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Jiménez-López, D. A., M. J. Carmona-Higuita, G. Mendieta-Leiva, R. Martínez-Camilo, A. Espejo-Serna, T. Krömer, N. Martínez-Meléndez, and N. Ramírez-Marcial. 2023. Linking different resources to recognize vascular epiphyte richness and distribution in a mountain system in southeastern Mexico. Flora: 152261. https://doi.org/10.1016/j.flora.2023.152261

Mesoamerican mountains are important centers of endemism and diversity of epiphytes. The Sierra Madre of Chiapas in southeastern Mexico is a mountainous region of great ecological interest due to its high biological richness. We present the first checklist of epiphytes for this region based on a compilation of various information sources. In addition, we determined the conservation status for each species based on the Mexican Official Standard (NOM-059-SEMARNAT-2010), endemism based on geopolitical boundaries, spatial completeness with inventory completeness index, richness distribution with range maps, and the relationship between climatic variables (temperature and rainfall) with species richness using generalized additive models. Our dataset includes 9,799 records collected between 1896-2017. Our checklist includes 708 epiphytes within 160 genera and 26 families; the most species-rich family was Orchidaceae (355 species), followed by Bromeliaceae (82) and Polypodiaceae (79). There were 74 species within a category of risk and 59 species considered endemic. Completeness of epiphyte richness suggests that sampling is still largely incomplete, particularly in the lower parts of the mountain system. Species and family range maps show the highest richness at high elevations, while geographically richness increases towards the southeast. Epiphyte richness increases with increased rainfall, although a unimodal pattern was observed along the temperature gradient with a species richness peak between 16-20 C°. The Sierra Madre of Chiapas forms a refuge to more than 40% of all epiphytes reported for Mexico and its existing network of protected areas overlaps with the greatest epiphyte richness.

Reichgelt, T., A. Baumgartner, R. Feng, and D. A. Willard. 2023. Poleward amplification, seasonal rainfall and forest heterogeneity in the Miocene of the eastern USA. Global and Planetary Change 222: 104073. https://doi.org/10.1016/j.gloplacha.2023.104073

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

Borges, C., A. Bertassoni, L. F. Liévano‐Latorre, T. A. F. Dória, R. Santos‐Silva, F. Miranda, and E. Barreto. 2022. Safeguarding sloths and anteaters in the future: Priority areas for conservation under climate change. Biotropica. https://doi.org/10.1111/btp.13185

Sloths and anteaters form the monophyletic order Pilosa, which is currently represented by only 16 extant species distributed exclusively in the Neotropics. This present‐day low species richness is an inheritance of the Pleistocene megafaunal extinctions, where over 65 Pilosa species known from the fossil record went extinct. The large number of species lost in the recent past suggests that this group is greatly vulnerable to extinction. Here, we propose long‐term priority conservation areas for the order Pilosa, considering different future climate change scenarios, biotic stability, and the multiple dimensions of the group's biodiversity, such as species richness, species endemism, and phylogenetic diversity. Projections of species distribution for future scenarios show increased fragmentation and clear habitat loss as the Amazon Forest is replaced by savanna‐like habitats. Conservation solutions were highly congruent for the different dimensions of biodiversity, with priority areas emerging mainly in the Atlantic Forest, Amazonian wetlands, highlands of Ecuador, and the Central American isthmus. Expanding the currently protected areas network by 6% with the proposed priority areas, independently of which future climatic scenario is considered, can increase sloths and anteaters' coverage in the future by 12%. As a group of high phylogenetic and ecological importance, future conservation planning should deliberately aim to protect areas favorable to Pilosa, especially given the current scenario of environmental dismantling and neglect of critical Neotropical biomes.

Ecke, F., B. A. Han, B. Hörnfeldt, H. Khalil, M. Magnusson, N. J. Singh, and R. S. Ostfeld. 2022. Population fluctuations and synanthropy explain transmission risk in rodent-borne zoonoses. Nature Communications 13. https://doi.org/10.1038/s41467-022-35273-7

Population fluctuations are widespread across the animal kingdom, especially in the order Rodentia, which includes many globally important reservoir species for zoonotic pathogens. The implications of these fluctuations for zoonotic spillover remain poorly understood. Here, we report a global empirical analysis of data describing the linkages between habitat use, population fluctuations and zoonotic reservoir status in rodents. Our quantitative synthesis is based on data collated from papers and databases. We show that the magnitude of population fluctuations combined with species’ synanthropy and degree of human exploitation together distinguish most rodent reservoirs at a global scale, a result that was consistent across all pathogen types and pathogen transmission modes. Our spatial analyses identified hotspots of high transmission risk, including regions where reservoir species dominate the rodent community. Beyond rodents, these generalities inform our understanding of how natural and anthropogenic factors interact to increase the risk of zoonotic spillover in a rapidly changing world. Many rodent species are known as hosts of zoonotic pathogens, but the ecological conditions that trigger spillover are not well-understood. Here, the authors show that population fluctuations and association with human-dominated habitats explain the zoonotic reservoir status of rodents globally.

