Science Rendue Possible

Goicolea, T., A. Adde, O. Broennimann, J. I. García‐Viñas, A. Gastón, M. José Aroca‐Fernández, A. Guisan, and R. G. Mateo. 2024. Spatially‐nested hierarchical species distribution models to overcome niche truncation in national‐scale studies. Ecography. https://doi.org/10.1111/ecog.07328

Spatial truncation in species distribution models (SDMs) might cause niche truncation and model transferability issues, particularly when extrapolating models to non‐analog environmental conditions. While broad calibration extents reduce truncation issues, they usually overlook local ecological factors driving species distributions at finer resolution. Spatially‐nested hierarchical SDMs (HSDMs) address truncation by merging (a) a global model calibrated with broadly extended, yet typically low‐resolution, basic, and imprecise data; and (b) a regional model calibrated with spatially restricted but more precise and reliable data. This study aimed to examine HSDMs' efficacy to overcome spatial truncation in national‐scale studies. We compared two hierarchical strategies (‘covariate', which uses the global model output as a covariate for the regional model, and ‘multiply', which calculates the geometric mean of the global and regional models) and a non‐hierarchical strategy. The three strategies were compared in terms of niche truncation, environmental extrapolation, model performance, species' predicted distributions and shifts, and trends in species richness. We examined the consistency of the results over two study areas (Spain and Switzerland), 108 tree species, and four future climate scenarios. Only the non‐hierarchical strategy was susceptible to niche truncation, and environmental extrapolation issues. Hierarchical strategies, particularly the ‘covariate' one, presented greater model accuracy than non‐hierarchical strategies. The non‐hierarchical strategy predicted the highest overall values and the lowest decreases over time in species distribution ranges and richness. Differences between strategies were more evident in Switzerland, which was more affected by niche truncation issues. Spain was more negatively affected by climate change and environmental extrapolation. The ‘covariate' strategy exhibited higher model performance than the ‘multiply' one. However, uncertainties regarding model temporal transferability advocate for adopting and further examining multiple hierarchical approaches. This research underscores the importance of adopting spatially‐nested hierarchical SDMs given the compromised reliability of non‐hierarchical approaches due to niche truncation and extrapolation issues.

Bürger, M., and J. Chory. 2024. A potential role of heat‐moisture couplings in the range expansion of Striga asiatica. Ecology and Evolution 14. https://doi.org/10.1002/ece3.11332

Parasitic weeds in the genera Orobanche, Phelipanche (broomrapes) and Striga (witchweeds) have a devastating impact on food security across much of Africa, Asia and the Mediterranean Basin. Yet, how climatic factors might affect the range expansion of these weeds in the context of global environmental change remains unexplored. We examined satellite‐based environmental variables such as surface temperature, root zone soil moisture, and elevation, in relation to parasitic weed distribution and environmental conditions over time, in combination with observational data from the Global Biodiversity Information Facility (GBIF). Our analysis reveals contrasting environmental and altitude preferences in the genera Striga and Orobanche. Asiatic witchweed (Striga asiatica), which infests corn, rice, sorghum, and sugar cane crops, appears to be expanding its range in high elevation habitats. It also shows a significant association with heat‐moisture coupling events, the frequency of which is rising in such environments. These results point to geographical shifts in distribution and abundance in parasitic weeds due to climate change.

Tiwary, R., P. P. Singh, D. Adhikari, M. D. Behera, and S. K. Barik. 2024. Vulnerability assessment of Taxus wallichiana in the Indian Himalayan Region to future climate change using species niche models and global climate models under future climate scenarios. Biodiversity and Conservation. https://doi.org/10.1007/s10531-024-02859-0

