the classes. Modelled and observed vegetation maps showed good to excellent agreement (κ = 0.745). A sensitivity study examined modelled responses of vegetation distribution to spatially uniform changes in temperature, precipitation and [CO2], the latter included via an offset to α (based on an independent, data-based light use efficiency model for forest net primary production). Warming shifted the boundaries of most vegetation classes northward and westward while temperate steppe and desert replaced alpine tundra and steppe in the southeast of the Tibetan Plateau. Increased precipitation expanded mesic vegetation at the expense of xeric vegetation. The effect of [CO2] doubling was roughly equivalent to increasing precipitation by ~ 30%, favouring woody vegetation types, particularly in northern China. Agricultural zones in northern China responded most strongly to warming, but also benefited from increases in precipitation and [CO2]. These results broadly conform to previously published findings made with the process-based model BIOME4, but they add regional detail and realism and extend the earlier results to include cropping systems. They provide a potential basis for a broad-scale assessment of global change impacts on natural and managed ecosystems.

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Wang, H., I. C. Prentice, and J. Ni. "Data-based modelling and environmental sensitivity of vegetation in China." Biogeosciences Discussions 10, no. 1 (2013): 49–81. http://dx.doi.org/10.5194/bgd-10-49-2013.

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Abstract. A process-oriented niche specification (PONS) model was constructed to quantify climatic controls on the distribution of ecosystems, based on the vegetation map of China. PONS uses general hypotheses about bioclimatic controls to provide a "bridge" between statistical niche models and more complex process-based models. Canonical correspondence analysis provided an overview of relationships between the abundances of 55 plant communities in 0.1° grid cells and associated mean values of 20 predictor variables. Of these, GDD (accumulated degree days above 0 °C) Cramer–Prentice α (an estimate of the ratio of actual to equilibrium evapotranspiration) and mGDD5 (mean temperature during the period above 5 °C) showed the greatest predictive power. These three variables were used to develop generalized linear models for the probability of occurrence of 16 vegetation classes, aggregated from the original 55 types by k-means clustering according to bioclimatic similarity. Each class was hypothesized to possess a unimodal relationship to each bioclimate variable, independently of the other variables. A simple calibration was used to generate vegetation maps from the predicted probabilities of the classes. Modelled and observed vegetation maps showed good to excellent agreement (κ = 0.745). A sensitivity study examined modelled responses of vegetation distribution to spatially uniform changes in temperature, precipitation and [CO2], the latter included via an offset to α (based on an independent, data-based light use efficiency model for forest net primary production). Warming shifted the boundaries of most vegetation classes northward and westward while temperate steppe and desert replaced alpine tundra and steppe in the southeast of the Tibetan Plateau. Increased precipitation expanded mesic vegetation at the expense of xeric vegetation. The effect of [CO2] doubling was roughly equivalent to increasing precipitation by ∼ 30%, favouring woody vegetation types, particularly in northern China. Agricultural zones in northern China responded most strongly to warming, but also benefited from increases in precipitation and [CO2]. These results broadly conform to previously published findings made with the process-based model BIOME4, but they add regional detail and realism and extend the earlier results to include cropping systems. They provide a potential basis for a broad-scale assessment of global change impacts on natural and managed ecosystems.

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Ellis, Christopher. "Climate Change, Bioclimatic Models and the Risk to Lichen Diversity." Diversity 11, no. 4 (2019): 54. http://dx.doi.org/10.3390/d11040054.

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This paper provides an overview of bioclimatic models applied to lichen species, supporting their potential use in this context as indicators of climate change risk. First, it provides a brief summary of climate change risk, pointing to the relevance of lichens as a topic area. Second, it reviews the past use of lichen bioclimatic models, applied for a range of purposes with respect to baseline climate, and the application of data sources, statistical methods, model extents and resolution and choice of predictor variables. Third, it explores additional challenges to the use of lichen bioclimatic models, including: 1. The assumption of climatically controlled lichen distributions, 2. The projection to climate change scenarios, and 3. The issue of nonanalogue climates and model transferability. Fourth, the paper provides a reminder that bioclimatic models estimate change in the extent or range of a species suitable climate space, and that an outcome will be determined by vulnerability responses, including potential for migration, adaptation, and acclimation, within the context of landscape habitat quality. The degree of exposure to climate change, estimated using bioclimatic models, can help to inform an understanding of whether vulnerability responses are sufficient for species resilience. Fifth, the paper draws conclusions based on its overview, highlighting the relevance of bioclimatic models to conservation, support received from observational data, and pointing the way towards mechanistic approaches that align with field-scale climate change experiments.

