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Update 2021-08-31

This reflects some of the early activity steps that will be built upon as the work progresses:

• Developed a methodological framework to generate spectral heterogeneity indices (Rao’s Q and Shannon diversities) using MODIS satellite-based vegetation indices (NDVI and EVI).
• Google Earth Engine (GEE) platform was used to extract MOD13A1 NDVI and EVI 16-day composite data at 500 m spatial resolution for July month. These indices were used as an input for the estimation of Shannon (α) and Rao’s Q (β) diversities using R-package function spectralrao().
• Generated spatial database of tree productivity for > 12,000 permanent 400 m² forest plots across southern Quebec using tree biomass increments, which was collected between two different field surveys. Tree biomass was computed for individual species within each sample plot. All plots include approximately 400,000 trees covering 50 types of species, and representative of the deciduous, mixed, and boreal forests of North America.
• NDVI and EVI values were extracted using the GEE platform for each sample plot over the duration of the field survey and included as new attributes to the spatial database.

Update 2022-01-27

1. In this study, we aim to understand changes in the relationship between biodiversity and ecosystem function (BEF) at different spatial grains and how the BEF slope relationship varies with scales when satellite data are combined with in situ data. The study combines permanent forest plot records with remote sensing data.
2.  We selected a southern Quebec forest survey dataset from 1970 onwards, which comprises temperate, mixed, and boreal woods in eastern Canada, and is located between 45N and 51N parallels.
3. We selected a total of 12,324 pairs of surveys (two successive measurements of the same plot for two different times) that satisfied our criteria for 46 tree species and estimated tree productivity using yearly aboveground biomass increments calculated using tree diameter at breast height.
4. Satellite derived NDVI and in-situ based tree productivity, alpha (species richness) and beta diversities (Sørensen and Jaccard indices) were computed at varying scales (15×15, 20×20, 25×25, 30×30, 35×35, 40×40, 45×45 and 50×50 km2).
5. We expect nonlinear BEF slope relationships with tree productivity in distinct ecoregions of southern Quebec based on remote sensing-derived spectral heterogeneity and in-situ derived alpha and beta diversities.

Background:  Theory and models predict the strength of the relationship between biodiversity and ecosystem functioning (BEF) to vary with spatial scale. In this study, we are testing this understanding by assessing how changes in tree diversity mediate primary production at different spatial grains. We are applying spectral variation methods to MODIS remote sensing data to estimate tree diversity (alpha and beta) at these different spatial grains. We corroborate these estimates of diversity with in situ measures of tree diversity taken from thousands of permanent plots distributed across southern Quebec. Next, we quantify the slope of the correlation (regression estimate) between these spectral diversity estimates (Rao’s Q and Shannon indices) with measures of primary production (NDVI and EVI) at those scales. We obtain different slope estimates at different spatial grains. We then assess the nonlinear functional form describing how BEF slope values change across the different scales and explain this as turnover in the distribution of plant diversity and primary production across geographic gradients in topography, soils and climate. We expect that remote sensing derived estimates of spectral variation will be a powerful way to quickly assess how biodiversity change at different scales may alter ecosystem production across different ecoregions around the world.