WHY THIS PROJECT?
Normal 0 21 false false false CS X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Thousands of elevational gradients are distributed across the globe on all continents and on most islands in various latitudes, climates and habitats. Moreover, birds are the best known faunal group, and have been common taxa to investigate many different patterns. Consequently, no surprise that there are about 190 elevational gradients of bird species richness in more than 150 published studies. In these works, several diversity patterns are exhibited on montane gradients (Rahbek 1995, 2005; McCain 2005, 2007a): decreasing diversity with increasing elevation, high diversity across a plateau of lower elevations then decreasing monotonically, a unimodal pattern with maximum diversity at intermediate elevations, or in rare instances increasing monotonically.
Proposed drivers of biodiversity can be grouped into four main categories: current climate, space (and mid-domain effect), evolutionary history and biotic processes (Pianka 1966, Gaston 2000, McCain 2007a), possibly explaining large-scale patterns in species richness. Sampling method could be another factor influencing apparent diversity patterns. All these drivers predict diversity patterns in following manners:
1. Sampling
Differences in sampling effort across the gradient may result in an experimental bias in diversity estimation (e.g. Colwell and Coddington 1994). For example, in cases where elevational bands were sampled with unequal effort, a relationship between diversity and elevation could simply be a result of differential sampling effort.
2. Space
On mountains, the „species-area” predicts that elevational bands covering more area (e.g. mountain base) should harbour more species than elevational bands covering a small area (e.g. mountain tops) (Rahbek 1997; McCain 2007b).
3. Mid-domain effect
The MDE assumes that spatial boundaries (e.g. the base and top of a mountain) cause more overlap of species ranges toward the centre of an area where many large- to medium-sized ranges must overlap but are less likely to abut an edge of the area (Colwell et al. 2004, 2005 and references therein).
4. Temperature
Climatic tolerances put restrictions on how many species can survive at different locations and elevations (e.g. Brown 2001). On mountains, temperature decreases monotonically by an average of 0.6 °C per 100-m elevational gain (Barry 1992). If temperature is a main determinant of bird diversity, the predominant elevational diversity pattern predicted is decreasing diversity with decreasing temperature and increasing elevation.
5. Temperature and water
Temperature decreases with elevation on all mountains, while rainfall and water availability follow more complex relationships with elevation depending on the local climate. On arid mountains, water availability is highest at intermediate elevations where rainfall and soil water retention are highest and evaporation lowest. On humid mountains, water availability is high across a broad base of lower elevations and only decreases toward the tops of the mountains, again due to higher runoff and decreases in rainfall. Bird species richness is predicted to be positively related to the warmest and wettest conditions elevationally, predicting mid-elevation peaks in bird species richness on arid mountains and decreasing diversity on warm, wet mountains.
6. Evolutionary history
Wiens et al. (2007) think that, although some studies have addressed correlations between elevational species richness patterns and climatic variables (e.g. McCain 2005, 2007; Oomen and Shanker 2005), patterns of species richness must ultimately be explained in terms of the processes that directly change the number of species in a region, namely speciation, extinction and biogeographic dispersal (e.g. Ricklefs 2004, Wiens and Donoghue 2004). Climate and other factors may still play a critically important role (and may be tightly correlated with species numbers), but they must act on these three processes to directly change the species numbers within a region.
Several authors have suggested that montane regions could have increased speciation rates at mid-elevations or increased extinction rates at the lowest and highest elevations (see species pump model; Moritz et al. 2000). An alternative hypothesis is that rates of diversification are similar at different elevations, and that intermediate elevations might have higher species richness because (for a given group) they have been colonized for longer periods of time than lowland or extreme high elevations.
McCain tested all these main drivers of diversity in his review (2009). Bird elevational diversity strongly supports current climate as the main driver of diversity, particularly combined trends in temperature and water availability. Bird diversity on humid mountains is either decreasing or shows a low-elevation plateau in diversity, while on dry mountains it is unimodal or a broad, low-elevation plateau usually with a mid-elevation maximum.These results emphasize that water in a necessary factor modifying the temperature effect on elevational diversity. May be the evapotranspiration could be even better predictor but there are no data available.
Proposed drivers of biodiversity can be grouped into four main categories: current climate, space (and mid-domain effect), evolutionary history and biotic processes (Pianka 1966, Gaston 2000, McCain 2007a), possibly explaining large-scale patterns in species richness. Sampling method could be another factor influencing apparent diversity patterns. All these drivers predict diversity patterns in following manners:
1. Sampling
Differences in sampling effort across the gradient may result in an experimental bias in diversity estimation (e.g. Colwell and Coddington 1994). For example, in cases where elevational bands were sampled with unequal effort, a relationship between diversity and elevation could simply be a result of differential sampling effort.
2. Space
On mountains, the „species-area” predicts that elevational bands covering more area (e.g. mountain base) should harbour more species than elevational bands covering a small area (e.g. mountain tops) (Rahbek 1997; McCain 2007b).
3. Mid-domain effect
The MDE assumes that spatial boundaries (e.g. the base and top of a mountain) cause more overlap of species ranges toward the centre of an area where many large- to medium-sized ranges must overlap but are less likely to abut an edge of the area (Colwell et al. 2004, 2005 and references therein).
4. Temperature
Climatic tolerances put restrictions on how many species can survive at different locations and elevations (e.g. Brown 2001). On mountains, temperature decreases monotonically by an average of 0.6 °C per 100-m elevational gain (Barry 1992). If temperature is a main determinant of bird diversity, the predominant elevational diversity pattern predicted is decreasing diversity with decreasing temperature and increasing elevation.
5. Temperature and water
Temperature decreases with elevation on all mountains, while rainfall and water availability follow more complex relationships with elevation depending on the local climate. On arid mountains, water availability is highest at intermediate elevations where rainfall and soil water retention are highest and evaporation lowest. On humid mountains, water availability is high across a broad base of lower elevations and only decreases toward the tops of the mountains, again due to higher runoff and decreases in rainfall. Bird species richness is predicted to be positively related to the warmest and wettest conditions elevationally, predicting mid-elevation peaks in bird species richness on arid mountains and decreasing diversity on warm, wet mountains.
6. Evolutionary history
Wiens et al. (2007) think that, although some studies have addressed correlations between elevational species richness patterns and climatic variables (e.g. McCain 2005, 2007; Oomen and Shanker 2005), patterns of species richness must ultimately be explained in terms of the processes that directly change the number of species in a region, namely speciation, extinction and biogeographic dispersal (e.g. Ricklefs 2004, Wiens and Donoghue 2004). Climate and other factors may still play a critically important role (and may be tightly correlated with species numbers), but they must act on these three processes to directly change the species numbers within a region.
Several authors have suggested that montane regions could have increased speciation rates at mid-elevations or increased extinction rates at the lowest and highest elevations (see species pump model; Moritz et al. 2000). An alternative hypothesis is that rates of diversification are similar at different elevations, and that intermediate elevations might have higher species richness because (for a given group) they have been colonized for longer periods of time than lowland or extreme high elevations.
McCain tested all these main drivers of diversity in his review (2009). Bird elevational diversity strongly supports current climate as the main driver of diversity, particularly combined trends in temperature and water availability. Bird diversity on humid mountains is either decreasing or shows a low-elevation plateau in diversity, while on dry mountains it is unimodal or a broad, low-elevation plateau usually with a mid-elevation maximum.These results emphasize that water in a necessary factor modifying the temperature effect on elevational diversity. May be the evapotranspiration could be even better predictor but there are no data available.