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Olsson, Cecilia, Kjell Bolmgren, Johan Lindström, and Anna Maria Jönsson. "Performance of tree phenology models along a bioclimatic gradient in Sweden." Ecological Modelling 266 (September 2013): 103–17. http://dx.doi.org/10.1016/j.ecolmodel.2013.06.026.

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Datta, Arunava, Oliver Schweiger, and Ingolf Kühn. "Origin of climatic data can determine the transferability of species distribution models." NeoBiota 59 (July 28, 2020): 61–76. http://dx.doi.org/10.3897/neobiota.59.36299.

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Methodological research on species distribution modelling (SDM) has so far largely focused on the choice of appropriate modelling algorithms and variable selection approaches, but the consequences of choosing amongst different sources of environmental data has scarcely been investigated. Bioclimatic variables are commonly used as predictors in SDMs. Currently, several online databases offer the same sets of bioclimatic variables, but they differ in underlying source of raw data and method of data processing (extrapolation and downscaling). In this paper, we asked whether predictive performance and spatial transferability of SDMs are affected by the choice of two different bioclimatic databases viz. WorldClim 2 and Chelsa 1.2. We used presence-absence data of the invasive plant Ageratina adenophora from the Western Himalaya for training SDMs and a set of independently-collected presence-only datasets from the Central and Eastern Himalaya to evaluate the transferability of the SDMs beyond the training range. We found that the performance of SDMs was, to a large degree, affected by the choice of the climatic dataset. Models calibrated on Chelsa 1.2 outperformed WorldClim 2 in terms of internal evaluation on the calibration dataset. However, when the model was transferred beyond the calibration range to the Central and Eastern Himalaya, models based on WorldClim 2 performed substantially better. We recommend that, in addition to the choice of predictor variables, the choice of predictor datasets with these variables should not be based merely on subjective decision whenever several options are available. Instead, such decisions should be based on robust evaluation of the most appropriate dataset for a given geographic region and species being modelled. Moreover, decisions could also depend on the objective of the study, i.e. projecting within the calibration range or beyond. Therefore, a quantitative evaluation of predictor datasets from alternative sources should be routinely performed as an integral part of the modelling procedure.

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Marino, Jorgelina, Magdalena Bennett, Daniel Cossios, et al. "Bioclimatic constraints to Andean cat distribution: a modelling application for rare species." Diversity and Distributions 17, no. 2 (2011): 311–22. http://dx.doi.org/10.1111/j.1472-4642.2011.00744.x.

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Bourgeois, Gaétan, Alain Bourque, and Gaétan Deaudelin. "Modelling the impact of climate change on disease incidence: a bioclimatic challenge." Canadian Journal of Plant Pathology 26, no. 3 (2004): 284–90. http://dx.doi.org/10.1080/07060660409507145.

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Kabaš, Eva, Vera Batanjski, Vera Batanjski, et al. "Towards Detecting Bioclimatic Niche - Species Distribution Modelling in Four Maple Species (Acer Spp.)." Acta Botanica Croatica 73, no. 2 (2014): 401–17. http://dx.doi.org/10.2478/botcro-2014-0007.

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Abstract The aim of this paper was firstly to describe the ecological and geographical differentiation of the four maple species (Acer spp.) in Serbia and Kosovo based on floristic and phytocoenological data, and secondly, to model their distributions in order to predict which areas the species can be expected in. The intention was also to compare the resulting prediction maps with the available field records and see whether there are any differences between the actual and the predicted ranges. The data set included 1979 species records and each record was accompanied by geographic coordinates. The geographi-cal analysis was performed on the chorological data (latitude, longitude, altitude), while the ecological was based on vegetation data relating to the association, alliance, order and class as well as on 19 bioclimatic parameters. The data set was georeferenced using GIS tools. The results demonstrated that the distribution patterns of all the analyzed species are mostly affected by the limiting effects of the variables related to precipitation and temperature of the dry and also the warm period. Their synergic limiting effects are the most important force shaping distribution patterns within a territory. These findings highlight the importance of defining bioclimatic profiles of species using different techniques of distribution modelling.

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Kargapolova, Nina A., and Vasily A. Ogorodnikov. "Numerical stochastic modelling of spatial and spatio-temporal fields of the wind chill index in the South of Western Siberia." Russian Journal of Numerical Analysis and Mathematical Modelling 36, no. 1 (2021): 33–42. http://dx.doi.org/10.1515/rnam-2021-0003.

