Thomas Hanbury

A comprehensive evaluation of the habitat suitability across the India was conducted for the introduced species Opuntia ficus-indica . This assessment utilized a newly developed model called BioClimInd, takes into account five Earth System Models (ESMs). These ESMs consider two different emission scenarios known as Representative Concentration Pathways (RCP), specifically RCP 4.5 and RCP 8.5. Additionally, the assessment considered two future time frames: 2040–2079 (60) and 2060–2099 (80). Current study provided the threshold limit of different climatic variables in annual, quarter and monthly time slots like temperature annual range (26–30 °C), mean temperature of the driest quarter (25–28 °C); mean temperature of the coldest month (22–25 °C); minimum temperature of coldest month (13–17 °C); precipitation of the wettest month (250–500 mm); potential evapotranspiration Thronthwaite (1740–1800 mm). Predictive climatic habitat suitability posits that the introduction of this exotic species is deemed unsuitable in the Northern as well as the entirety of the cooler eastern areas of the country. The states of Rajasthan and Gujarat exhibit the highest degree of habitat suitability for this particular species. Niche hypervolumes and climatic variables affecting fundamental and realized niches were also assessed. This study proposes using multi-climatic exploration to evaluate habitats for introduced species to reduce modeling uncertainties.

Premise: Cacti are characteristic elements of the Neotropical flora and of major interest for biogeographic, evolutionary, and ecological studies. Here we test global biogeographic boundaries for Neotropical Cactaceae using specimen‐based occurrences coupled with data from visual observations, as a means to tackle the known collection biases in the family.MethodsSpecies richness and record density were assessed for preserved specimens and human observations and a bioregional scheme tailored to Cactaceae was produced using the interactive web application Infomap Bioregions based on data from 261,272 point records cleaned through automated and manual steps.Key ResultsWe find that areas in Mexico and southwestern USA, Eastern Brazil and along the Andean region have the greatest density of records and the highest species richness. Human observations complement information from preserved specimens substantially, especially along the Andes. We propose 24 cacti bioregions, among which the most species‐rich are: northern Mexico/southwestern USA, central Mexico, southern central Mexico, Central America, Mexican Pacific coast, central and southern Andes, northwestern Mexico/extreme southwestern USA, southwestern Bolivia, northeastern Brazil, Mexico/Baja California.ConclusionsThe bioregionalization proposed shows biogeographical boundaries specific to cacti, and can thereby aid further evolutionary, biogeographic, and ecological studies by providing a validated framework for further analyses. This classification builds upon, and is distinctive from, other expert‐derived regionalization schemes for other taxa. Our results showcase how observation data, including citizen‐science records, can complement traditional specimen‐based data for biogeographic research, particularly for taxa with specific specimen collection and preservation challenges and those that are threatened or internationally protected.This article is protected by copyright. All rights reserved.

Mapping biodiversity patterns across taxa and environments is crucial to address the evolutionary and ecological dimensions of species distribution, suggesting areas of particular importance for conservation purposes. Within Cactaceae, spatial diversity patterns are poorly explored, as are the abiotic factors that may predict these patterns. We gathered geographic and genetic data from 921 cactus species by exploring both the occurrence and genetic databases, which are tightly associated with drylands, to evaluate diversity patterns, such as phylogenetic diversity and endemism, paleo-, neo-, and superendemism, and the environmental predictor variables of such patterns in a global analysis. Hotspot areas of cacti diversity are scattered along the Neotropical and Nearctic regions, mainly in the desertic portion of Mesoamerica, Caribbean Island, and the dry diagonal of South America. The geomorphological features of these regions may create a complexity of areas that work as locally buffered zones over time, which triggers local events of diversification and speciation. Desert and dryland/dry forest areas comprise paleo- and superendemism and may act as both museums and cradles of species, displaying great importance for conservation. Past climates, topography, soil features, and solar irradiance seem to be the main predictors of distinct endemism types. The hotspot areas that encompass a major part of the endemism cells are outside or poorly covered by formal protection units. The current legally protected areas are not able to conserve the evolutionary diversity of cacti. Given the rapid anthropogenic disturbance, efforts must be reinforced to monitor biodiversity and the environment and to define/plan current and new protected areas.

Identifying the environmental drivers of the global distribution of succulent plants using the Crassulacean acid metabolism pathway of photosynthesis has previously been investigated through ensemble‐modeling of species delimiting the realized niche of the natural succulent biome. An alternative approach, which may provide further insight into the fundamental niche of succulent plants in the absence of dispersal limitation, is to model the distribution of selected species that are globally widespread and have become naturalized far beyond their native habitats. This could be of interest, for example, in defining areas that may be suitable for cultivation of alternative crops resilient to future climate change. We therefore explored the performance of climate‐only species distribution models (SDMs) in predicting the drivers and distribution of two widespread CAM plants, Opuntia ficus‐indica and Euphorbia tirucalli. Using two different algorithms and five predictor sets, we created distribution models for these exemplar species and produced an updated map of global inter‐annual rainfall predictability. No single predictor set produced markedly more accurate models, with the basic bioclim‐only predictor set marginally out‐performing combinations with additional predictors. Minimum temperature of the coldest month was the single most important variable in determining spatial distribution, but additional predictors such as precipitation and inter‐annual precipitation variability were also important in explaining the differences in spatial predictions between SDMs. When compared against previous projections, an a posteriori approach correctly does not predict distributions in areas of ecophysiological tolerance yet known absence (e.g., due to biotic competition). An updated map of inter‐annual rainfall predictability has successfully identified regions known to be depauperate in succulent plants. High model performance metrics suggest that the majority of potentially suitable regions for these species are predicted by these models with a limited number of climate predictors, and there is no benefit in expanding model complexity and increasing the potential for overfitting.

The Qinghai-Tibetan Plateau (QTP) harbors abundant and diverse plant life owing to its high habitat heterogeneity. However, the distribution pattern of biodiversity hotspots and their conservation status remain unclear. Based on 148,283 high-resolution occurrence coordinates of 13,450 seed plants, w…