scholarly journals Monitoring Plant Diversity to Support Agri-Environmental Schemes: Evaluating Statistical Models Informed by Satellite and Local Factors in Southern European Mountain Pastoral Systems

Diversity ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 8
Author(s):  
Antonio T. Monteiro ◽  
Paulo Alves ◽  
Claudia Carvalho-Santos ◽  
Richard Lucas ◽  
Mario Cunha ◽  
...  

The spatial monitoring of plant diversity in the endangered species-rich grasslands of European mountain pastoral systems is an important step for fairer and more efficient Agri-Environmental policy schemes supporting conservation. This study assessed the underlying support for a spatially explicit monitoring of plant species richness at parcel level (policy making scale) in Southern European mountain grasslands, with statistical models informed by Sentinel-2 satellite and environmental factors. Twenty-four grassland parcels were surveyed for species richness in the Peneda-Gerês National Park, northern Portugal. Using a multi-model inference approach, three competing hypotheses guided by the species-scaling theoretical framework were established: species–area (P1), species–energy (P2) and species–spectral heterogeneity (P3), each representing a candidate spatial pathway to predict species richness. To evaluate the statistical support of each spatial pathway, generalized linear models were fitted and model selection based on Akaike information criterion (AIC) was conducted. Later, the performance of the most supported spatial pathway(s) was assessed using a leave-one-out cross validation. A model guided by the species–energy hypothesis (P2) was the most parsimonious spatial pathway to monitor plant species richness in mountain grassland parcels (P2, AICc = 137.6, ∆AIC = 0.0, wi = 0.97). Species–area and species–spectral heterogeneity pathways (P1 and P3) were less statistically supported (ΔAICc values in the range 5.7–10.0). The underlying support of the species–energy spatial pathway was based on Sentinel-2 satellite data, namely on the near-infrared (NIR) green ratio in the spring season (NIR/Greenspring) and on its ratio of change between spring and summer (NIR/Greenchange). Both predictor variables related negatively to species richness. Grassland parcels with lower values of near-infrared (NIR) green ratio and lower seasonal amplitude presented higher species richness records. The leave-one-out cross validation indicated a moderate performance of the species–energy spatial pathway in predicting species richness in the grassland parcels covered by the dataset (R2 = 0.44, RMSE = 4.3 species, MAE = 3.5 species). Overall, a species–energy framework based on Sentinel 2 data resulted in a promising spatial pathway for the monitoring of species richness in mountain grassland parcels and for informing decision making on Agri-Environmental policy schemes. The near-infrared (NIR) green ratio and its change in time seems a relevant variable to deliver predictions for plant species richness and further research should be conducted on that.

2020 ◽  
Author(s):  
Petra Guy ◽  
Simon Smart ◽  
Colin Prentice

SummaryThe loss of plant biodiversity in Great Britain is a major concern, with a fifth of species endangered or vulnerable according to the latest IUCN Red List. The Government’s 25 Year Plan for the environment aims to halt this loss and build new habitats, including new woodlands. To ensure that biodiversity loss is halted in existing woodlands and gain is maximised in new ones, we need to better understand which drivers have been most influential in controlling biodiversity. Here we focus on vascular plant species’ richness.Previous attempts to explain plant species richness have mainly focussed on alpha diversity in a consistent, fixed unit area. Here, we additionally undertake a novel analysis of the effects of environmental heterogeneity and abiotic factors on species-area relationships derived from 16 randomly placed quadrats in each of 103 semi-natural, broad-leaved woodlands across Britain. Species-area relationships were examined at two scales (4m2 to 200m2 and 200m2 to 3200m2) to explore the relationship between the drivers of species richness and the exponent z, of the canonical species-area curve, S = cAz. We also explore the use of a new metric ζr, based on zeta diversity to quantify heterogeneity. Zeta diversity quantifies the number of species shared between multiple combinations of plots.Habitat heterogeneity increased species richness, as did the proximity of the woodlands to surrounding natural habitats. Higher levels of soil organic matter and the progression of woodlands to later successional stages, decreased species richness. Richness was also seen to have a unimodal response to soil acidity with a peak around pH 6. At the smaller scale, heterogeneity elements in the woodland such as riparian zones or coppicing led to an increase in the value of the exponent of the species area curve. At the larger scale, species turnover led to an increase in the exponent of the curves while succession led to a decrease. At both scales, soil organic matter content had a negative effect. ζr was found to be a significant and important variable and to affect both species richness and the slope of the species accumulation curves at larger scales.SynthesisHabitat heterogeneity measures included the presence of coppicing, open areas such as rides and riparian zones and the difference between species assemblages in different plots in the woodland. Results suggest that to maximize vascular plant diversity, woodlands should be managed for heterogeneity. In addition, the increase in richness with exposure to surrounding natural habitats suggests that woodlands benefit from being embedded in more benign habitats and further, that land management surrounding woodlands has a clear role to play in supporting biodiversity within woodlands. This is an area were Agri-environment schemes have an important role.


Weed Science ◽  
2009 ◽  
Vol 57 (3) ◽  
pp. 241-247 ◽  
Author(s):  
Fredric W. Pollnac ◽  
Bruce D. Maxwell ◽  
Fabian D. Menalled

The ecological significance of species diversity within agroecosystems has become a point of interest in recent years. Although the time and spatial scale at which diversity is measured may influence the interpretation of its functional importance, little research has been conducted on methodological approaches to assess the number and relative abundance of agricultural plant species. In this study, we (1) evaluated the applicability of the species-area curve to examine plant species richness and α and β diversity in conventional no-tillage and organically managed spring wheat systems, and (2) assessed temporal changes in plant species richness across systems. Measurements were obtained at three times during two growing seasons in experimental plots and at three times during one growing season on commercial farms in Montana. In accordance with previous studies, management system affected species richness and diversity. In eight of nine studied cases, we detected a positive relationship between species richness and sampled area. In these eight cases, intercepts (α diversity) were higher for the organic systems than for the conventional no-tillage systems. Slopes (β diversity) were higher for the organic system in six of nine cases studied. Species richness declined as the season progressed for both systems, with the organic systems consistently having more species than the conventional no-tillage systems. Despite differences in the species composition and between the experimental plots and commercial farm field size, the patterns of species richness and α and β diversity were relatively constant, suggesting that the processes responsible for the assembly of plant communities in agroecosystems of the Northern Great Plains are similar at a range of spatial scales.


2013 ◽  
Vol 41 (2) ◽  
pp. 261-273 ◽  
Author(s):  
Katharina Gerstner ◽  
Carsten F. Dormann ◽  
Tomáš Václavík ◽  
Holger Kreft ◽  
Ralf Seppelt

Ecography ◽  
2006 ◽  
Vol 29 (4) ◽  
pp. 541-548 ◽  
Author(s):  
Thomas Spiegelberger ◽  
Diethart Matthies ◽  
Heinz Müller-Schärer ◽  
Urs Schaffner

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