University of Seville

About: University of Seville is a education organization based out in Seville, Andalucía, Spain. It is known for research contribution in the topics: Population & Context (language use). The organization has 20098 authors who have published 47317 publications receiving 947007 citations. The organization is also known as: Universidad de Sevilla.

Bioclimate envelope models: what they detect and what they hide: Correspondence

Abstract: INTRODUCTION In a recent issue of Global Ecology and Biogeo-graphy , Pearson & Dawson (2003) provided an informative review of the use of bioclimate envelope models (BEM) for predicting future distributional ranges of temperate plant species under expected global climate change. The authors discuss several criticisms of the BEM approach and they conclude that these need not be a major drawback when applied as a starting point for predicting the impacts of potential climate change on species ranges. Here, I argue that the strongly deterministic and reductionist BEM rely on biological assumptions that are much more commonly violated in nature than Pearson & Dawson (2003) assume. Moreover, the statistical methods currently used for model validation overestimate model fits as a result of pseudoreplication. Both features make BEM prone to produce artificially optimistic scenarios of future climate change impacts on plant distributions. Little doubt exists that climate determines the large-scale distributions of many temperate plant species (Woodward, 1987). However , ongoing range shifts are affected by a multitude of other constraints and processes acting on population performance (e.g. These differ greatly across species' ranges from their expanding to their eroding margins, and so also does the character of the respective populations (Lesica & Allendorf, 1995; Davis & Shaw, 2001). This will most probably result in geographically differential responses to changing environmental conditions , a point largely ignored by BEM approaches. In the following, I will comment on three major biological critiques of BEM that have been reviewed and downplayed by Pearson & Dawson (2003). BIOTIC INTERACTIONS BEM treat species as if they were acting independently of their biotic environment, thus neglecting potential effects of predation, competition or mutualisms on range dynamics. Pearson & Dawson (2003) argue accordingly that interactions between species may shape their spatial distributions on fine geographical scales, but are of minor importance at coarse scales, which are the main focus of BEM. However biotic interactions, not climate, are commonly considered the principal determinants of low-latitude range limits (Brown et al ., 1996). Moreover, ecological research on biological invasions (unintended 'large-scale experiments') has broadly documented that biotic interactions affect species' performance throughout their established ranges. The release of invaders from their specialist antagonists in invaded areas underpins improved performances as compared with populations within the original range, and thus constitutes a key factor promoting the invasion process (Keane & Crawley, 2002). Range dynamics themselves are likewise affected by biotic …

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

Abstract: This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.