Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.11.06.621913

Too hot for the weeds? Exploring the impact of climate change in herbaceous Convolvulaceae in Cerrado and Mata Atlantica biomes (SE Brazil)

Barbosa, J. C. J.·Alves, F. V. S.·Moreira, A. L. C.·Loeuille, B.·Chatrou, L. W.·Simao-Bianchini, R.·Simoes, A. R. G.
View original source ↗Export metadata ↓

Abstract

AimWe investigated the potential resilience to climatic change of nine species of weeds in Convolvulaceae, using predictive spatial modeling across two contrasting biomes in Southeastern Brazil: Cerrado (=Savanna) and Mata Atlantica (=Atlantic Forest). We inferred future changes in distribution area, the climatic variables that will be most impactful, and the potential occurrence of future climatic refuges. LocationSoutheastern Brazil (Sao Paulo, Brazil). MethodsA total of 195, taxonomically vetted, distribution records were compiled for nine species of Convolvulaceae. Potential distribution areas were modelled in RStudio 1.3.1056 with R 3.6.3 using modleR; environmental layers used were the 19 bioclimatic variables with 30 seconds resolution. After a correlation analysis, four bioclimatic variables were selected for distribution modelling: Temperature Seasonality (BIO4), Mean Temperature of Wettest Quarter (BIO8), Precipitation of Wettest Month (BIO13) and Precipitation of Driest Quarter (BIO17). The species distribution modelling was performed using the Maxent algorithm for the present time (1960-1990) and for future projections (2050 and 2070), under two different scenarios of projections, moderate and pessimistic.. The final distribution models were generated through the selection of primary models with a minimum level of TSS (True Skills Statistics) equal to 0.7. ResultsThe analysed species demonstrated different levels of response to climatic change: Distimake aegyptius, D. dissectus, and Evolvulus pteurocaulon exhibited a gain in the climatic suitability range, regardless of the future scenarios. Other species, such as E. glomeratus, Ipomoea bonariensis, and I. alba showed a decline in climatic suitability range, more accentuated in the pessimistic scenario. Three species showed a positive response in a moderate future scenario, but a decline in the most extreme projection. Areas that may act, in the future, as climatic refuges for the displaced species are also highlighted, in view of being prioritised for conservation. Main ConclusionThis study reveals that climate change will have varied impacts on herbaceous species of Convolvulaceae occurring in the Brazilian Cerrado and Mata Atlantica biomes. Some species are likely to benefit from climate change, showing an increase in climatic suitability in both moderate and pessimistic future scenarios. Other species, however, are expected to experience a decline in suitable climatic conditions, in particular under the most pessimistic climatic scenario, and are more likely to be threatened in the future, due to the constriction of suitable habitats. The analysis also highlights that certain regions may serve as important climatic refuges for these species in the future. These findings emphasize the necessity for targeted conservation plans to protect the biodiversity of the Cerrado and Mata Atlantica phytogeographic domains and weed management strategies - not only in the present but also in future climatic conditions.

Explore related subjects

ecologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Barbosa, J. C. J., Alves, F. V. S., Moreira, A. L. C., Loeuille, B., Chatrou, L. W., Simao-Bianchini, R., Simoes, A. R. G.. 2024-11-08. Too hot for the weeds? Exploring the impact of climate change in herbaceous Convolvulaceae in Cerrado and Mata Atlantica biomes (SE Brazil). https://doi.org/10.1101/2024.11.06.621913

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Operationalising the context in regenerative agriculture: decision-making and farm variability

Soil degradation is a widespread challenge that requires a broad response at the individual farm level. To ensure effectivity, the practices should be tailored to the farm context: land manager objectives and farm specific challenges. These have however been difficult to quantify. Here we demonstrate that a workable farm context can be created based on a value survey, open satellite and soil data, and published models for vegetation gross primary productivity and soil erosion. Based on the findings, despite individual differences, farmers value profitability and operational efficiency, but also biodiversity and soil health. At least the regenerative farmers surveyed also value working for the greater good more than maintaining tradition or power. In spite of wide differences in farm production orientation, we also found that each farm also had a broad variation in individual fields GPP. Most fields have a stable GPP level, which is either high or low, and that there is a 2-3-fold difference between the weakest and best producing fields indicating the potential for improving GPP by improving the growing conditions on currently weak fields. In addition, soil loss was found to be highly concentrated in critical source areas, where 10% of the field area contributed to 50% of the soil loss. Overall, open data can be linked to modelling workflows to rapidly produce a decision-making context for farmers. This facilitates benchmarking and co-learning as well as enables land managers and advisors to identify the farm context for planning effective responses to soil degradation.

ecology↗
bioRxiv2026

Fly, land, listen: Autonomous intermittent locomotion enables scalable low-noise drone ecoacoustic surveys

Ecoacoustic monitoring is enabling scientists and land managers to monitor and manage biodiversity more effectively and cost-efficiently in the face of human pressures and rapidly changing climates. Currently, most ecoacoustic surveys use manually deployed static sensors to record data, limiting the scale and reach of surveying efforts. Here we present a proof-of-concept autonomous drone platform that can use intermittent locomotion to conduct ecoacoustic surveys using an onboard sensor. Our custom prototype is able to fly, navigate, and avoid obstacles autonomously, land at a pre-determined location, record audio from an onboard microphone whilst static, before taking off and moving to the next sampling site. Autonomous navigation and operation enable greater sampling flexibility, reach, and scalability. Furthermore, by recording audio only whilst landed, noise from the drone's rotors does not mask signals or disturb animals, simplifying signal processing and downstream ecological analyses. We conducted trials in a scrubland habitat at the Knepp Estate in West Sussex, where our prototype demonstrated successful autonomous navigation and obstacle avoidance. Furthermore, we found that avian biodiversity data collected from the drone platform was comparable to that from traditional static acoustic sensor deployments, and that vocalisation patterns were not significantly impacted by the noise of the drone arriving or leaving a site. While scaled deployments of our technology would require further technical and regulatory challenges to be solved, our first demonstration of autonomous intermittent robotics-assisted ecoacoustic surveys lays the foundations for more cost-effective and far-reaching biodiversity surveys, with transformative potential for conservation, agricultural management, biosecurity, and more.

ecology↗
bioRxiv2026

Do higher-order moments improve inference of population dynamics?

Fitting mathematical models of population dynamics to microbial time-series data allows us to estimate the ecological processes and interactions taking place in the microbiome. Repeated experiments of microbial systems yield replicates which slightly differ from each other. Some of this variability arises due to the fact that births and deaths occur at random. Most prior work focuses on fitting a deterministic mathematical model to the average across replicates. We use a stochastic model to fit the variability to the observed variability across replicates. Using a simulation-driven approach, we study the conditions under which our approach allows us to infer a larger fraction of ecological parameters correctly. We observe a substantial improvement in parameter inference. Lastly, our Bayesian approach not only allows us to incorporate prior information about the system, but also provides a distribution of parameters which conveys some idea of the uncertainty of the estimates.

ecology↗