Citizen science plant observations encode global trait patterns

Global patterns of plant functional traits and their relationships to climate

Plant functional traits (FTs) determine growth, reproduction and survival strategies of plants adapted to their growth environment. Exploring global geographic patterns of FTs, their covariation and their relationships to climate are necessary steps towards better-founded predictions of how global environmental change will affect ecosystem composition. We compile an extensive global dataset for 16 FTs and characterise trait-trait and trait-climate relationships separately within non-woody, woody deciduous and woody evergreen plant groups, using multivariate analysis and generalised additive models (GAMs). Among the six major FTs considered, two dominant trait dimensions-representing plant size and the leaf economics spectrum (LES) respectively-are identified within all three groups. Size traits (plant height, diaspore mass) however are generally higher in warmer climates, while LES traits (leaf mass and nitrogen per area) are higher in drier climates. Larger leaves are associated principally with warmer winters in woody evergreens, but with wetter climates in non-woody plants. GAM-simulated global patterns for all 16 FTs explain up to three-quarters of global trait variation. Global maps obtained by upscaling GAMs are broadly in agreement with iNaturalist citizen-science FT data. This analysis contributes to the foundations for global trait-based ecosystem modelling by demonstrating universal relationships between FTs and climate.

Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power

Power analysis currently dominates sample size determination for experiments, particularly in grant and ethics applications. Yet, this focus could paradoxically result in suboptimal study design because publication biases towards studies with the largest effects can lead to the overestimation of effect sizes. In this Essay, we propose a paradigm shift towards better study designs that focus less on statistical power. We also advocate for (pre)registration and obligatory reporting of all results (regardless of statistical significance), better facilitation of team science and multi-institutional collaboration that incorporates heterogenization, and the use of prospective and living meta-analyses to generate generalizable results. Such changes could make science more effective and, potentially, more equitable, helping to cultivate better collaborations.

A Decade of Hidden Phytoplasmas Unveiled Through Citizen Science

Climate change is impacting agriculture in many ways, and a contribution from all is required to reduce the imminent losses related to it. Recently, it has been shown that citizen science could be a way to trace the impact of climate change. However, how can citizen science be applied in plant pathology? Here, using as an example a decade of phytoplasma-related diseases reported by growers, agronomists, and citizens in general, and confirmed by a government laboratory, we explored how to better value plant pathogen monitoring data. Through this collaboration, we found that in the last decade, 34 hosts have been affected by phytoplasmas; 9, 13, and 5 of these plants were, for the first time, reported phytoplasma hosts in eastern Canada, all of Canada, and worldwide, respectively. Another finding of great impact is the first report of a 'Candidatus Phytoplasma phoenicium'-related strain in Canada, while 'Ca. P. pruni' and 'Ca. P. pyri' were reported for the first time in eastern Canada. These findings will have a great impact on the management of phytoplasmas and their insect vectors. Using these insect-vectored bacterial pathogens, we show the need for new strategies that can allow fast and accurate communication between concerned citizens and those institutions confirming their observations.[Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Aliens on the Road: Surveying Wildlife Roadkill to Assess the Risk of Biological Invasion

Monitoring the presence and distribution of alien species is pivotal to assessing the risk of biological invasion. In our study, we carried out a worldwide review of roadkill data to investigate geographical patterns of biological invasions. We hypothesise that roadkill data from published literature can turn out to be a valuable resource for researchers and wildlife managers, especially when more focused surveys cannot be performed. We retrieved a total of 2314 works published until January 2022. Among those, only 41 (including our original data) fitted our requirements (i.e., including a total list of roadkilled terrestrial vertebrates, with a number of affected individuals for each species) and were included in our analysis. All roadkilled species from retrieved studies were classified as native or introduced (domestic, paleo-introduced, or recently released). We found that a higher number of introduced species would be recorded among roadkill in Mediterranean and Temperate areas with respect to Tropical and Desert biomes. This is definitely in line with the current knowledge on alien species distribution at the global scale, thus confirming that roadkill datasets can be used beyond the study of road impacts, such as for an assessment of different levels of biological invasions among different countries.

A quixotic view of spatial bias in modelling the distribution of species and their diversity

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Photographs as an essential biodiversity resource: drivers of gaps in the vascular plant photographic record

The photographic record is increasingly becoming an important biodiversity resource for primary research and conservation monitoring. However, globally, there are important gaps in this record even in relatively well-researched floras. To quantify the gaps in the Australian native vascular plant photographic record, we systematically surveyed 33 sources of well-curated species photographs, assembling a list of species with accessible and verifiable photographs, as well as the species for which this search failed. Of 21 077 Australian native species, 3715 lack a verifiable photograph across our 33 surveyed resources. There are three major geographic hotspots of unphotographed species in Australia, all far from current population centres. Many unphotographed species are small in stature or uncharismatic, and many are also recently described. The large number of recently described species without accessible photographs was surprising. There are longstanding efforts in Australia to organise the plant photographic record, but in the absence of a global consensus to treat photographs as an essential biodiversity resource, this has not become common practice. Many recently described species are small-range endemics and some have special conservation status. Completing the botanical photographic record across the globe will facilitate a virtuous feedback loop of more efficient identification, monitoring and conservation.

Applicability of Point- and Polygon-Based Vegetation Monitoring Data to Identify Soil, Hydrological and Climatic Driving Forces of Biological Invasions-A Case Study of Ailanthus altissima, Elaeagnus angustifolia and Robinia pseudoacacia

Invasive tree species are a significant threat to native flora. They modify the environment with their allelopathic substances and inhibit the growth of native species by shading, thus reducing diversity. The most effective way to control invasive plants is to prevent their spread which requires identifying the environmental parameters promoting it. Since there are several types of invasive plant databases available, determining which database type is the most relevant for investigating the occurrence of alien plants is of great importance. In this study, we compared the efficiency and reliability of point-based (EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS)) and polygon-based (National Forestry Database (NFD)) databases using geostatistical methods in ArcGIS software. We also investigated the occurrence of three invasive tree species (Ailanthus altissima, Elaeagnus angustifolia, and Robinia pseudoacacia) and their relationships with soil, hydrological, and climatic parameters such as soil organic matter content, pH, calcium carbonate content, rooting depth, water-holding capacity, distance from the nearest surface water, groundwater depth, mean annual temperature, and mean annual precipitation with generalized linear models in R-studio software. Our results show that the invasion levels of the tree species under study are generally over-represented in the LUCAS point-based vegetation maps, and the point-based database requires a dataset with a larger number of samples to be reliable. Regarding the polygon-based database, we found that the occurrence of the invasive species is generally related to the investigated soil and hydrological and climatic factors.