Browsing by Author "Datta, Arunava"

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    Identifying safe cultivars of invasive plants : six questions for risk assessment, management, and communication
    (Pensoft, 2020-10-15) Datta, Arunava; Kumschick, Sabrina; Geerts, Sjirk; Wilson, John R. U.
    ENGLISH ABSTRACT: The regulation of biological invasions is often focussed at the species level. However, the risks posed by infra- and inter-specific entities can be significantly different from the risks posed by the corresponding species, to the extent that they should be regulated and managed differently. In particular, many ornamental plants have been the subject of long-term breeding and selection programmes, with an increasing focus on trying to develop cultivars and hybrids that are less invasive. In this paper, we frame the problem of determining the risk of invasion posed by cultivars or hybrids as a set of six questions that map on to the key components of a risk analysis, viz., risk identification, risk assessment, risk management, and risk communication. 1) Has an infra- or inter-specific entity been proposed as “safe to use” despite at least one of the corresponding species being a harmful invasive? 2) What are the trait differences between the proposed safe alternative and its corresponding invasive species? 3) Do the differences in traits translate into a difference in invasion risk that is significant for regulation? 4) Are the differences spatially and temporally stable? 5) Can the entities be distinguished from each other in practice? 6) What are the appropriate ways to communicate the risks and what can be done to manage them? For each question, we use examples to illustrate how they might be addressed focussing on plant cultivars that are purported to be safe due to sterility. We review the biological basis of sterility, methods used to generate sterile cultivars, and the methods available to confirm sterility. It is apparent that separating invasive genetic entities from less invasive, but closely related, genetic entities in a manner appropriate for regulation currently remains unfeasible in many circumstances – it is a difficult, expensive and potentially fruitless endeavour. Nonetheless, we strongly believe that an a priori assumption of risk should be inherited from the constituent taxa and the onus (and cost) of proof should be held by those who wish to benefit from infra- (or inter-) specific genetic entities. The six questions outlined here provide a general, science-based approach to distinguish closely-related taxa based on the invasion risks they pose.
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    Is invasion science moving towards agreed standards? The influence of selected frameworks
    (Pensoft, 2020-10-15) Wilson, John R. U.; Datta, Arunava; Hirsch, Heidi; Keet, Jan-Hendrik; Mbobo, Tumeka; Nkuna, Khensani V.; Nsikani, Mlungele M.; Pysek, Petr; Richardson, David M.; Zengeya, T. A.; Kumschick, Sabrina
    ENGLISH ABSTRACT: The need to understand and manage biological invasions has driven the development of frameworks to circumscribe, classify, and elucidate aspects of the phenomenon. But how influential have these frameworks really been? To test this, we evaluated the impact of a pathway classification framework, a framework focussing on the introduction-naturalisation-invasion continuum, and two papers that outline an impact classification framework. We analysed how these framework papers are cited and by whom, conducted a survey to determine why people have cited the frameworks, and explored the degree to which the frameworks are implemented. The four papers outlining these frameworks are amongst the most-cited in their respective journals, are highly regarded in the field, and are already seen as citation classics (although citations are overwhelmingly within the field of invasion science). The number of citations to the frameworks has increased over time, and, while a significant proportion of these are self-citations (20–40%), this rate is decreasing. The frameworks were cited by studies conducted and authored by researchers from across the world. However, relative to a previous citation analysis of invasion science as a whole, the frameworks are particularly used in Europe and South Africa and less so in North America. There is an increasing number of examples of uptake into invasion policy and management (e.g., the pathway classification framework has been adapted and adopted into EU legislation and CBD targets, and the impact classification framework has been adopted by the IUCN). However, we found that few of the citing papers (6–8%) specifically implemented or interrogated the frameworks; roughly half of all citations might be viewed as frivolous (“citation fluff”); there were several clear cases of erroneous citation; and some survey respondents felt that they have not been rigorously tested yet. Although our analyses suggest that invasion science is moving towards a more systematic and standardised approach to recording invasions and their impacts, it appears that the proposed standards are still not applied consistently. For this to be achieved, we argue that frameworks in invasion science need to be revised or adapted to particular contexts in response to the needs and experiences of users (e.g., so they are relevant to pathologists, plant ecologists, and practitioners), the standards should be easier to apply in practice (e.g., through the development of guidelines for management), and there should be incentives for their usage (e.g., recognition for completing an EICAT assessment).
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    Origin of climatic data can determine the transferability of species distribution models
    (Pensoft, 2020-07-28) Datta, Arunava; Schweiger, Oliver; Kuhn, Ingolf
    ENGLISH ABSTRACT: 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.