Summary1. Gridded climatologies have become an indispensable component of bioclimatic modelling, with a range of applications spanning conservation and pest management. Such globally conformal data sets of historical and future scenario climate surfaces are required to model species potential ranges under current and future climate scenarios. 2. We developed a set of interpolated climate surfaces at 10¢ and 30¢ resolution for global land areas excluding Antarctica. Input data for the baseline climatology were gathered from the WorldClim and CRU CL1AE0 and CL2AE0 data sets. A set of future climate scenarios were generated at 10¢ resolution. For each of the historical and future scenario data sets, the full set of 35 Bioclim variables was generated. Climate variables (including relative humidity at 0900 and 1500 hours) were also generated in CLIMEX format. The Ko¨ppen-Geiger climate classification scheme was applied to the 10¢ hybrid climatology as a tool for visualizing climatic patterns and as an aid for specifying absence or background data for correlative modelling applications. 3. We tested the data set using a correlative model (MaxEnt) addressing conservation biology concerns for a rare Australian shrub, and a mechanistic niche model (CLIMEX) to map climate suitability for two invasive species. In all cases, the underlying climatology appeared to behave in a robust manner. 4. This global climate data set has the advantage over the WorldClim data set of including humidity data and an additional 16 Bioclim variables. Compared with the CRU CL2AE0 data set, the hybrid 10¢ data set includes improved precipitation estimates as well as projected climate for two global climate models running relevant greenhouse gas emission scenarios. 5. For many bioclimatic modelling purposes, there is an operational attraction to having a globally conformal historical climatology and future climate scenarios for the assessments of potential climate change impacts. Our data set is known as 'CliMond' and is available for free download from http://www.climond.org.
Aim Investigate the relative abilities of different bioclimatic models and data sets to project species ranges in novel environments utilizing the natural experiment in biogeography provided by Australian Acacia species.Location Australia, South Africa. MethodsWe built bioclimatic models for Acacia cyclops and Acacia pycnantha using two discriminatory correlative models (MaxEnt and Boosted Regression Trees) and a mechanistic niche model (CLIMEX). We fitted models using two training data sets: native-range data only ('restricted') and all available global data excluding South Africa ('full'). We compared the ability of these techniques to project suitable climate for independent records of the species in South Africa. In addition, we assessed the global potential distributions of the species to projected climate change.Results All model projections assessed against their training data, the South African data and globally were statistically significant. In South Africa and globally, the additional information contained in the full data set generally improved model sensitivity, but at the expense of increased modelled prevalence, particularly in extrapolation areas for the correlative models. All models projected some climatically suitable areas in South Africa not currently occupied by the species. At the global scale, widespread and biologically unrealistic projections by the correlative models were explained by open-ended response curves, a problem which was not always addressed by broader background climate space or by the extra information in the full data set. In contrast, the global projections for CLIMEX were more conservative. Projections into 2070 indicated a polewards shift in climate suitability and a decrease in model interpolation area.Main conclusions Our results highlight the importance of carefully interpreting model projections in novel climates, particularly for correlative models. Much work is required to ensure bioclimatic models performed in a robust and ecologically plausible manner in novel climates. We explore reasons for variations between models and suggest methods and techniques for future improvements.
Accepted ArticleThis article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/gcb.13492 This article is protected by copyright. All rights reserved. Accepted ArticleThis article is protected by copyright. All rights reserved. AbstractGlobally, Phytophthora cinnamomi is listed as one of the 100 worst invasive alien species and active management is required to reduce impact and prevent spread in both horticulture and natural ecosystems. Conversely, there are regions thought to be suitable for the pathogen where no disease is observed. We developed a CLIMEX model for the global distribution of P. cinnamomi based on the pathogen's response to temperature and moisture and by incorporating extensive empirical evidence on the presence and absence of the pathogen. The CLIMEX model captured areas of climatic suitability where P. cinnamomi occurs that is congruent with all available records. The model was validated by the collection of soil samples from asymptomatic vegetation in areas projected to be suitable by the model for which there were few records. DNA was extracted and the presence or absence of P. cinnamomi determined by high throughput sequencing (HTS). While not detected using traditional isolation methods, HTS detected P. cinnamomi at higher elevations in eastern Australia and central Tasmania as projected by the CLIMEX model. Further support for the CLIMEX model was obtained by using the large dataset from southwest Australia where the proportion of positive records in an area is related to the Ecoclimatic Index value for the same area. We provide for the first time a comprehensive global map of the current P. cinnamomi distribution, an improved CLIMEX model of the distribution, and a projection to 2080 of the distribution with predicted climate change. This information provides the basis for more detailed regional scale modelling and supports risk assessment for governments to plan management of this important soil-borne plant pathogen.
Helicoverpa armigera has recently invaded South and Central America, and appears to be spreading rapidly. We update a previously developed potential distribution model to highlight the global invasion threat, with emphasis on the risks to the United States. The continued range expansion of H. armigera in Central America is likely to change the invasion threat it poses to North America qualitatively, making natural dispersal from either the Caribbean islands or Mexico feasible. To characterise the threat posed by H. armigera, we collated the value of the major host crops in the United States growing within its modelled potential range, including that area where it could expand its range during favourable seasons. We found that the annual value of crops that would be exposed to H. armigera totalled approximately US$78 billion p.a., with US$843 million p.a. worth growing in climates that are optimal for the pest. Elsewhere, H. armigera has developed broad-spectrum pesticide resistance; meaning that if it invades the United States, protecting these crops from significant production impacts could be challenging. It may be cost-effective to undertake pre-emptive biosecurity activities such as slowing the spread of H. armigera throughout the Americas, improving the system for detecting H. armigera, and methods for rapid identification, especially distinguishing between H. armigera, H. zea and potential H. armigera x H. zea hybrids. Developing biological control programs, especially using inundative techniques with entomopathogens and parasitoids could slow the spread of H. armigera, and reduce selective pressure for pesticide resistance. The rapid spread of H. armigera through South America into Central America suggests that its spread into North America is a matter of time. The likely natural dispersal routes preclude aggressive incursion responses, emphasizing the value of preparatory communication with agricultural producers in areas suitable for invasion by H. armigera.
Summary1. The so-called BIOCLIM variables have played a central role in the advancement of ecologicalmodellingmethods for correlative species distribution modelling. 2. We propose to establish a register of the BIOCLIMvariables, allowing for the extension of the suite of described, readily available covariate data tosupport bioclimatic modelling. The registry will provide a simple means for researchers to add usefuldata sets in a transparent, documented manner. 3. As a case study, we introduce and describe the set offivemost significant principal components of the first 35 BIOCLIM variables (Bio01 to Bio35) and proposethey be assigned as Bio36 to Bio40.Together, these five PCA variables capture more than 90%of thevariability in the full suite of 35 BIOCLIM variables. 4. The PCA variables may provide a means to explore the climaticlimits of poorly known species, with a reduced risk of overfitting the models. The BIOCLIM variable registry should facilitate the expansion of the suite of variables commonly used in species distribution modelling.
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