A new system to classify global climate zones based on plant physiology and using high temporal resolution climate data

Abstract

Aim: Climate classification systems (CCSs) can be used to predict how species' distributions might be altered by climate change and to increase the reliability of these estimates is an important goal in biogeographical research. We produce an objective, global climate classification system (CCS) at high temporal resolution based on plant physiology as a robust way to predict how climate change may impact terrestrial biomes. Location: Global Taxon: Plantae Methods: We construct ten climate variables that capture the physiological processes that determine plant distributions and use cluster analysis to present a new global CCS which accounts for variation in these aspects of climate. We use Kappa statistics to compare the distribution of climate zones in a five-and six-cluster CCS constructed using the physiology variables to the popular Köppen-Geiger and Köppen-Trewartha CCSs, respectively, and find good correlation in both cases. Results: Our CCS highlights ten climate zones for plants. We show that clustering of the physiologically relevant variables reproduces known, present-day patterns of vegetation but also indicates important areas where zone assignment in our physiological CCSs is different to that of the Köppen systems. Main conclusions: The existing Köppen CCSs do not entirely reflect the physiological processes that determine plant distributions. Predictions of climate-driven changes in plant distributions may thus be unreliable in areas where zone assignment by clustering of physiologically relevant variables is different to that of the Köppen systems. Both the physiological relevance and temporal resolution of climate variables used to construct CCSs should be considered in order to predict reliably how climate change may alter plant distributions and to support an appropriate global response to conserve plant biodiversity for the future.

Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited

“…It might be that the use of fine-temporal resolution environmental data, i.e., the yearly averaged monthly values from the prec-temp dataset, is important for modeling the climatic preferences of a species with restricted habitats and little capacity for behavioral buffering, such as Camptoloma, whereas the annual bioclimatic variables from WorldClim work well for the more widespread Canarina. Our study thus supports the hypothesis that temporal resolution of environmental data when building ENMs should be at a scale adequate to understand physiological responses to climate change in the organism under study (Gardner et al, 2020), or in other words, at a scale over which biological responses directly influence their predicted presences in ENM models (Montalto et al, 2014).…”

“…There has been recent discussion on the importance of including fine-scale temporal resolution in the environmental data used for building ENMs (Kearney et al, 2012;Gardner et al, 2020;Perez-Navarro et al, 2020). The average-year bioclimatic variables obtained from WorldClim might be too coarse in temporal resolution to capture the climatic niche of short-lived species or species with large geographic ranges and contrasting seasonal regimes, for example, those distributed north and south of the equator (Kearney et al, 2012;Montalto et al, 2014).…”

Complementarity between herbaceous and woody plants in providing resources for bees in a semi-arid tropical climate: insights for conservation

“…According to the Köppen system, the semi-arid climate (BSh) predominates in the Caatinga, with summer and autumn rains and dry winter (Alvares et al 2014). The climate zone corresponding to that classification in the Gardner et al (2020) system is Tropical Savanna.…”

“…As a consequence, less structurally complex and diverse environments are expected, and there will be a reduction in the number of plant species with different growth habits and specialized pollination systems, directly affecting resource supplies for bees (Silva et al 2019) Given the knowledge gap on resources availability for bees from the whole plant community and the vulnerability of Brazilian semi-arid vegetation to land use and climate crisis, we analyzed the availability of floral and non-floral supplies for bees at the community level in three fragments of Caatinga, northeast Brazil. The Caatinga is a seasonally dry forest located in the Brazilian semi-arid region, classified as Tropical Savanna sensu Gardner et al (2020).…”

Regularities in species’ niches reveal the world’s climate regions

“…In Thornthwaite, 1943 words, the ‘truly active factors’ describing a climate type may vary among organisms, and it remains unknown whether Köppen’s climate classification can indicate the active climatic factors for other organisms than plants. Despite several attempts to refine or propose alternative climate types or regions ( Trewartha, 1954 ; Holdridge, 1947 ; Thornthwaite, 1948 ; Netzel and Stepinski, 2016 ; Gardner et al, 2020 ), quantitative studies defining climatic regions for other organisms are still lacking.…”