Charles Russell Orcutt

Species’ range size is a fundamental unit of analysis in biodiversity research, given its association with extinction risk and species richness. One of its most notable patterns is its positive relationship with latitude, which has been considered an ecogeographical rule called Rapoport’s rule. Despite this rule being confirmed for various taxonomic groups, its validity has been widely discussed and several taxa still lack a formal assessment. Different hypotheses have been proposed to explain their potential mechanisms, with those related to temperature and elevational being the most supported thus far. In this study, we employed two level of analyses (cross-species and assemblage) to investigate the validity of Rapoport’s rule in spiny lizards (genus Sceloporus). Additionally, we evaluated four environmental-related hypotheses (minimum temperature, temperature variability, temperature stability since the last glacial maximum, and elevation) posed to explain such pattern, contrasting our results to those patterns expected under a null model of range position. Our results provided support for Rapoport’s rule at both levels of analyses, contrasting with null expectations. Consistently, minimum temperature and elevation were the most relevant variables explaining the spatial variation in range size. At the cross-species level, our null simulations revealed that both variables deviated significantly from random expectations. Conversely, at the assemblage level, none of the variables were statistically different from the expected relationships. We discussed the implication of our findings in relation to the ecology and evolution of spiny lizards.

Premise Vertical surfaces in urban environments represent a potential expansion of niche space for lithophytic fern species. There are, however, few records of differential success rates of fern species in urban environments.MethodsThe occurrence rates of 16 lithophytic fern species native to the northeastern USA in 14 biomes, including four urban environments differentiated by percentage of impervious surfaces, were evaluated. In addition, the natural macroclimatic ranges of these species were analyzed to test whether significant differences existed in climatic tolerance between species that occur in urban environments and species that do not.ResultsThree species appear to preferentially occur in urban environments, two species may facultatively occur in urban environments, and the remaining 11 species preferentially occur in nondeveloped rural environments. The natural range of fern species that occur in urban environments had higher summer temperatures than the range of species that do not, whereas other macroclimatic variables, notably winter temperatures and precipitation, were less important or insignificant.ConclusionsVertical surfaces in urban environments may represent novel niche space for some native lithophytic fern species in northeastern USA. However, success in this environment depends, in part, on tolerance of the urban heat island effect, especially heating of impervious surfaces in summer.

Background: The genus Pinguicula harbors 110 species, of which 53 are distributed in Mexico. The formation of the Mexican mountains has favored the Pinguicula diversification. Pinguicula specimens collected in the State of México, along the Trans-Mexican Volcanic Belt (TMVB) do not correspond with any known species. Questions: Do the collected specimens belong to a new species? What is its conservation status? How many Pinguicula species are there along the TMVB and how do they differentiate? How is the Pinguicula species richness distributed? Studied species: Pinguicula. Study site and dates: TMVB, 2005-2023. Methods: Based on herbarium specimens and recently collected material, a morphological analysis and description were made. Conservation status was assessed following IUCN Red List Categories and Criteria. Herbarium specimens and digital records of Pinguicula from the TMVB were examined to generate a list and key. We analyzed the richness distribution of Pinguicula by states, vegetation types, elevation ranges, and grid cells. Results: Pinguicula tlahuica is proposed as a new species. It is distinguished by the linear-spatulate summer leaves. The new species falls into the Endangered (EN) category. Along the TMVB, 16 species of Pinguicula are distributed. The State of México, Hidalgo and Michoacán, and the pine-oak forest were the richest. Pinguicula appeared between 759-3,427 m asl. The grid cell analyses revealed different areas with high richness. Conclusions: Along the TMVB, the Pinguicula species richness centered on the Eastern and Western sectors. Pinguicula crassifolia, P. michoacana, P. tlahuica, and P. zamudioana are endemic to the TMVB.

