A pan-Himalayan test of predictions on plant species richness based on primary production and water-energy dynamics

Kuber P Bhatta,Madan K Suwal,Ole R Vetaas,Benjamin A Robson

doi:10.21425/f5fbg49459

Abstract

Spatial variation in plant species diversity is well-documented but an overarching first-principles theory for diversity variation is lacking. Chemical energy expressed as Net Primary Production (NPP) is related to a monotonic increase in species richness at a macroscale and supports one of the leading energy-productivity hypotheses, the More individuals Hypothesis. Alternatively, water-energy dynamics (WED) hypothesizes enhanced species richness when water is freely available and energy supply is optimal. This theoretical model emphasises the amount and duration of photosynthesis across the year and therefore we include the length of the growing season and its interaction with precipitation. This seasonal-WED model assumes that biotemperature and available water represent the photosynthetically active period for the plants and hence, is directly related to NPP, especially in temperate and alpine regions. This study aims to evaluate the above-mentioned theoretical models using interpolated elevational species richness of woody and herbaceous flowering plants of the entire Himalayan range based on data compiled from databases. Generalized linear models (GLM) and generalized linear mixed models (GLMM) were used to analyse species richness (elevational gamma diversity) in the six geopolitical sectors of the Himalaya. NPP, annual precipitation, potential evapotranspiration (derived by the Holdridge formula), and length of growing season were treated as the explanatory variables and the models were evaluated using the Akaike Information Criterion (AIC) and explained deviance. Both precipitation plus potential evapotranspiration (PET), and NPP explain plant species richness in the Himalaya. The seasonal-WED model explains the species richness trends of both plant life-forms in all sectors of the Himalayan range better than the NPP-model. Despite the linear precipitation term failing to precisely capture the amount of water available to plants, the seasonal-WED model, which is based on the thermodynamical transition between water phases, is reasonably good and can forecast peaks in species richness under different climate and primary production conditions.

Highlights

A well-supported hypothesis in ecology and biogeography is that increased thermal energy promotes higher species diversity (Wright 1983, Currie 1991, Brown et al 2004, Clarke and Gaston 2006, Brown 2014)
We found that a Water-energy Dynamics (WED) model, which takes into account both kinetic thermal energy and water as drivers of plant species richness, explains spatial variance in plant species richness better than the Net Primary Production (NPP) model estimated by earth observation tool (MODIS), which only considers chemical energy
The main model assessment of NPP vs water−energy dynamics (WED) is based on 63 Generalised Linear Models (GLM) regression models of species richness in the Himalayan Mountain range (9 models for each Himalayan sector as well as the whole Himalaya, for each of which models M1, M2 and M3 was fitted for the herbaceous, woody- and total species richness) (Table 1, Table S1)

Summary

Introduction

A well-supported hypothesis in ecology and biogeography is that increased thermal energy promotes higher species diversity (Wright 1983, Currie 1991, Brown et al 2004, Clarke and Gaston 2006, Brown 2014). It is unconvincing that many models on macroscale species diversity do not include water but focus on how energy promotes species diversity by regulating metabolism, population size, and speciation rate (Evans et al 2005, Clarke and Gaston 2006) These energy-based models may convincingly explain why there are so many species in the warm equatorial sector and so few at the cold poles (Brown 2014), but fail to explain why the subtropics and warm-temperate sectors, which despite being relatively energy-rich, have low productivity levels and relatively few species (Vetaas et al 2019). This may relate to optimal moisture conditions at mid-elevations compared to the summits (frost) and lowland (high evapotranspiration) (Peters et al 2019, Vetaas et al 2019, and references therein)

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