Science Enabled by Specimen Data

Mai, J., and G. Liu. 2023. Modeling and predicting the effects of climate change on cotton-suitable habitats in the Central Asian arid zone. Industrial Crops and Products 191: 115838.

Climate change has significantly affected global agricultural production, particularly in arid zones of Central Asia. Thus, we analyzed changes in the habitat suitability of cotton in Central Asia under various shared socioeconomic pathway (SSP) scenarios during 2021–2060. The results showed that the average minimum temperature in April, precipitation seasonality, and distance to rivers were the main environmental factors influencing the suitable distribution of cotton. Suitable habitats expanded toward the north and east, reaching a maximum net increase of 10.85 × 104 km2 under the SSP5–8.5 scenario during 2041–2060, while habitats in the southwestern area showed a contracting trend. The maximum decreased and increased habitats were concentrated at approximately 68°E and 87°E, respectively. In addition, their latitudinal distributions were concentrated at approximately 40°N and 44°N. The longitudinal and latitudinal dividing lines of increased and decreased habitats were 69°E and 41°N, respectively. Habitats at the same altitude showed an increasing trend, excluding the elevation range of 125–325 m. Habitat shifts could exacerbate spatial conflicts with forest/grassland and natural reserves. The maximum spatial overlap between them was observed under the SSP5–8.5 scenario during 2041–2060. These findings could provide scientific evidence for rational cotton cultivation planning in global arid zones.

Amaral, D. T., I. A. S. Bonatelli, M. Romeiro-Brito, E. M. Moraes, and F. F. Franco. 2022. Spatial patterns of evolutionary diversity in Cactaceae show low ecological representation within protected areas. Biological Conservation 273: 109677.

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.

Bernal‐Escobar, M., D. Zuleta, and K. J. Feeley. 2022. Changes in the climate suitability and growth rates of trees in eastern North America. Ecography 2022.

According to the ‘fitness‐suitability' hypothesis, ongoing changes in climate are expected to affect habitat suitability and hence species' fitness. In trees, differences in fitness may manifest as changes in growth rates, which will alter carbon uptake. Using tree‐ring data, we calculated > 1.5 million annual stem growth rate estimates (standardized for tree size) for 15 677 trees representing 37 species from 558 populations throughout eastern North America. We used collections data and species distribution models to estimate each population's climatic suitability from 1900 to 2010. We then assessed the relationships between growth, suitability and time using linear mixed‐effects models. We found that stem growth rates decreased significantly through time independent of changes in climate suitability and that relationships between growth rates and climate suitability were highly variable across species. Contrary to expectations, we found that growth rates were negatively correlated with species' climate suitability, a relationship that was consistent over time for gymnosperms and became more negative through time for angiosperms. These results may suggest that stem growth rates are not a good proxy for fitness and/or that unidentified factors may be slowing tree growth and outweighing any potential benefits of climate change and increasing atmospheric CO2 concentrations. Regardless of the cause, this finding indicates that we should not count on the increased growth of eastern North American trees to help offset anthropogenic carbon emissions.

Buckland, C. E., A. J. A. C. Smith, and D. S. G. Thomas. 2022. A comparison in species distribution model performance of succulents using key species and subsets of environmental predictors. Ecology and Evolution 12.

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.

Gori, B., T. Ulian, H. Y. Bernal, and M. Diazgranados. 2022. Understanding the diversity and biogeography of Colombian edible plants. Scientific Reports 12.

Despite being the second most biodiverse country in the world, hosting more than 7000 useful species, Colombia is characterized by widespread poverty and food insecurity. Following the growing attention in Neglected and Underutilized Species, the present study will combine spatial and taxonomic analysis to unveil their diversity and distribution, as well as to advocate their potential as key resources for tackling food security in the country. The cataloguing of Colombian edible plants resulted in 3805 species. Among these, the most species-rich genera included Inga, Passiflora, Miconia, Solanum, Pouteria , Protium , Annona and Bactris . Biogeographic analysis revealed major diversity hotspots in the Andean humid forests by number of records, species, families, and genera. The departments of Antioquia, Boyacá, Meta, and Cundinamarca ranked first both in terms of number of unique georeferenced records and species of edible plants. Significant information gaps about species distribution were detected in the departments of Cesar, Sucre, Atlántico, Vichada, and Guainía, corresponding to the Caribe and Llanos bioregions, indicating the urgent need for focusing investigation in these areas. Furthermore, a significant level of geographic specificity was found in edible plant species’ distributions between 13 different bioregions and 33 departments, hinting the adoption of tailorized prioritisation protocols for the conservation and revitalization of such resources at the local level.

