Poison ivy an unlikely hero in warding off exotic invaders?

Dozens of studies have looked at the effects of Japanese knotweed on natural communities in Europe and North America. Yet Bucknell University professor Chris Martine still felt there was something important to learn about what the plant was doing along the river in his own backyard.

“The more time I spent in the forests along the Susquehanna River, the more it seemed like something was really going wrong there,” said Martine. “In addition to the prevalence of this single invasive species, it looked like the very existence of these forests was under threat.”

What Martine noticed was similar to what local nature lovers and biologists with the Pennsylvania Natural Heritage Program were also starting to see: these forests, specifically those classified as Silver Maple Floodplain Forests, were not regenerating themselves where knotweed had taken a foothold.

In a new study published in the open access Biodiversity Data Journal, Martine and two recent Bucknell alumni conclude that Japanese knotweed has not only excluded nearly all of the native understory plant species in these forests, but it has prevented the trees already established in the canopy from leaving behind more of themselves.

“If you were to fly over these forests, or even look at a Google Earth image, you’d see a nice green canopy along the river consisting of mature silver maples, river birches, and sycamores,” explained Martine. “But below that canopy there is almost nothing for tens of feet before you reach an eight-to-twelve-foot-tall thicket of knotweed. Few new trees have been able to grow through that in the last 50-60 years and our surveys found that seedlings of these species are quite rare.”

The authors suggest that as mature trees die of natural causes over the next several decades and are not replaced, these systems will shift from tree-dominated riverbank habitats to “knotweed-dominated herbaceous shrublands” incapable of supporting a rich diversity of insects, birds, and other wildlife. Loss of trees in these habitats could likely also lead to riverbank erosion and increase the severity of flood events.

The few places where knotweed has not taken over offer a bit of hope, however, from an unlikely hero: poison-ivy, which Martine calls “perhaps the least popular plant in America.”

“What we see in the data is that poison-ivy often trades understory dominance with knotweed. That is, when knotweed isn’t the big boss, poison-ivy usually is. The difference is that whereas knotweed knocks everyone else out of the system, poison-ivy is more of a team player. Many other native plants can co-occur with it and it even seems to create microhabitats that help tree seedlings get established.”

The prevalence of poison-ivy in these sites didn’t go unnoticed by undergraduate Anna Freundlich, who collected most of the plant community data — more than 1,000 data points — in a single summer as a research fellow.

“Anna developed a pretty serious methodology for avoiding a poison-ivy rash that included long sleeves, long pants, gloves, duct tape, and an intense wash-down protocol,” said her research advisor, “and even after crawling through the plant for weeks she managed to never once get a rash.”

Martine cautions against too much optimism regarding the chances of one itch-inducing native plant saving the day, however.

“Righting this ship is going to require eradicating knotweed from some of these sites, and that won’t be easy work. It will take some hard manual labor. But it’s worth doing if we want to avoid the imminent ecological catastrophe. These forests really can’t afford another half-century of us letting knotweed run wild.”

Freundlich is a now pursuing a Master’s degree in plant ecology at the University of Northern Colorado. Lead author Matt Wilson, a Bucknell Master’s student at the time of the study who analyzed the dataset, now works for the Friends of the Verde River in Cottonwood, AZ.

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Original source:

Wilson M, Freundlich A, Martine C (2017) Understory dominance and the new climax: Impacts of Japanese knotweed (Fallopia japonica) invasion on native plant diversity and recruitment in a riparian woodland. Biodiversity Data Journal 5: e20577. https://doi.org/10.3897/BDJ.5.e20577

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About Japanese knotweed:

Japanese knotweed is considered to be one of the toughest, most damaging and insidious plants in the world. Native to East Asia, the species has already established successfully in many parts throughout North America and Europe, where it can easily grow and invade private properties and homes. It is hardy enough to penetrate patios, house foundations and concrete. Given it spreads easily and can grow underground to a depth of 3 metres with a horizontal range of up to 7 metres, it is extremely difficult to eradicate and its treatment requires special attention. To find advice on recognition, hazards and treatment, you can check out The Ultimate Japanese Knotweed Guide.

Artificial neural networks could power up curation of natural history collections

Deep learning techniques manage to differentiate between similar plant families with up to 99 percent accuracy, Smithsonian researchers reveal

Millions, if not billions, of specimens reside in the world’s natural history collections, but most of these have not been carefully studied, or even looked at, in decades. While containing critical data for many scientific endeavors, most objects are quietly sitting in their own little cabinets of curiosity.

Thus, mass digitization of natural history collections has become a major goal at museums around the world. Having brought together numerous biologists, curators, volunteers and citizens scientists, such initiatives have already generated large datasets from these collections and provided unprecedented insight.

Now, a study, recently published in the open access Biodiversity Data Journal, suggests that the latest advances in both digitization and machine learning might together be able to assist museum curators in their efforts to care for and learn from this incredible global resource.

A team of researchers from the Smithsonian Department of BotanyData Science Lab, and Digitization Program Office recently collaborated with NVIDIA to carry out a pilot project using deep learning approaches to dig into digitized herbarium specimens.

Smithsonian researchers classifying digitized herbarium sheets.
Smithsonian researchers classifying digitized herbarium sheets.

Their study is among the first to describe the use of deep learning methods to enhance our understanding of digitized collection samples. It is also the first to demonstrate that a deep convolutional neural network–a computing system modelled after the neuron activity in animal brains that can basically learn on its own–can effectively differentiate between similar plants with an amazing accuracy of nearly 100%.

In the paper, the scientists describe two different neural networks that they trained to perform tasks on the digitized portion (currently 1.2 million specimens) of the United States National Herbarium.

