Matches in SemOpenAlex for { <https://semopenalex.org/work/W193346797> ?p ?o ?g. }
- W193346797 endingPage "177" @default.
- W193346797 startingPage "159" @default.
- W193346797 abstract "In this paper a multivariate linear regression model is proposed for predicting and mapping regional species richness in areas below the timberline according to environmental variables. The data used in setting up the model were derived from a floristic inventory. Using a stepwise regression technique, five environmental variables were found to explain 48.9% of the variability in the total number of plant species: namely temperature range, proximity to a big river or lake, threshold of minimum annual precipitation, amount of calcareous rock outcrops and number of soil types. A considerable part of the unexplained variability is thought to have been influenced by variations in the quality of the botanical inventory. These results show the importance of systematic floristic sampling in addition to conventional inventories when using floristic data as a basis in nature conservation. Nevertheless it is still possible to interpret the resulting diversity patterns ecologically. Regional species richness in Switzerland appears to be a function of: (i) environmental heterogeneity; (ii) threshold values of minimum precipitation; and (iii) presence of calcareous rock outcrops. According to similar studies, environmental heterogeneity was the strongest determinant of total species richness. In contrast to some studies, high productivity decreased the number of species. Furthermore, the implications of this work for climate change scenarios are discussed." @default.
- W193346797 created "2016-06-24" @default.
- W193346797 creator A5020053279 @default.
- W193346797 date "1998-01-01" @default.
- W193346797 modified "2023-09-30" @default.
- W193346797 cites W113312865 @default.
- W193346797 cites W1501988926 @default.
- W193346797 cites W1545075080 @default.
- W193346797 cites W1907425863 @default.
- W193346797 cites W1969733700 @default.
- W193346797 cites W1971222014 @default.
- W193346797 cites W1975003732 @default.
- W193346797 cites W1978120470 @default.
- W193346797 cites W1979435499 @default.
- W193346797 cites W2001318871 @default.
- W193346797 cites W2018204894 @default.
- W193346797 cites W2018436594 @default.
- W193346797 cites W2019000563 @default.
- W193346797 cites W2043820957 @default.
- W193346797 cites W2054050934 @default.
- W193346797 cites W2057606729 @default.
- W193346797 cites W206286344 @default.
- W193346797 cites W2065745399 @default.
- W193346797 cites W2066017461 @default.
- W193346797 cites W2066809097 @default.
- W193346797 cites W2087677069 @default.
- W193346797 cites W2090143187 @default.
- W193346797 cites W2090999887 @default.
- W193346797 cites W2092103879 @default.
- W193346797 cites W2099728413 @default.
- W193346797 cites W2114689794 @default.
- W193346797 cites W2312399181 @default.
- W193346797 cites W2313554273 @default.
- W193346797 cites W2314874216 @default.
- W193346797 cites W2314909328 @default.
- W193346797 cites W2317481643 @default.
- W193346797 cites W2331931313 @default.
- W193346797 cites W2335080955 @default.
- W193346797 cites W2428041923 @default.
- W193346797 cites W2527225461 @default.
- W193346797 cites W2618783149 @default.
- W193346797 cites W2759784795 @default.
- W193346797 cites W2795802637 @default.
- W193346797 cites W3006671633 @default.
- W193346797 cites W59689390 @default.
- W193346797 cites W598186006 @default.
- W193346797 cites W614397662 @default.
- W193346797 cites W2460046513 @default.
- W193346797 cites W2516606052 @default.
- W193346797 cites W3202540900 @default.
- W193346797 doi "https://doi.org/10.1023/a:1008880317661" @default.
- W193346797 hasPublicationYear "1998" @default.
- W193346797 type Work @default.
- W193346797 sameAs 193346797 @default.
- W193346797 citedByCount "120" @default.
- W193346797 countsByYear W1933467972012 @default.
- W193346797 countsByYear W1933467972013 @default.
- W193346797 countsByYear W1933467972014 @default.
- W193346797 countsByYear W1933467972015 @default.
- W193346797 countsByYear W1933467972016 @default.
- W193346797 countsByYear W1933467972017 @default.
- W193346797 countsByYear W1933467972019 @default.
- W193346797 countsByYear W1933467972020 @default.
- W193346797 countsByYear W1933467972022 @default.
- W193346797 countsByYear W1933467972023 @default.
- W193346797 crossrefType "journal-article" @default.
- W193346797 hasAuthorship W193346797A5020053279 @default.
- W193346797 hasBestOaLocation W1933467972 @default.
- W193346797 hasConcept C100970517 @default.
- W193346797 hasConcept C105795698 @default.
- W193346797 hasConcept C106131492 @default.
- W193346797 hasConcept C130217890 @default.
- W193346797 hasConcept C132651083 @default.
- W193346797 hasConcept C140779682 @default.
- W193346797 hasConcept C159985019 @default.
- W193346797 hasConcept C161584116 @default.
- W193346797 hasConcept C187604713 @default.
- W193346797 hasConcept C18903297 @default.
- W193346797 hasConcept C192562407 @default.
- W193346797 hasConcept C204323151 @default.
- W193346797 hasConcept C205649164 @default.
- W193346797 hasConcept C31972630 @default.
- W193346797 hasConcept C33923547 @default.
- W193346797 hasConcept C39432304 @default.
- W193346797 hasConcept C41008148 @default.
- W193346797 hasConcept C45152089 @default.
- W193346797 hasConcept C53565203 @default.
- W193346797 hasConcept C86803240 @default.
- W193346797 hasConceptScore W193346797C100970517 @default.
- W193346797 hasConceptScore W193346797C105795698 @default.
- W193346797 hasConceptScore W193346797C106131492 @default.
- W193346797 hasConceptScore W193346797C130217890 @default.
- W193346797 hasConceptScore W193346797C132651083 @default.
- W193346797 hasConceptScore W193346797C140779682 @default.
- W193346797 hasConceptScore W193346797C159985019 @default.
- W193346797 hasConceptScore W193346797C161584116 @default.
- W193346797 hasConceptScore W193346797C187604713 @default.
- W193346797 hasConceptScore W193346797C18903297 @default.