Ramirez-Villegas, J., C. K. Khoury, H. A. Achicanoy, M. V. Diaz, A. C. Mendez, C. C. Sosa, Z. Kehel, et al. 2022. State of ex situ conservation of landrace groups of 25 major crops. Nature Plants 8: 491–499.

Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation. By analysing the state of representation of traditional varieties of 25 major crops in ex situ repositories, this study demonstrates conservation progress made over more than a half-century and identifies the gaps remaining to be filled.

Pang, S. E. H., Y. Zeng, J. D. T. Alban, and E. L. Webb. 2022. Occurrence–habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions B. Leroy [ed.],. Diversity and Distributions 28: 1327–1343.

Aims Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence–habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past and recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence–habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence–habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of ARCs, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximize the temporal range of anthropogenic predictors, exclude mismatched occurrences and test for residual data misrepresentations.

Williams, C. J. R., D. J. Lunt, U. Salzmann, T. Reichgelt, G. N. Inglis, D. R. Greenwood, W. Chan, et al. 2022. African Hydroclimate During the Early Eocene From the DeepMIP Simulations. Paleoceanography and Paleoclimatology 37.

The early Eocene (∼56‐48 million years ago) is characterised by high CO2 estimates (1200‐2500 ppmv) and elevated global temperatures (∼10 to 16°C higher than modern). However, the response of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with sparse data coverage (e.g. Africa). Here we present a study of African hydroclimate during the early Eocene, as simulated by an ensemble of state‐of‐the‐art climate models in the Deep‐time Model Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre‐industrial simulations and modern observations suggests that model biases are model‐ and geographically dependent, however these biases are reduced in the model ensemble mean. A comparison between the Eocene simulations and the pre‐industrial suggests that there is no obvious wetting or drying trend as the CO2 increases. The results suggest that changes to the land sea mask (relative to modern) in the models may be responsible for the simulated increases in precipitation to the north of Eocene Africa. There is an increase in precipitation over equatorial and West Africa and associated drying over northern Africa as CO2 rises. There are also important dynamical changes, with evidence that anticyclonic low‐level circulation is replaced by increased south‐westerly flow at high CO2 levels. Lastly, a model‐data comparison using newly‐compiled quantitative climate estimates from palaeobotanical proxy data suggests a marginally better fit with the reconstructions at lower levels of CO2.

Sluiter, I. R. K., G. R. Holdgate, T. Reichgelt, D. R. Greenwood, A. P. Kershaw, and N. L. Schultz. 2022. A new perspective on Late Eocene and Oligocene vegetation and paleoclimates of South-eastern Australia. Palaeogeography, Palaeoclimatology, Palaeoecology 596: 110985.

We present a composite terrestrial pollen record of latest Eocene through Oligocene (35.5–23 Ma) vegetation and climate change from the Gippsland Basin of south-eastern Australia. Climates were overwhelmingly mesothermic through this time period, with mean annual temperature (MAT) varying between 13 and 18 °C, with an average of 16 °C. We provide evidence to support a cooling trend through the Eocene–Oligocene Transition (EOT), but also identify three subsequent warming cycles through the Oligocene, leading to more seasonal climates at the termination of the Epoch. One of the warming episodes in the Early Oligocene appears to have also occurred at two other southern hemisphere sites at the Drake Passage as well as off eastern Tasmania, based on recent research. Similarities with sea surface temperature records from modern high southern latitudes which also record similar cycles of warming and cooling, are presented and discussed. Annual precipitation varied between 1200 and 1700 mm/yr, with an average of 1470 mm/yr through the sequence. Notwithstanding the extinction of Nothofagus sg. Brassospora from Australia and some now microthermic humid restricted Podocarpaceae conifer taxa, the rainforest vegetation of lowland south-eastern Australia is reconstructed to have been similar to present day Australian Evergreen Notophyll Vine Forests existing under the sub-tropical Köppen-Geiger climate class Cfa (humid subtropical) for most of the sequence. Short periods of cooler climates, such as occurred through the EOT when MAT was ~ 13 °C, may have supported vegetation similar to modern day Evergreen Microphyll Fern Forest. Of potentially greater significance, however, was a warm period in the Early to early Late Oligocene (32–26 Ma) when MAT was 17–18 °C, accompanied by small but important increases in Araucariaceae pollen. At this time, Araucarian Notophyll/Microphyll Vine Forest likely occurred regionally.

Rodrigues, A. V., G. Nakamura, V. G. Staggemeier, and L. Duarte. 2022. Species misidentification affects biodiversity metrics: Dealing with this issue using the new R package naturaList. Ecological Informatics 69: 101625.

Biodiversity databases are increasingly available and have fostered accelerated advances in many disciplines within ecology and evolution. However, the quality of the evidence generated depends critically on the quality of the input data, and species misidentifications are present in virtually any o…