Flow variability and the ecology of large rivers

Puckridge, J. T.; Sheldon, Fran; Walker, Keith F.; Boulton, A. J.

doi:10.1071/mf94161

Cited by 599 publications

(509 citation statements)

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“…Prior to analysis, screening of raw data ensured a benchmark period of 20-years (1980 -1999) A total of 201 hydrological indices used in 15 previously published articles were used in our analysis (Hughes and James, 1989;Poff and Ward, 1989;Richards, 1989;Biggs, 1990; Jowett and Duncan, 1990; Poff, 1996;Richter et al, 1996;Clausen and Biggs, 1997;Richter et al, 1997;Puckridge et al, 1998;Richter et al, 1998;Clausen and Biggs, 2000;Wood et al, 2000;Wood et al, 2001). For brevity, Appendix 1 lists those variables identified by the PCA method and/or utilised in regression models in this paper (for full details of all candidate variables see Monk et al, 2006).…”

Section: Methodsmentioning

confidence: 99%

Selection of river flow indices for the assessment of hydroecological change

Monk

Wood

Hannah

et al. 2006

River Research & Apps

116

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• This is the pre-peer reviewed version of the article, which has been pub- Author for Correspondence:Wendy Monk, Canadian Rivers Institute, Department of Biology, Bag Service #45111, University of New Brunswick, Fredericton, New Brunswick, E3B 6E1, Canada. an 11-year macroinvertebrate community dataset (i.e. LIFE scores). The same 'best' models are produced using the PCA-based method and all 201 hydrological variables for two of the three river flow regime groups. However, weaker models are yielded by the PCA-based method for the remaining (flashy) river flow regime class and the whole data set (all 83 rivers). Thus, it is important to exercise caution when employing data reduction/ index redundancy approaches, as they may reject variables of ecological significance due to the assumption that the statistically dominant sources of hydrological variability are the principal drivers of, perhaps more subtle (sensitive), hydroecological associations.3 IntroductionThe ecological importance of river flow regime variability is increasingly well recognised (e.g., Clausen and Biggs, 1997;Wood and Armitage, 2004); and a wide range of potentially 'ecologically relevant' hydrological indices have been identified (e.g. Olden and Poff, 2003). However, such hydroecological analysis is limited by a general lack of paired longterm hydrological and ecological time-series (Wood et al., 2001; Jackson and Füreder, 2006). The search for 'ecologically relevant' hydrological indices has been driven by the need to quantify variability in ecological communities and/or individual populations that may be sensitive to natural hydrological changes or anthropogenic modifications (Richter et al., 1996). Some concerns have been raised regarding the large number of potential hydrological predictors available, since significant redundancy (multicollinearity) exists between many variables (Olden and Poff, 2003). Consequently, some guiding principles are required to aid researchers and water resource managers select the most 'ecologically relevant' hydrological variable(s).Olden and Poff (2003) proposed a method using principal components analysis (PCA) for assessing redundancy between hydrological variables and identifying those indices which account for most variation in river flow regimes using long-term flow records for 420 locations across the continental USA. They suggested that the variables identified by this method may form the basis of future hydroecological analysis. However, to date, their redundancy methodology and the resulting variables have not been widely tested in terms of ecological prediction.The aim of this short communication is to provide the first test of the PCA-based approach proposed by Olden and Poff (2003) in association with ecological data, and to compare its 4 effectiveness against regression models developed using 201 potentially 'ecologically relevant' hydrological variables identified in previous research. Data and methodsHydrological and ecological data were employed for 83 sites in England and Wales ( Figu...

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Section: Methodsmentioning

confidence: 99%

Selection of river flow indices for the assessment of hydroecological change

Monk

Wood

Hannah

et al. 2006

River Research & Apps

116

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“…Ecologically, water is the most limiting factor for plant growth in arid environments. The spatio-temporal dynamics of vegetation are, therefore, largely determined by available water [68][69][70][71][72][73]. Not surprisingly, biotic diversity is concentrated in riparian areas [74,75].…”

Section: Figurementioning

confidence: 99%

Genetic consequences of postglacial colonization by the endemic Yarkand hare (Lepus yarkandensis) of the arid Tarim Basin

Shan

Liu

et al. 2011

Chin. Sci. Bull.

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Orogenesis of the Qinghai-Tibetan Plateau, which occurred in a stepwise manner, contributed to the extreme aridity of the Tarim Basin, resulting in vulnerable and unstable ecosystems. Quaternary climatic oscillations may have affected the ecosystems and, consequently, the distributions and genetic structuring of the Tarim Basin's biota. We used nucleotide sequence data from 2 mitochondrial (mt) DNA genes (Cyt b and the D-loop) to test hypotheses associated with the matrilineal and demographical histories of the Tarim Basin's endemic Yarkand hare (Lepus yarkandensis). Range-wide sampling involving 20 populations and 224 individuals detected 126 haplotypes that clustered into 5 major lineages in both the phylogenetic tree and median-joining network. Populations from the northern and eastern Tarim Basin shared a similar history, as did those from the western and southern regions. Demographical analysis and genetic diversity estimations suggested that the western and southern regions might have served as glacial refugia for the Yarkand hare during Quaternary climatic oscillations. The distribution of the Yarkand hare, especially in the northern and eastern parts, probably represented 3 postglacial colonization events, dated to 0.21, 0.090 and 0.054 MYA, which corresponded to known interglacial periods. Given the relatively complete geographic isolation between the eastern and southern populations, the Yarkand hare likely dispersed during postglacial periods from the southwest to the north, and then onward to the east. The absence of water likely forced the species into refugia, and this differed from other Pleistocene biogeographical drivers. The demographical and historical patterns have important implications for conservation. Chinese Sci Bull, 2011, 56: 1370−1382, doi: 10.1007 Pleistocene climatic changes imposed significant range shifts on many Palearctic biota, and contributed to their demographic history and genetic diversity [1]. Many temperate species existed only in refugia at times of glacial maxima, and recolonized or expanded into newly available habitats during interglacial periods [2,3]. Quaternary evolutionary histories of European and North American biota *These authors contributed equally to this work †Corresponding authors

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“…The 'ecologically-relevant' hydrological variables were identified from previous research reported within 15 hydrological and ecological journal papers (see Appendix I, Hughes and James, 1989;Poff and Ward, 1989;Richards, 1989;Biggs, 1990;Jowett and Duncan, 1990;Poff, 1996;Richter, et al, 1996;Clausen and Biggs, 1997;Puckridge, et al, 1998;Richter, et al, 1998;Clausen and Biggs, 2000;Clausen, et al, 2000;Wood, et al, 2000;Wood, et al, 2001). Flow variables were assigned to one of five hydrological regime facets, as originally proposed in the Indicators of Hydrologic Alteration methodology (Richter, et al, 1996) and its derivatives (Poff, et al, 1997;Olden and Poff, 2003).…”

Section: Correlation and Regression Analysismentioning

confidence: 99%