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Abstract The paper presents the results of comparison of various methods of spatial interpolation of the wind chill index in two regions located in the South of Western Siberia (Russia). It is shown that stochastic interpolation provides the least interpolation error in the considered regions. The results of modelling the spatial and spatio-temporal fields of the considered bioclimatic index on a regular grid are presented.

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McKenney, D. W., J. H. Pedlar, K. Lawrence, P. Papadopol, and K. Campbell. "HARDINESS ZONES AND BIOCLIMATIC MODELLING OF PLANT SPECIES DISTRIBUTIONS IN NORTH AMERICA©." Acta Horticulturae, no. 1085 (June 2015): 139–48. http://dx.doi.org/10.17660/actahortic.2015.1085.24.

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Xu, Tingbao, and Michael F. Hutchinson. "New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package." Environmental Modelling & Software 40 (February 2013): 267–79. http://dx.doi.org/10.1016/j.envsoft.2012.10.003.

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Waltari, Eric, Ronny Schroeder, Kyle McDonald, Robert P. Anderson, and Ana Carnaval. "Bioclimatic variables derived from remote sensing: assessment and application for species distribution modelling." Methods in Ecology and Evolution 5, no. 10 (2014): 1033–42. http://dx.doi.org/10.1111/2041-210x.12264.

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Kriticos, Darren J., Bruce L. Webber, Agathe Leriche, et al. "CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling." Methods in Ecology and Evolution 3, no. 1 (2011): 53–64. http://dx.doi.org/10.1111/j.2041-210x.2011.00134.x.

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Głogowski, Arkadiusz, Paolo Perona, Krystyna Bryś, and Tadeusz Bryś. "Nonlinear reconstruction of bioclimatic outdoor-environment dynamics for the Lower Silesia region (SW Poland)." International Journal of Biometeorology 65, no. 7 (2021): 1189–203. http://dx.doi.org/10.1007/s00484-021-02101-4.

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AbstractMeasured meteorological time series are frequently used to obtain information about climate dynamics. We use time series analysis and nonlinear system identification methods in order to assess outdoor-environment bioclimatic conditions starting from the analysis of long historical meteorological data records. We investigate and model the stochastic and deterministic properties of 117 years (1891–2007) of monthly measurements of air temperature, precipitation and sunshine duration by separating their slow and fast components of the dynamics. In particular, we reconstruct the trend behaviour at long terms by modelling its dynamics via a phase space dynamical systems approach. The long-term reconstruction method reveals that an underlying dynamical system would drive the trend behaviour of the meteorological variables and in turn of the calculated Universal Thermal Climatic Index (UTCI), as representative of bioclimatic conditions. At longer terms, the system would slowly be attracted to a limit cycle characterized by 50–60 years cycle fluctuations that is reminiscent of the Atlantic Multidecadal Oscillation (AMO). Because of lack of information about long historical wind speed data we performed a sensitivity analysis of the UTCI to three constant wind speed scenarios (i.e. 0.5, 1 and 5 m/s). This methodology may be transferred to model bioclimatic conditions of nearby regions lacking of measured data but experiencing similar climatic conditions.

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Pinkard, E. A., D. J. Kriticos, T. J. Wardlaw, A. J. Carnegie, and Agathe Leriche. "Estimating the spatio-temporal risk of disease epidemics using a bioclimatic niche model." Ecological Modelling 221, no. 23 (2010): 2828–38. http://dx.doi.org/10.1016/j.ecolmodel.2010.08.017.

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Peakall, Rod, Lauren Jones, Colin C. Bower, and Brendan G. Mackey. "Bioclimatic assessment of the geographic and climatic limits to hybridisation in a sexually deceptive orchid system." Australian Journal of Botany 50, no. 1 (2002): 21. http://dx.doi.org/10.1071/bt01021.

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Australia is a major centre of diversity for pollination by sexual deception, a pollination syndrome unique to orchids and characterised by highly specific pollinator relationships. Chiloglottis pescottiana is a rare natural hybrid between sexually deceptive C. trapeziformis and C. valida. We utilised bioclimatic models to predict the potential range of the parental orchid species, the hybrid and their pollinators. The predicted ranges of the parental orchid species rarely overlapped (only 2&percnt; of the core range), with the geographic separation of the species reflecting the occupation of largely distinct climatic niches and limiting opportunities for hybridisation. Comparison of the predictions with independent distributions of the orchid taxa revealed a close match. Unexpectedly, our results revealed that several related and morphologically similar orchid species are, nevertheless, ecologically distinct from C. valida. Our study demonstrates that bioclimatic modelling provides an additional tool for exploring a range of ecological and evolutionary questions.