The team first trained a net to automatically recognize herbarium sheets that had been stained with mercury crystals, since mercury was commonly used by some early collectors to protect the plant collections from insect damage. The second net was trained to discriminate between two families of plants that share a strikingly similar superficial appearance.

Sample herbarium specimen image of stained clubmoss
Sample herbarium specimen image of stained clubmoss.

The trained neural nets performed with 90% and 96% accuracy respectively (or 94% and 99% if the most challenging specimens were discarded), confirming that deep learning is a useful and important technology for the future analysis of digitized museum collections.

“The results can be leveraged both to improve curation and unlock new avenues of research,” conclude the scientists.

“This research paper is a wonderful proof of concept. We now know that we can apply machine learning to digitized natural history specimens to solve curatorial and identification problems. The future will be using these tools combined with large shared data sets to test fundamental hypotheses about the evolution and distribution of plants and animals,” says Dr. Laurence J. Dorr, Chair of the Smithsonian Department of Botany.

 

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Original source:

Schuettpelz E, Frandsen P, Dikow R, Brown A, Orli S, Peters M, Metallo A, Funk V, Dorr L (2017) Applications of deep convolutional neural networks to digitized natural history collections. Biodiversity Data Journal 5: e21139. https://doi.org/10.3897/BDJ.5.e21139

A decade of monitoring shows the dynamics of a conserved Atlantic tropical forest

Characterised with its immense biodiversity and high levels of endemism, the Atlantic Tropical Forest has been facing serious anthropogenic threats over the last several decades, demanding for such activities and their effects to be closely studied and monitored as part of the forest dynamics.

Cattle farming, expanding agricultural land areas and mining have reduced the Atlantic Forest to many small patches of vegetation. As a result, important ecosystem services, such as carbon stock, are steadily diminishing as the biomass decreases.

Brazilian researchers, led by Dr. Écio Souza Diniz, Federal University of Viçosa, spent a decade monitoring a semi-deciduous forest located in an ecological park in Southeast Brazil. Their observations are published in the open access Biodiversity Data Journal.

The team surveyed two stands within the forest to present variations in the structure and diversity of the plants over time, along with their dynamics, including mortality and establishment rates. They based their findings on the most abundant tree species occurring within each stand.

At the forest stands, the most abundant and important species for biomass accumulation are concluded to be trees larger than 20 cm in diameter, which characterise advanced successional stage within the forest.

“It is fundamental that opportunities to monitor conserved sites of the Atlantic Forest are taken, so that studies about their dynamics are conducted in order to better understand how they work,” note the scientists.

“The information from such surveys could improve the knowledge about the dynamics at anthropised and fragmented sites compared with protected areas.”

In order to encourage further research into the composition, diversity and structure of the Atlantic Forest over time and the subsequent contributions to the preservation of this threatened ecosystem, the authors made their data publicly available. The datasets, including species occurrences, are now openly accessible via the Global Biodiversity Information Facility(GBIF) and the biodiversity informatics data standard Darwin Core.

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Original source:

Diniz ES, Carvalho W, Santos R, Gastauer M, Garcia P, Fontes M, Coelho P, Moreira A, Menino G, Oliveira-Filho A (2017) Long-term monitoring of diversity and structure of two stands of an Atlantic Tropical Forest. Biodiversity Data Journal 5: e13564. https://doi.org/10.3897/BDJ.5.e13564

Effects of soil and drainage on the savanna vegetation in the northern Brazilian Amazonia

It is a well-known fact that environmental factors such as soil texture and drainage determine to a very large degree the vegetation appearance, richness and composition at any site. However, there has been little research on how these variables influence the flora in the marvellous savannas – large open areas characterised by a complex and unique network of natural resources and life forms.

Consequently, a Brazilian research team, led by Dr. Maria Aparecida de Moura Araújo, Universidade Federal de Roraima, investigated the hydro-edaphic conditions in the savanna areas in the northern Brazilian Amazonia. Their study, complete with an openly available and ready for re-use dataset, is published in the open access Biodiversity Data Journal.  

Image 1_Annonaceae_Xylopia aromatica_treeIn the course of the Program for Biodiversity Research, managed by the Brazilian government, the scientists sampled 20 permanent plots in two savanna areas in the state of Roraima, located in the northern of the Brazilian Amazon. As a result, the team reports a total of 128 plant species classified into 34 families from three savanna habitats with different levels of hydro-edaphic restrictions.

Amongst the various factors playing a role in the soil characteristics of the area, are the tectonic events and past climatic fluctuations which have occurred in the most recent period of the Cenozoic era. Paleo, as well as modern fires are likely to be other culprits for the specific conditions.

In conclusion, the authors suggest that the most restrictive savanna habitats – the wet grasslands, represent the home to less structurally complex plants, compared to the well-drained shrubby localities.

“The present study highlights the environmental heterogeneity and the biological importance of Roraima’s savanna regarding the conservation of natural resources from the Amazon,” say the scientists.

Image 2_Convolvulaceae_Merremia aturensis_herb“In addition, it points out the need for greater investment in floristic inventories associated with greater diversification of sites, since this entire ecosystem has been rapidly modified by agribusiness.”

Licensed under a Creative Commons License (CC-BY 4.0) and available in a Darwin Core Archive DwC-A format; the complete dataset is openly available via the Global Biodiversity Information Facility (GBIF).

 

Original source:
Araújo M, Rocha A, Miranda I, Barbosa R (2017) Hydro-edaphic conditions defining richness and species composition in savanna areas of the northern Brazilian Amazonia. Biodiversity Data Journal 5: e13829. https://doi.org/10.3897/BDJ.5.e13829