Showing posts with label Wild Plants. Show all posts
Showing posts with label Wild Plants. Show all posts

Dec 10, 2022

How intensive agriculture turned a wild plant into a pervasive weed

New research in Science is showing how the rise of modern agriculture has turned a North American native plant, common waterhemp, into a problematic agricultural weed.

An international team led by researchers at the University of British Columbia (UBC) compared 187 waterhemp samples from modern farms and neighbouring wetlands with more than 100 historical samples dating as far back as 1820 that had been stored in museums across North America. Much like the sequencing of ancient human and neanderthal remains has resolved key mysteries about human history, studying the plant's genetic makeup over the last two centuries allowed the researchers to watch evolution in action across changing environments.

"The genetic variants that help the plant do well in modern agricultural settings have risen to high frequencies remarkably quickly since agricultural intensification in the 1960s," said first author Dr. Julia Kreiner, a postdoctoral researcher in UBC's Department of Botany.

The researchers discovered hundreds of genes across the weed's genome that aid its success on farms, with mutations in genes related to drought tolerance, rapid growth and resistance to herbicides appearing frequently. "The types of changes we're imposing in agricultural environments are so strong that they have consequences in neighbouring habitats that we'd usually think were natural," said Dr. Kreiner.

The findings could inform conservation efforts to preserve natural areas in landscapes dominated by agriculture. Reducing gene flow out of agricultural sites and choosing more isolated natural populations for protection could help limit the evolutionary influence of farms.

Common waterhemp is native to North America and was not always a problematic plant. Yet in recent years, the weed has become nearly impossible to eradicate from farms thanks to genetic adaptations including herbicide resistance.

"While waterhemp typically grows near lakes and streams, the genetic shifts that we're seeing allow the plant to survive on drier land and to grow quickly to outcompete crops," said co-author Dr. Sarah Otto, Killam University Professor at the University of British Columbia. "Waterhemp has basically evolved to become more of a weed given how strongly it's been selected to thrive alongside human agricultural activities."

Notably, five out of seven herbicide-resistant mutations found in current samples were absent from the historical samples. "Modern farms impose a strong filter determining which plant species and mutations can persist through time," said Dr. Kreiner. "Sequencing the plant's genes, herbicides stood out as one of the strongest agricultural filter determining which plants survive and which die."

Waterhemp carrying any of the seven herbicide resistant mutations have produced an average of 1.2 times as many surviving offspring per year since 1960 compared to plants that don't have the mutations.

Herbicide resistant mutations were also discovered in natural habitats, albeit at a lower frequency, which raises questions about the costs of these adaptations for plant life in non-agricultural settings. "In the absence of herbicide applications, being resistant can actually be costly to a plant, so the changes happening on the farms are impacting the fitness of the plant in the wild," said Dr. Kreiner.

Agricultural practices have also reshaped where particular genetic variants are found across the landscape. Over the last 60 years, a weedy southwestern variety has made an increasing progression eastward across North America, spreading their genes into local populations as a result of their competitive edge in agricultural contexts.

"These results highlight the enormous potential of studying historical genomes to understand plant adaptation on short timescales," says Dr. Stephen Wright, co-author and Professor in Ecology and Evolutionary Biology at the University of Toronto. "Expanding this research across scales and species will broaden our understanding of how farming and climate change are driving rapid plant evolution."

Read more at Science Daily

May 13, 2021

How smartphones can help detect ecological change

Leipzig/Jena/Ilmenau. Mobile apps like Flora Incognita that allow automated identification of wild plants cannot only identify plant species, but also uncover large scale ecological patterns. These patterns are surprisingly similar to the ones derived from long-term inventory data of the German flora, even though they have been acquired over much shorter time periods and are influenced by user behaviour. This opens up new perspectives for rapid detection of biodiversity changes. These are the key results of a study led by a team of researchers from Central Germany, which has recently been published in Ecography.

With the help of Artificial Intelligence, plant species today can be classified with high accuracy. Smartphone applications leverage this technology to enable users to easily identify plant species in the field, giving laypersons access to biodiversity at their fingertips. Against the backdrop of climate change, habitat loss and land-use change, these applications may serve another use: by gathering information on the locations of identified plant species, valuable datasets are created, potentially providing researchers with information on changing environmental conditions.

But is this information reliable -- as reliable as the information provided by data collected over long time periods? A team of researchers from the German Centre for Integrative Biodiversity Research (iDiv), the Remote Sensing Centre for Earth System Research (RSC4Earth) of Leipzig University (UL) and Helmholtz Centre for Environmental Research (UFZ), the Max Planck Institute for Biogeochemistry (MPI-BGC) and Technical University Ilmenau wanted to find an answer to this question. The researchers analysed data collected with the mobile app Flora Incognita between 2018 and 2019 in Germany and compared it to the FlorKart database of the German Federal Agency for Nature Conservation (BfN). This database contains long-term inventory data collected by over 5,000 floristic experts over a period of more than 70 years.

Mobile app uncovers macroecological patterns in Germany

The researchers report that the Flora Incognita data, collected over only two years, allowed them to uncover macroecological patterns in Germany similar to those derived from long-term inventory data of German flora. The data was therefore also a reflection of the effects of several environmental drivers on the distribution of different plant species.

However, directly comparing the two datasets revealed major differences between the Flora Incognita data and the long-term inventory data in regions with a low human population density. "Of course, how much data is collected in a region strongly depends on the number of smartphone users in that region," said last author Dr. Jana Wäldchen from MPI-BGC, one of the developers of the mobile app. Deviations in the data were therefore more pronounces in rural areas, except for well-known tourist destinations such as the Zugspitze, Germany's highest mountain, or Amrum, an island on the North Sea coast.

User behaviour also influences which plant species are recorded by the mobile app. "The plant observations carried out with the app reflect what users see and what they are interested in," said Jana Wäldchen. Common and conspicuous species were recorded more often than rare and inconspicuous species. Nonetheless, the large quantity of plant observations still allows a reconstruction of familiar biogeographical patterns. For their study, the researchers had access to more than 900,000 data entries created within the first two years after the app had been launched.

Automated species recognition bears great potential

The study shows the potential of this kind of data collection for biodiversity and environmental research, which could soon be integrated in strategies for long-term inventories. "We are convinced that automated species recognition bears much greater potential than previously thought and that it can contribute to a rapid detection of biodiversity changes," said first author Miguel Mahecha, professor at UL and iDiv Member. In the future, a growing number of users of apps like Flora Incognita could help detect and analyse ecosystem changes worldwide in real time.

The Flora Incognita mobile app was developed jointly by the research groups of Dr. Jana Wäldchen at MPI-BGC and the group of Professor Patrick Mäder at TU Ilmenau. It is the first plant identification app in Germany using deep neural networks (deep learning) in this context. Fed by thousands of plant images, that have been identified by experts, it can already identify over 4,800 plant species.

Read more at Science Daily