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de Freitas, C. R., and L. V. Symon. "A bioclimatic index of human survival times in the Antarctic." Polar Record 23, no. 147 (1987): 651–59. http://dx.doi.org/10.1017/s0032247400008354.

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AbstractAn index of human ‘survival time outdoors in extreme cold’ (STOEC) has been developed, using body-atmosphere energy budget modelling procedures. The index, which is applicable in places like Antarctica where only limited climatological data are available, is based on the calculated rate of fall of core temperature from 37°C to 27°C of a standard inactive healthy subject in full polar clothing.Applied to data from 12 Antarctic stations it indicates relative severity of their mean and extreme climatic conditions. The severest winter conditions become lifethreatening after only about 20 minutes. At most stations in winter, exposure outdoors for more than two hours would be dangerous. Conditions at all coastal stations in summer are mildenough to allow a normal core temperature to be maintained. The index has many applications, for example estimating likely survival times of immobilized accident victims and guidelines for duration of work periods outside.

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Crowther, M. S. "Distributions of species of the Antechinus stuartii-A. flavipes complex as predicted by bioclimatic modelling." Australian Journal of Zoology 50, no. 1 (2002): 77. http://dx.doi.org/10.1071/zo01031.

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Previous work on bioclimatic mapping of species within the Antechinus stuartii–A. flavipes complex has been carried out, but this was before A. subtropicus was recognised and a complete taxonomic revision of the complex had been completed. This revised study of bioclimatic modelling of species within the A. stuartii–A. flavipes complex indicates substantial differences between the four species (A. stuartii, A. agilis, A. subtropicus and A. flavipes) in 35 climatic indices. A. stuartii is predicted to have a near-coastal distribution in northern and central New South Wales stretching as far south as Kioloa and as far north as south-eastern Queensland, avoiding the far coastal strip. A. agilis is predicted to have an extensive distribution in Victoria and southern New South Wales as far north as western Sydney; it is also predicted to occur in Tasmania, even though there is no evidence of it ever occurring there. A. flavipes is predicted to have an extensive inland and coastal distribution much larger than its recorded distribution. A. subtropicus is predicted to have a very narrow distribution in areas with high seasonal rainfall and high temperatures with low seasonality. All species are predicted to occur sympatrically, with A. stuartii and A. agilis predicted to have extensive overlap on the coast near Kioloa and to the immediate west and south-west of Sydney.

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Amiri, Mohadeseh, Mostafa Tarkesh, Reza Jafari, and Gottfried Jetschke. "Bioclimatic variables from precipitation and temperature records vs. remote sensing-based bioclimatic variables: Which side can perform better in species distribution modeling?" Ecological Informatics 57 (May 2020): 101060. http://dx.doi.org/10.1016/j.ecoinf.2020.101060.

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Číhal, Lukáš, and Oto Kaláb. "Species distribution models for critically endangered liverworts (Bryophyta) from the Czech Republic: a guide to future survey expeditions." Acta Musei Silesiae, Scientiae Naturales 66, no. 2 (2017): 101–10. http://dx.doi.org/10.1515/cszma-2017-0011.

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Abstract Using 35 presence-only data samples and five uncorrelated bioclimatic variables, we made species distribution models (SDMs) for 4 species of critically endangered (CR) liverworts from genus Jungermanniales and Marchantiales (Cephaloziella elegans, Leiocolea heterocolpos, Lophozia wenzelii and Riccia papillosa) using the maximum entropy modelling method (MaxEnt). Since we were modelling CR species, only one model proved to be strong enough to be used in the field. However, SDMs can serve as effective and fast tools for acceleration of the discovery of the rare and endangered species. The final model presented in this study can serve as a guide to future survey expeditions, the conservation of the target species and also to help understand their ecology.

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Kulloli, R. N., and S. Kumar. "Comparison of Bioclimatic, NDVI and Elevation variables in assessing extent of Commiphora wightii (Arnt.) Bhand." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 589–95. http://dx.doi.org/10.5194/isprsarchives-xl-8-589-2014.