Climatic changes can affect species distributions, population abundance, and evolution. Such organismal responses could be determined by the amount and quality of available habitats, which can vary independently. In this study, we assessed changes in habitat quantity and quality independently to generate explicit predictions of the species' responses to climatic changes between Last Glacial Maximum (LGM) and present day. We built ecological niche models for genetic groups within 21 reptile, mammal, and plant taxa from the Baja California peninsula inhabiting lowland or highland environments. Significant niche divergence was detected for all clades within species, along with significant differences in the niche breadth and area of distribution between northern and southern clades. We quantified habitat quantity from the distribution models, and most clades showed a reduction in distribution area towards LGM. Further, niche marginality (used as a measure of habitat quality) was higher during LGM for most clades, except for northern highland species. Our results suggest that changes in habitat quantity and quality can affect organismal responses independently. This allows the prediction of genomic signatures associated with changes in effective population size and selection pressure that could be explicitly tested from our models.

Aim Understanding the impacts of past and future climate change on genetic diversity and structure is a current major research gap. We ask whether past range shifts explain the observed genetic diversity of surfgrass species and if future climate change projections anticipate genetic diversity losses. Our study aims to identify regions of long‐term climate suitability with higher and unique seagrass genetic diversity and predict future impacts of climate change on them.LocationNortheast Pacific.Time PeriodAnalyses considered a timeframe from the Last Glacial Maximum (LGM; 20 kybp) until one Representative Concentration Pathway (RCP) scenario of future climate changes (RCP 8.5; 2100).Major Taxa StudiedTwo seagrass species belonging to the genus Phyllospadix.MethodsWe estimated population genetic diversity and structure using 11 polymorphic microsatellite markers. We predicted the distribution of the species for the present, LGM, and near future (RCP 8.5, no climate mitigation) using Species Distribution Models (SDMs).ResultsSDMs revealed southward range shifts during the LGM and potential poleward expansions in the future. Genetic diversity of Phyllospadix torreyi decreases from north to south, but in Phyllospadix scouleri the trend is variable. Phyllospadix scouleri displays signals of genome admixture at the southernmost and northernmost edges of its distribution.Main ConclusionsThe genetic patterns observed in the present reveal the influence of climate‐driven range shifts in the past and suggest further consequences of climate change in the future, with potential loss of unique gene pools. This study also shows that investigating climate links to present genetic information at multiple timescales can establish a historical context for analyses of the future evolutionary history of populations.

Arid and semi-arid areas are highly productive ecosystems that have a great diversity of species, among which grasses stand out. These species have ecological, environmental, and economic importance. The objective was to identify the ecological descriptors of 15 native species of grasses and diversity patterns through multivariate analysis techniques (principal component analysis, PCA, and cluster analysis, CA), in addition to identifying potential distribution areas (current and future) and regions of high and low diversity from 3841 accessions and 21 climatic variables. Among the main results, the extreme values, coefficient of variation, and median for each species could be determined. PCA determined that, with 10 variables, it was possible to explain 54.36% of the variation between the analyzed species. CA resulted in the formation of four statistically significant groups, with specific climatic characteristics. Regarding potential distribution areas and climate change, a reduction in distribution is expected (2050) on most of the current surface, with a possible opportunity zone in the north of the country. Finally, two hotspots (high diversity areas) and four coldspots (low diversity areas) were identified among the analyzed species. These results can be used to create strategies for sustainable use and the conservation of these resources.

Species occurrence-based climate niche models (CNMs) serve as valuable tools for predicting the future ranges of species’ suitable habitats, aiding the development of climate change adaptation strategies. However, these models do not address an essential aspect - productivity, which holds economic significance for timber production and ecological importance for carbon sequestration and ecosystem services. In this study, we investigated the potential to extend the CNMs to predict species productivity under various climate conditions. Lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.) were selected as our model species due to their comprehensive range-wide occurrence data and measurement of site productivity. To achieve this, we compared and optimized the performance of four individual modeling algorithms (Random Forest (RF), Maxent, Generalized Boosted Models (GBM), and Generalized Additive Model (GAM)) in reflecting site productivity by evaluating the effect of spatial filtering, and the ratio of presence to absence (p/a ratio) observations. Additionally, we applied a binning process to capture the overarching trend of climatic effects while minimizing the impact of other factors. We observed consistency in optimal performance across both species when using the unfiltered data and a 1:1.5 p/a ratio, which could potentially be extended to other species. Among the modeling algorithms explored, we selected the ensemble model combining RF and Maxent as the final model to predict the range-wide site productivity for both species. The predicted range-wide site productivity was validated with an independent dataset for each species and yielded promising results (R2 above 0.7), affirming our model’s credibility. Our model introduced an innovative approach for predicting species productivity with high accuracy using only species occurrence data, and significantly advanced the application of CNMs. It provided crucial tools and insights for evaluating climate change's impact on productivity and holds a better potential for informed forest management and conservation decisions.