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. https://doi.org/10.1016/j.indcrop.2022.115838

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. https://doi.org/10.1016/j.biocon.2022.109677

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.

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. https://doi.org/10.1029/2022pa004419

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.

Reichgelt, T., D. R. Greenwood, S. Steinig, J. G. Conran, D. K. Hutchinson, D. J. Lunt, L. J. Scriven, and J. Zhu. 2022. Plant Proxy Evidence for High Rainfall and Productivity in the Eocene of Australia. Paleoceanography and Paleoclimatology 37. https://doi.org/10.1029/2022pa004418

During the early to middle Eocene, a mid‐to‐high latitudinal position and enhanced hydrological cycle in Australia would have contributed to a wetter and “greener” Australian continent where today arid to semi‐arid climates dominate. Here, we revisit 12 southern Australian plant megafossil sites from the early to middle Eocene to generate temperature, precipitation and seasonality paleoclimate estimates, net primary productivity (NPP) and vegetation type, based on paleobotanical proxies and compare to early Eocene global climate models. Temperature reconstructions are uniformly subtropical (mean annual, summer, and winter mean temperatures 19–21 °C, 25–27 °C and 14–16 °C, respectively), indicating that southern Australia was ∼5 °C warmer than today, despite a >20° poleward shift from its modern geographic location. Precipitation was less homogeneous than temperature, with mean annual precipitation of ∼60 cm over inland sites and >100 cm over coastal sites. Precipitation may have been seasonal with the driest month receiving 2–7× less than mean monthly precipitation. Proxy‐model comparison is favorable with an 1680 ppm CO2 concentration. However, individual proxy reconstructions can disagree with models as well as with each other. In particular, seasonality reconstructions have systemic offsets. NPP estimates were higher than modern, implying a more homogenously “green” southern Australia in the early to middle Eocene, when this part of Australia was at 48–64 °S, and larger carbon fluxes to and from the Australian biosphere. The most similar modern vegetation type is modern‐day eastern Australian subtropical forest, although distance from coast and latitude may have led to vegetation heterogeneity.

Colli-Silva, M., J. R. Pirani, and A. Zizka. 2022. Ecological niche models and point distribution data reveal a differential coverage of the cacao relatives (Malvaceae) in South American protected areas. Ecological Informatics 69: 101668. https://doi.org/10.1016/j.ecoinf.2022.101668

For many regions, such as in South America, it is unclear how well the existent protected areas network (PAs) covers different taxonomic groups and if there is a coverage bias of PAs towards certain biomes or species. Publicly available occurrence data along with ecological niche models might help to overcome this gap and to quantify the coverage of taxa by PAs ensuring an unbiased distribution of conservation effort. Here, we use an occurrence database of 271 species from the cacao family (Malvaceae) to address how South American PAs cover species with different distribution, abundance, and threat status. Furthermore, we compared the performance of online databases, expert knowledge, and modelled species distributions in estimating species coverage in PAs. We found 79 species from our survey (29% of the total) lack any record inside South American PAs and that 20 out of 23 species potentially threatened with extinction are not covered by PAs. The area covered by South American PAs was low across biomes, except for Amazonia, which had a relative high PA coverage, but little information on species distribution within PA available. Also, raw geo-referenced occurrence data were underestimating the number of species in PAs, and projections from ecological niche models were more prone to overestimating the number of species represented within PAs. We discuss that the protection of South American flora in heterogeneous environments demand for specific strategies tailored to particular biomes, including making new collections inside PAs in less collected areas, and the delimitation of more areas for protection in more known areas. Also, by presenting biasing scenarios of collection effort in a representative plant group, our results can benefit policy makers in conserving different spots of tropical environments highly biodiverse.

Chevalier, M. 2022. <i>crestr</i>: an R package to perform probabilistic climate reconstructions from palaeoecological datasets. Climate of the Past 18: 821–844. https://doi.org/10.5194/cp-18-821-2022

Abstract. Statistical climate reconstruction techniques are fundamental tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (or PDFs) can be used in various environments and with different climate proxies because they rely on elementary calibration data (i.e. modern geolocalised presence data). However, the difficulty of accessing and curating these calibration data and the complexity of interpreting probabilistic results have often limited their use in palaeoclimatological studies. Here, I introduce a new R package (crestr) to apply the PDF-based method CREST (Climate REconstruction SofTware) on diverse palaeoecological datasets and address these problems. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) associated with an extensive range of climate variables (20 terrestrial and 19 marine variables) that enables its use in most terrestrial and marine environments. Private data collections can also be used instead of, or in combination with, the provided calibration dataset. The package includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment and thus be more easily integrated with existing workflows. It is hoped that crestr will be used to produce the much-needed quantified climate reconstructions from the many regions where they are currently lacking, despite the availability of suitable fossil records. To support this development, the use of the package is illustrated with a step-by-step replication of a 790 000-year-long mean annual temperature reconstruction based on a pollen record from southeastern Africa.