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Commiphora wightii (Arnt.) Bhand., is an important medicinal plant of Indian Medicine System (IMS) since ancient time. It is used in different ailments of obesity, arthritis, rheumatism and high cholesterol. Due to overexploitation its natural populations declined to large extent. IUCN has put it under Data Deficient (DD) category due to lack of data on its extent of occurrence in nature. Hence, the study was carried out using MaxEnt distribution modelling algorithm to estimate its geographic distribution and to identify potential habitats for its reintroduction. For modelling employed 68 presence locality data, 19 bioclimatic variables, Normalize Difference Vegetation Index (NDVI) and elevation data. These were tested for multicollinearity and those variables having r-value less than 0.8 were selected for further analysis, which was carried out in two ways i) Bioclimatic variables and elevation; ii) NDVI and elevation. Area Under the Curve (AUC) in both analysis was above 0.9 for all variables, indicating very high accuracy of prediction. Variables governing distribution of C. wightii in the analysis using bioclimatic and elevation data set are precipitation seasonality (56.6 %), annual precipitation (16.4 %) and elevation (14.7 %). Extent of occurrence of C.wightii predicted by model closely matched in the districts of Jaisalmer and Barmer. In the second analysis elevation (48.3 %), NDVI of June (11.1 %) and August (11.2 %) contributed for NDVI and Elevation data set. NDVI of June corresponds to its leafing phase while NDVI of August to flowering phase. Area of its occurrence predicted for NDVI and elevation data set are Bikaner, Churu, Jhunjhunun some part of Jodhpur which are completely sandy, where C. wightii is totally absent. Extent of occurrence was also validated in ground survey. Potential areas for its reintroduction were identified as Jaisalmer and Barmer districts in Indian arid zone.

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Chemura, Abel, Dumisani Kutywayo, Pardon Chidoko, and Caleb Mahoya. "Bioclimatic modelling of current and projected climatic suitability of coffee (Coffea arabica) production in Zimbabwe." Regional Environmental Change 16, no. 2 (2015): 473–85. http://dx.doi.org/10.1007/s10113-015-0762-9.

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Berry, P. M., T. P. Dawson, P. A. Harrison, and R. G. Pearson. "Modelling potential impacts of climate change on the bioclimatic envelope of species in Britain and Ireland." Global Ecology and Biogeography 11, no. 6 (2002): 453–62. http://dx.doi.org/10.1111/j.1466-8238.2002.00304.x.

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Tytar, V. M., I. I. Kozinenko, and S. V. Mezhzherin. "Modelling the Bioclimatic Niche and Distribution of the Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), in Ukraine." Vestnik Zoologii 53, no. 6 (2019): 471–82. http://dx.doi.org/10.2478/vzoo-2019-0042.

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Abstract The Steppe mouse, Mus spicilegus, is endemic to Europe and found to be expanding its home range in recent years. In Ukraine there are indications a north- and eastwards expansion and/or reestablishment of M. spicilegus. We suggest that climatic conditions may be the primary factors that foster or limit the range expansion of M. spicilegus in Eastern Europe. Our objective was to complement the knowledge about the distribution of the species with an estimation of the potential distribution of the species in Ukraine using known occurrence sites (in Ukraine and neighbouring areas) and environmental variables in an ecological niche modelling algorithm. After accounting for sampling bias and spatial autocorrelation, we retained 73 occurrence records. The algorithm used in this paper, Maxent (Phillips et al., 2006), is a machine learning algorithm and only needs presence data, besides the environmental layers. Using this approach, we have highlighted the importance and significance of a number of bioclimatic variables, particularly those characterizing wintering conditions, under which higher mean temperatures enhance habitat suitability, whereas increased precipitation leads to an opposite effect. The broadly northwards shift of the home range of the species in Ukraine could generally be due to the increasing (since the 1980s) mean temperature of the winter season. We expect this expansion process will continue together with the changing climate and new records of locations of the species may be used for monitoring such change.

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CARLSEN, Tor, Mika BENDIKSBY, Tom H. HOFTON, et al. "Species delimitation, bioclimatic range, and conservation status of the threatened lichen Fuscopannaria confusa." Lichenologist 44, no. 5 (2012): 565–75. http://dx.doi.org/10.1017/s0024282912000199.

