Date Published: June 20, 2019
Publisher: Public Library of Science
Author(s): Poonam Tripathi, Mukunda Dev Behera, Partha Sarathi Roy, Angelina Martínez-Yrízar.
Knowledge of species richness patterns and their relation with climate is required to develop various forest management actions including habitat management, biodiversity and risk assessment, restoration and ecosystem modelling. In practice, the pattern of the data might not be spatially constant and cannot be well addressed by ordinary least square (OLS) regression. This study uses GWR to deal with spatial non-stationarity and to identify the spatial correlation between the plant richness distribution and the climate variables (i.e., the temperature and precipitation) in a 1° grid in different biogeographic zones of India.
We utilized the species richness data collected using 0.04 ha nested quadrats in an Indian study. The data from this national study, titled ‘Biodiversity Characterization at Landscape Level’, were aggregated at the 1° grid level and adjudged for sampling sufficiency. The performances of OLS and GWR models were compared in terms of the coefficient of determination (R2) and the corrected Akaike Information Criterion (AICc).
A comparative study of the R2 and AICc values of the models showed that all the GWR models performed better compared with the analogous OLS models. The climate variables were found to significantly influence the distribution of plant richness in India. The minimum precipitation (Pmin) consistently dominated individually (R2 = 0.69; AICc = 2608) and in combinations. Among the shared models, the one with a combination of Pmin and Tmin had the best model fits (R2 = 0.72 and AICc = 2619), and variation partitioning revealed that the influence of these parameters on the species richness distribution was dominant in the arid and the semi-arid zones and in the Deccan peninsula zone.
The shift in climate variables and their power to explain the species richness of biogeographic zones suggests that the climate–diversity relationships of plants species vary spatially. In particular, the dominant influence of Tmin and Pmin could be closely linked to the climate tolerance hypothesis (CTH). We found that the climate variables had a significant influence in defining species richness patterns in India; however, various other environmental and non-environmental (edaphic, topographic and anthropogenic) variables need to be integrated in the models to understand climate–species richness relationships better at a finer scale.
Knowledge of plant richness patterns under various environmental conditions is important in dealing with biodiversity conservation and management actions. The spatial distribution of species is associated with variations in latitude, elevation, climate and area [1–4]. Among these, the climate variables, i.e. precipitation (water) and temperature (energy), have emerged as the key influencing factors [5–7]. Water and energy are essential for plant physiological processes as they directly influence photosynthesis, respiration, plant growth and productivity . However, the influences of the two factors (water and energy) may not be equally important globally, and their relative importance shifts along a latitude [8–10]. Many plausible hypotheses have been postulated on the basis of these findings and observations. The energy hypothesis suggests that the species richness of a region is a function of the total energy available and, therefore, provides a positive relationship between the species richness and energy variables such as temperature [11–13]. Another important insight into the water–energy dynamics was provided by O’Brien . This insight suggests that the broad-scale patterns of species richness derive from the interaction of the available energy and water. It is predicted from the water–energy dynamics that more species occupy regions where more water and energy are available and that the strength of this relationship might vary with spatial scale [15, 16]. The climate tolerance hypothesis (CTH) suggests that ‘species richness is the highest at warm and/or humid environment[s] because a wider range of functional strategies can persist under similar conditions’ . Several species cannot survive in extremely cold or hot environments . The environmental stress hypothesis suggests that the species pool decreases with increasing climate harshness . Climatic harshness is often defined by extreme climatic variability, e.g. low temperatures and low water availability . On the basis of the aforementioned hypotheses, it may be inferred that the spatial heterogeneity of climatic factors may significantly influence the species distribution pattern at both the regional and global scales. Therefore, the distribution of plant richness is not smooth, and different drivers may apply at different latitudes or in different biogeographic regions [8, 13].
The key finding from our study is that climate heterogeneity underlies the broad scale species richness distribution in India. We suggest that the spatial distribution of climatic water availability strongly influences the distribution of species in India. Species richness predictors are thought to vary systematically with the spatial scale at which climate–richness relationships are quantified. In the present study, the GWR bandwidth defined this scale. Although we found climate variables to have a decisive influence in defining species richness patterns in India, there are various other environmental and non-environmental (edaphic, topographic and anthropogenic) variables that need to be integrated in the models to understand climate–species richness relationships better at a finer grid level. The data were analysed at the 1° grid level, and only a few grid cells were available in the Himalaya (18) and in the Western Ghats zone (17). Therefore, elevational variations were not considered in the present study. The Gangetic plains, the Himalaya and the Trans-Himalaya need critical analysis. The moderate to high species richness in these zones were overlapped with the presence of protected areas, which is highlighting the potential contributions of these zones to the species pool, but constrained by forest loss. India has some of the most diverse bio-climatic zones of the world; nonetheless, the large human population and extensive agricultural activities exert continuous pressure on the forests, leading to decreasing species richness. The warming of bio-climatic regions, especially the potential effects of changes in precipitation, needs to be investigated closely to understand climate–species richness relationships so that mitigation measures may be developed in the face of climate change.