Conservation and management of drylands is a global challenge. Key attributes of these ecosystems, such as dominant vegetation including shrubs, can provide a crucial mechanism to inform conservation strategies. The shrub species Ephedra californica and Larrea tridentata are common native shrub species within the deserts of California and frequently benefit other plant and animal species. Here, we tested the hypothesis that shrubs support reptile and amphibian communities through relative increases in available habitat, estimated through increasing shrub densities at the site level. Reported occurrence data from the Global Biodiversity Information Facility (GBIF) and high-resolution satellite images were used to test for local-to-regional patterns in reptile and amphibian distribution and diversity by shrub densities at sites. At 43 distinct sites, the relationship between shrub density and reported reptile and amphibian communities was also tested. A total of 71 reptile and amphibian species were reported regionally. Increases in shrub density across sites positively influenced the relative abundance and richness of reptiles and amphibians observed. Moreover, increasing shrub density also had a positive influence on species evenness. Aridity differences between sites did not significantly influence the relationship between shrub density and reptiles and amphibians suggesting that the relationship was robust. This study highlights the importance of foundational shrub species in supporting reptile and amphibian communities in arid and semi-arid regions. Large-scale patterns of biodiversity in deserts can be supported by positive plant-animal interactions including small islands of fertility and resources for animals in the context of a warming climate.

The subtribe Ponerinae (Orchidaceae) includes the genera Helleriella A. D. Hawkes, Isochilus R. Brown, Nemaconia Knowles & Westc., and Ponera Lindl. Most of its species are epiphytes and usually grow on trees of the genus Quercus L. in cloud forests and temperate coniferous and broad-leaved forests; some taxa are rarely lithophytes or less frequently terrestrial. The aim of this study was to estimate the distribution of the species of the subtribe Ponerinae using ecological niche models (ENM), determine areas with highest richness and endemism rates with the occurrence data and the models obtained, and determine if the areas with highest richness and endemism recognized in this work are located within any of the conservation areas (ANPs) and/or Regiones Terrestres Prioritarias (RTPs). We reviewed 1 044 herbarium specimens from ten institutional collections, corresponding to two species of Helleriella , eleven of Isochilus , six of Nemaconia , and two of Ponera , and a geographic and taxonomic database was generated. ENM were constructed with MaxEnt 3.3; and we determine areas with highest species richness and endemism with Biodiverse 4.3. Mexico is the richest country with 21 species, followed by Guatemala with nine. The more widely distributed species are: Isochilus linearis (Jacq.) R.Br, and Nemaconia striata (Lindl.) Van den Berg, Salazar & Soto Arenas; I . oaxacanus Salazar & Soto Arenas is endemic to Mexican state of Oaxaca and N . dressleriana (Soto Arenas) van den Berg, Salazar & Soto Arenas of Morelos. The cells with higher occurrence richness and occurrence weighted endemism were located in Chiapas Highlands, and the higher occurrence of corrected weighted endemism is located in Transmexican Volcanic Belt, considered the nucleus of the Mexican Transition Zone. On the other hand, the cells with greater ENM richness and ENM weighted endemism were located in Sierra Madre del Sur, and the higher ENM corrected weighted endemism in Sierra Madre Oriental. It is suggested to change the status of the regions Cañón del Zopilote and El Tlacuache from RTPs to ANPs.

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.