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AbstractFuscopannaria confusa is a rare lichen restricted to very humid localities in boreal forests. Two Fuscopannaria species, F. ahlneri and F. mediterranea, and Parmeliella parvula are morphologically problematic to distinguish from F. confusa. Our aim with the present study was to evaluate the taxonomic status of F. confusa and thereby clarify its conservation status in Norway. By phylogenetic analysis of multi-locus DNA sequences, we show that F. confusa is genetically well distinguished from F. ahlneri,F. mediterranea, and P. parvula. Fuscopannaria confusa should therefore be treated as a separate species. A species distribution modelling analysis indicates that F. confusa has a slightly continental but potentially wide geographic distribution in Norway. However, suitable localities are continuously being destroyed by clear-cut logging and hydroelectric power development. Because of the decline in suitable habitats, F. confusa should be regarded as highly threatened in Norway and listed as EN (endangered) at the national level.

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Morales‐Barbero, Jennifer, and Julia Vega‐Álvarez. "Input matters matter: Bioclimatic consistency to map more reliable species distribution models." Methods in Ecology and Evolution 10, no. 2 (2018): 212–24. http://dx.doi.org/10.1111/2041-210x.13124.

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Bede‐Fazekas, Ákos, and Imelda Somodi. "The way bioclimatic variables are calculated has impact on potential distribution models." Methods in Ecology and Evolution 11, no. 12 (2020): 1559–70. http://dx.doi.org/10.1111/2041-210x.13488.

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Cheval, S., A. Dumitrescu, M. Adamescu, and C. Cazacu. "Identifying climate change hotspots relevant for ecosystems in Romania." Climate Research 80, no. 3 (2020): 165–73. http://dx.doi.org/10.3354/cr01603.

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Studies regarding species distribution, resilience and adaptability of different ecosystems as well as the response of human society are linked with our ability to identify past and predict future changes. Climate change, together with other changes like land use, land cover and invasive alien species, are important to establish the background for further modelling approaches (e.g. species modelling, ecosystem resilience, etc.). We used high-quality and homogeneous air temperature and precipitation data sets for Romania in order to detect climate change hotspots. The changes were quantified considering 2 periods: 1961-1986 (reference) and 1987-2013 (current conditions). Bioclimatic variables were used to identify the climate change hotspots relevant for different decision makers. The identification of areas affected by significant changes may support the development of mitigation plans for enhancing the resilience and adaptive capacity of socio-economical systems to future impacts.

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Kennedy, Blair E., Douglas J. King, and Jason Duffe. "Comparison of Empirical and Physical Modelling for Estimation of Biochemical and Biophysical Vegetation Properties: Field Scale Analysis across an Arctic Bioclimatic Gradient." Remote Sensing 12, no. 18 (2020): 3073. http://dx.doi.org/10.3390/rs12183073.

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To evaluate the potential of multi-angle hyperspectral sensors for monitoring vegetation variables in Arctic environments, empirical and physical modelling using field data was implemented for the retrieval of leaf and canopy chlorophyll content (LCC, CCC) and plant area index (PAI) measured at four sites situated across a bioclimatic gradient in the Western Canadian Arctic. Field reflectance data were acquired with an ASD FieldSpec (305–1075 nm) and used to simulate CHRIS Mode1 spectra (411–997 nm). Multi-angle measurements were taken corresponding to CHRIS view zenith angles (VZA) (−55°, −36°, 0°, +36°, +55°). Empirical modelling compared parametric regression based on vegetation indices (VIs) to non-parametric Gaussian Processes Regression (GPR). In physical modelling, PROSAIL was inverted using numerical optimization and look-up table (LUT) approaches. Cross-validation of the empirical models ranked GPR as best, followed by simple ratio (SR) with optimally selected NIR and red wavelengths, and then ROSAVI using its published wavelengths (mean r2cv = 0.62, 0.58, and 0.54, respectively across all sites, variables, and VZAs). However, the best predictive performance was achieved by SR followed by GPR and ROSAVI (NRMSEcv = 0.12, 0.16, 0.16, respectively). PROSAIL simulated the multi-angle top-of-canopy reflectance well with numerical optimization (r2 = ~0.99, RMSE = 0.004 ± 0.002), but best performing LUT models of LCC, CCC and PAI were poorer than the empirical approaches (mean r2 = 0.48, mean NRMSE = 0.22). PROSAIL performed best at the high Arctic sparsely vegetated site (r2 = 0.57–0.86 for all parameters). Overall, the best performing VZA was −55° for empirical modelling and 0° and ±55° for physical modelling; however, these were not significantly better than the other VZAs. Overall, this study demonstrates that, for Arctic vegetation, nadir narrowband reflectance data used to derive simple empirical VIs with optimally selected bands is a more efficient approach for modelling chlorophyll and PAI than more complex empirical and physical approaches.

