We compare different null models for species richness patterns in the Nepalese Himalayas, the largest altitudinal gradient in the world. Species richness is estimated by interpolation of presences between the extreme recorded altitudinal ranges. The number of species in 100-m altitudinal bands increases steeply with altitude until 1,500 m above sea level. Between 1,500 and 2,500 m, little change in the number of species is observed, but above this altitude, a decrease in species richness is evident. We simulate different null models to investigate the effect of hard boundaries and an assumed linear relationship between species richness and altitude. We also stimulate the effect of interpolation when incomplete sampling is assumed. Some modifications on earlier simulations are presented. We demonstrate that all three factors in combination may explain the observed pattern in species richness. Estimating species richness by interpolating species presence between maximum and minimum altitudes creates an artificially steep decrease in species richness toward the ends of the gradient. The addition of hard boundaries and an underlying linear trend in species richness is needed to simulate the observed broad pattern in species richness along altitude in the Nepalese Himalayas.

Aim Species richness and endemic richness vary along elevation gradients, but not necessarily in the same way. This study tests if the maxima in gamma diversity for flowering plants and the endemic subset of these plants are coherent or not. LocationThe study was conducted in Nepal, between 1000 and 5000 m a.s.l. MethodsWe used published data on distribution and elevational ranges of the Nepalese flora to interpolate presence between maximum and minimum elevations. Correlation, regression and graphical analyses were used to evaluate the diversity pattern between 1000 and 5000 m a.s.l. ResultsThe interval of maximum species endemic to Nepal or the Himalayas (3800 -4200 m) is above the interval of maximum richness (1500 -2500 m). The exact location of maximum species density is uncertain and its accuracy depends on ecologically sound estimates of area in the elevation zones. There is no positive statistically significant correlation between log-area and richness (total or endemic). Total richness is positively correlated with log-area-adjusted, i.e. estimated area adjusted for the degree of topographic heterogeneity. The proportion of endemic species increases steadily from low to high elevations. The peak in endemism (c. 4000 m) corresponds to the start of a rapid decrease in species richness above 4000 m. This may relate to the last glacial maximum (equilibrium line at c. 4000 m) that penetrated down to 2500-3000 m. This dynamic hard boundary may have caused an increase in the extinction rate above 4000 m, and enhanced the probability of isolation and facilitated speciation of neoendemics, especially among genera with a high proportion of polyploids. Main conclusionsThe results reject the idea of corresponding maxima in endemic species and species richness in the lowlands tentatively deduced from Stevens' elevational Rapoport effect. They confirm predictions based on hard boundary theory, but hard-boundaries should be viewed as dynamic rather than static when broad-scale biogeographical patterns with a historical component are being interpreted.

Aim  The study explores fern species richness patterns along a central Himalayan elevational gradient (100–4800 m a.s.l.) and evaluates factors influencing the spatial increase and decrease of fern richness. Location  The Himalayas stretch from west to east by 20°, i.e. 75–95° east, and Nepal is located from 80 to 88° east in this range. Methods  We used published data of the distribution of ferns and fern allies to interpolate species elevational ranges. Defining species presence between upper and lower elevation limit is the basis for richness estimates. The richness pattern was regressed against the total number of rainy days, and gradients that are linearly related to elevation, such as length of the growing season, potential evapotranspiration (PET, energy), and a moisture index (MI = PET/mean annual rainfall). The regressions were performed by generalized linear models. Results  A unimodal relationship between species richness and elevation was observed, with maximum species richness at 2000 m. Fern richness has a unimodal response along the energy gradients, and a linear response with moisture gradients. Main conclusions  The study confirms the importance of moisture on fern distributions as the peak coincides spatially with climatic factors that enhance moisture levels; the maximum number of rainy days and the cloud zone. Energy‐related variables probably control species richness directly at higher elevations but at the lower end the effect is more probably related to moisture.

Aim To explore the variation in species richness along a subtropical elevation gradient, and evaluate how climatic variables explain the richness of the different life forms such as trees, shrubs, climbers, herbs and ferns. Location The study was made in a subtropical to warm temperate region in the south‐eastern part of Nepal, between 100 and 1500 m above sea level (a.s.l.). Methods The number of species was counted in six plots (50 × 20 m) in each of the 15 100 m elevation bands covering the main physiognomic structures along an imaginary transect. Each species recorded was assigned to a life form. Potential evapotranspiration (PET, i.e. energy), mean annual rainfall (MAR), and their ratio (MI = moisture index) were evaluated as explanatory variables by means of generalized linear models (GLM). Each variable was tested individually, and in addition MAR and PET were used to test the water‐energy dynamics model for each life form. Results The richness of herbaceous species, including herbaceous climbers, was unrelated to any of the climate variables. PET was strongly negatively correlated with elevation, and the following relationships were found between increasing PET and richness: (i) shrubs, trees and total species (sum of all life forms) showed unimodal responses (ii) ferns decreased monotonically, and (iii) woody climbers increased monotonically. Richness of all woody groups increased monotonically with MAR and MI. The water‐energy dynamics model explained 63% of the variation in shrubs, 67% for trees and 70% for woody species combined. Main conclusions For the various herbaceous life forms (forbs, grasses, and herbaceous climbers) we found no significant statistical trends, whereas for woody life forms (trees, shrubs, and woody climbers) significant relationships were found with climate. E.M. O’Brien's macro‐scale model based on water‐energy dynamics was found to explain woody species richness at a finer scale along this elevational‐climatic gradient.

Abstract. The physiognomy of dry savannas is described as a combination of discontinuous woody perennials and a continuous grassland matrix. Interactions between these two components are of vital importance for the persistence of a savanna landscape. Earlier savanna models have emphasized competitive interactions for water between the two components. Recent studies have argued that small‐scale facilitating interactions between woody perennials and the herbaceous understorey are also important. This phenomenon has been given little theoretical consideration in the savanna literature, but it has been an important topic in agroforestry and arid‐grassland ecology. This paper reviews some of the evidence for micro‐site effects of trees and shrubs, and attempts to integrate their interactions with the surrounding open grassland. Woody perennials modify the microclimate by interception of solar radiation and rainfall. Their root systems extract nutrients horizontally and vertically, which are concentrated in the sub‐canopy soil from litter decomposition and root turnover. Legumes are abundant in dry savannas, and may have symbiotic relationships with Rhizobium bacteria. This symbosis increases the availability of nitrogen in the soil. Isolated trees and shrubs initiate feedback mechanisms in their interactions with other organisms, and contribute to an uneven distribution of water and nutrients in dry savanna. This influences the species composition, and community diversity. Small‐scale facilitating interaction between the woody and herbaceous components and competitive interaction on larger scales, are complementary processes which together explain a dynamic coexistence.