Climate change is a major threat to biodiversity as many species are facing the risk of extinction due to their inability to adapt to the changes in temperature, precipitation, and other environmental variables. The impact of climate change on the habitat distribution of Taxus wallichiana , a medicinally important endangered tree species, has not been studied specifically for the Indian Himalayan region (IHR). We assessed the vulnerability of the species to climate change using Ecological Niche Modeling (ENM) in conjunction with two latest global climate models (GCMs) viz., HadGEM3-GC31-LL and IPSL-CM6A-LR, under two future scenarios i.e. Shared Socioeconomic Pathways (SSPs) - SSP126 and SSP585 from Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report, 2023. Based on current distribution of the species and bioclimatic conditions., the Maxent-derived projections indicated significant reduction in its suitable habitat in IHR. Under the moderate scenario i.e. SSP126, suitable habitats are expected to decrease to 6,313,494 ha (10.62% of the total geographical area of IHR) with HadGEM3-GC31-LL and to 4,161,437 ha (7.00%) with IPSL-CM6A-LR from the present distribution area of 8,132,637 ha (13.68%). Under high-emission SSP585 scenario, the predicted habitat area is expected to decline to 4,833,212 ha (8.13%) with HadGEM3-GC31-LL and to 3,204,306 ha (5.39%) with IPSL-CM6A-LR.Annual mean temperature, isothermality, and annual precipitation were important environmental variables impacting the species distribution and models’ predictive capacity. The model outputs clearly predict a gloomy picture under both the future climate scenarios for T. wallichiana emphasizing the need for a targeted conservation effort for the species. .

Zhang, H., W. Guo, and W. Wang. 2023. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecology and Evolution 13. https://doi.org/10.1002/ece3.10747

How to effectively obtain species‐related low‐dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high‐dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

Zargar, S. A., A. H. Ganie, Z. A. Reshi, M. A. Shah, N. Sharma, and A. A. Khuroo. 2023. Oxalis corniculata L. (Oxalidaceae), an addition of an alien plant species to the flora of Ladakh, India. Vegetos. https://doi.org/10.1007/s42535-023-00612-6

Oxalis corniculata L. is recorded for the first time from the Trans-Himalayan region of Ladakh. The plant species has a conspicuous stem, obcordate leaf blades, and umbellate inflorescence with yellow flowers and cylindrical or narrowly ovoid fruits. As the plant is known to spread rapidly, it may become an aggressive weed of agricultural crops in Ladakh in near future. The taxonomic description, photographs and distribution map of O. corniculata are provided to facilitate its field identification in the region.

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.

Wilson Brown, M. K., and E. B. Josephs. 2023. Evaluating niche changes during invasion with seasonal models in Capsella bursa‐pastoris. American Journal of Botany. https://doi.org/10.1002/ajb2.16140

Premise Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess compare ecological niche models generated from full-year averages to seasonal models Methods In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal. Key Results We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons, but no monthly models are able to predict North American summer occurrences very well. Conclusions The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.

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. https://doi.org/10.1038/s41477-022-01144-8

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.

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.

Kumar, D., and S. Rawat. 2022. Modeling the effect of climate change on the distribution of threatened medicinal orchid Satyrium nepalense D. Don in India. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-20412-w

It is vital to understand the distribution area of a threatened plant species for its better conservation and management planning. Satyrium nepalense (family: Orchidaceae) is a threatened terrestrial orchid species with valuable medicinal and nutritional properties. The survival of S. nepalense in wild conditions has been challenged by increasing global surface temperature. Hence, understanding the impact of climate change on its potential distribution is crucial to conserve and restore this species. In present study, Maxent species distribution modeling algorithm was used to simulate the current distribution of S. nepalense in India and predict the possible range shift in projected future climate scenarios. A set of 19 bioclimatic variables from WorldClim database were used to predict the potential suitable habitats in current climatic condition and four Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios by integrating five General Circulation Models (GCMs) for future distribution modeling of species for the years 2050 and 2070. Furthermore, change analysis was performed to identify the suitable habitat in current and future climate for delineating range expansion (gain), contraction (loss), and stable (no change) habitats of species. The Maxent model predicted that ~ 2.38% of the geographical area in India is presently climatically suitable for S. nepalense . The key bioclimatic variables affecting the distribution of studied species were the mean temperature of warmest quarter, mean temperature of wettest quarter, precipitation of warmest quarter, and temperature seasonality. Under future climate change scenarios, the total suitable habitat of S. nepalense will increase slightly in the Himalayan region and likely to migrate towards northward, but in the Western Ghats region, the suitable areas will be lost severely. The net habitat loss under four RCP scenarios was estimated from 26 to 39% for the year 2050, which could further increase from 47 to 60% by the year 2070. The finding of the predictive Maxent modeling approach indicates that warming climates could significantly affect the potential habitats of S. nepalense and hence suitable conservation measures need to be taken to protect this threatened orchid species in wild conditions.