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BINDER, Mark D., and Christopher J. ELLIS. "Conservation of the rare British lichen Vulpicida pinastri: changing climate, habitat loss and strategies for mitigation." Lichenologist 40, no. 1 (2008): 63–79. http://dx.doi.org/10.1017/s0024282908007275.

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Abstract:Autecological information targeted towards rare and threatened lichen species is severely lacking. This study adopts the rare British lichen Vulpicida pinastri as a case study species and examines its ecological response to emerging threats: climate change and the recurrent loss of its primary habitat (juniper scrub). We used predictive niche modelling to examine the response of V. pinastri to a range of present-day climatic variables. A successful model was projected for a period during the 2050s based on IPCC climate change scenarios (UKCIP02 data), and threat was estimated as the proportional change in bioclimatic space. To estimate the potential range now and during the 2050s, projected bioclimatic space was masked by a habitat map equivalent to (i) the present-day distribution of juniper and (ii) theoretical juniper distribution based on existing rates of decline. Our results point to potential range loss of V. pinastri with climate warming, exacerbated by the recurrent decline in juniper habitat. This predictive modelling approach was complemented by an assessment of local stand-scale effects. At four sites in north-east Scotland we examined the occurrence and abundance of V. pinastri thalli, in response to juniper spatial distribution, and the life-stage and structure of individual shrubs. Vulpicida pinastri appeared to be dispersal limited at small-scales, and was significantly more abundant on old and degenerate juniper shrubs. Our results evidence a close relationship between management for habitat quality and effective lichen conservation. Effective conservation of V. pinastri must ensure cohorts of older and degenerate juniper shrubs are maintained at sites where the species is expected to be most resistant to long-term climate warming, i.e. in the uplands of north-east Scotland.

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Chatzinikolaou, E., C. Chalkias, and E. Dimopoulou. "URBAN MICROCLIMATE IMPROVEMENT USING ENVI-MET CLIMATE MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 69–76. http://dx.doi.org/10.5194/isprs-archives-xlii-4-69-2018.

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Abstract. The aim of this paper is the modelling of urban microclimate, based on the limits imposed by the complexity of the three-dimensional space of cities. To this purpose, different Bioclimatic Scenarios were investigated through the microclimatic simulations using the micro-scale numerical model, ENVI-met 4v, applied in a case study of a Block in a highly residential neighbourhood of Athens. The study compares the bioclimatic scenarios of the roof top and road side vegetation plan in the current conditions, in order to evaluate how the existence of vegetation can affect the local air temperature and the thermal comfort condition of urban environment. This study also highlights the need to manage those microclimate data, through a geodatabase and provides a GIS approach of data organization and visualization. Creating building facades of the distributed temperature has showed that urban morphology parameters have an obvious impact on temperature distribution in the 3D space. On the other hand, the proposed roadside vegetation scenario has proved to be the most suitable way to improve the thermal comfort conditions of urban environment, as it can eliminate the Urban Heat Island (UHI) effects.

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Żurek, G., B. Wiewióra, and D. Gozdowski. "Relations between bioclimatic variables and endophyte colonization of grasses in Poland." Fungal Ecology 6, no. 6 (2013): 554–56. http://dx.doi.org/10.1016/j.funeco.2013.09.001.

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Støa, Bente, Rune Halvorsen, Sabrina Mazzoni, and Vladimir I. Gusarov. "Sampling bias in presence-only data used for species distribution modelling: theory and methods for detecting sample bias and its effects on models." Sommerfeltia 38, no. 1 (2018): 1–53. http://dx.doi.org/10.2478/som-2018-0001.

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Abstract This paper provides a theoretical understanding of sampling bias in presence-only data in the context of species distribution modelling. This understanding forms the basis for two integrated frameworks, one for detecting sampling bias of different kinds in presence-only data (the bias assessment framework) and one for assessing potential effects of sampling bias on species distribution models (the bias effects framework). We exemplify the use of these frameworks to museum data for nine insect species in Norway, for which the distribution along the two main bioclimatic gradients (related to oceanicity and temperatures) are modelled using the MaxEnt method. Models of different complexity (achieved by use of two different model selection procedures that represent spatial prediction or ecological response modelling purposes, respectively) were generated with different types of background data (uninformed and background-target-group [BTG]). The bias assessment framework made use of comparisons between observed and theoretical frequency-of-presence (FoP) curves, obtained separately for each combination of species and bioclimatic predictor, to identify potential sampling bias. The bias effects framework made use of comparisons between modelled response curves (predicted relative FoP curves) and the corresponding observed FoP curves for each combination of species and predictor. The extent to which the observed FoP curves deviated from the expected, smooth and unimodal theoretical FoP curve, varied considerably among the nine insect species. Among-curve differences were, in most cases, interpreted as indications of sampling bias. Using BTG-type background data in many cases introduced strong sampling bias. The predicted relative FoP curves from MaxEnt were, in general, similar to the corresponding observed FoP curves. This indicates that the main structure of the data-sets were adequately summarised by the MaxEnt models (with the options and settings used), in turn suggesting that shortcomings of input data such as sampling bias or omission of important predictors may overshadow the effect of modelling method on the predictive performance of distribution models. The examples indicate that the two proposed frameworks are useful for identification of sampling bias in presence-only data and for choosing settings for distribution modelling options such as the method for extraction of background data points and determining the appropriate level of model complexity.

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Ramachandran, Vivek, Mukta Joshi, Mayuresh Ambekar, Samina Amin Charoo, and Uma Ramakrishnan. "The desert hamster Phodopus roborovskii (Satunin, 1903) (Rodentia, Cricetidae) from north-western Tibetan plateau, Ladakh, India: an addition to the mammalian fauna of the Indian subcontinent." Mammalia 84, no. 3 (2020): 253–58. http://dx.doi.org/10.1515/mammalia-2018-0199.

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AbstractDuring a systematic survey of the small mammals in the relatively unexplored north-western regions of the Tibetan plateau in India, we captured and identified the desert hamster Phodopus roborovskii using molecular phylogenetic methods. We also provide revised distributional estimates for this species using niche modelling (Maxent and 19 bioclimatic variables), taking into account sampling bias. We evaluated suitable habitats for the species, identifying regions in the Trans-Himalayas that may harbour this species. This study improves the knowledge of the desert hamster’s range and is a new record and an addition to the Indian sub-continental mammalian fauna, ~750 km southward extension from its known range.

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Usmadi, Didi, Sutomo Sutomo, Rajif Iryadi, Siti Fatimah Hanum, I. Dewa Putu Darma, and I. Putu Agus Hendra Wibawa. "Predicting Species Distribution for True Indigo (Indigofera tinctoria L.) in Citarum Watershed, West Java, Indonesia." Journal of Tropical Biodiversity and Biotechnology 6, no. 3 (2021): 65398. http://dx.doi.org/10.22146/jtbb.65398.

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Citarum watershed is a region of approximately 6,610 km2 in West Java, Indonesia. Citarum watershed has been degraded through historical land use and vegetation clearing. Rehabilitation of Citarum watershed uses Indigofera tinctoria L. that has value as a source of natural blue dye and is considered suitable for the region. Species distribution modelling and Habitat suitability index (SDM/HSI) were undertaken for I. tinctoria. The occurrence and environment data (bioclimatic, topography, and soil type) were input to HSI. Results of the Indigofera tinctoria habitat suitability model in Citarum watershed are very good (0.9–1) for some parts of the Citarum watershed. The medium and high suitability areas were respectively 4.49% and 4.37% of the area were located in the lowlands (Bekasi Regency and Karawang Regency). Prediction based on climate modelling for 2050 and 2070 estimated that the medium-high suitability area of Indigofera tinctoria will be reduced relative to the present.

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ZALUCKI, MYRON P., and MICHAEL J. FURLONG. "Forecasting Helicoverpa populations in Australia: A comparison of regression based models and a bioclimatic based modelling approach." Insect Science 12, no. 1 (2005): 45–56. http://dx.doi.org/10.1111/j.1672-9609.2005.00007.x.

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Lindenmayer, D. B., H. A. Nix, J. P. McMahon, M. F. Hutchinson, and M. T. Tanton. "The Conservation of Leadbeater's Possum, Gymnobelideus leadbeateri (McCoy): A Case Study of the Use of Bioclimatic Modelling." Journal of Biogeography 18, no. 4 (1991): 371. http://dx.doi.org/10.2307/2845479.

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Witkowski and Byron B. Lamont. "Resilience of two Banksia species to global change: Comparing results of bioclimatic modelling, demographic and translocation studies." International Journal of Biodiversity Science & Management 2, no. 2 (2006): 59–72. http://dx.doi.org/10.1080/17451590609618099.

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Journal articles on the topic 'Bioclimatic modelling'

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