I hope it is OK to post such a vague question.
I am a PhD student currently working on a project studying the effectiveness of wildlife compensation measures (specifically, wildflower meadows in agricultural areas) in northern Germany. Originally our project focused exclusively on pollinators (bees, syrphid flies) and predatory invertebrates (spiders, carabids) - in addition to traditional biodiversity metrics we will also use the InVEST Pollinator model, and we intend to assess the effect on aphids in neighbouring fields next year.
We have also decided to investigate soil carbon, and have samples the soil at each site.
My hope is that we will find similar results to other studies - that these wildflower meadows / species rich grasslands sequester a great deal of carbon. We intend to compare to reference carbon values for local agricultural fields, and see if soil carbon is higher in meadows which have been restored for longer. Finally, we will build an InVEST carbon model for wildflower meadows across the state. We will also repeat our measurements next year.
However I would be very grateful for advice. Ideally, we want this data to help justify the usefulness of the scheme - we also want the farmers to know how much good they are doing in difficult circumstances.
Best case scenario, we want to help/advise the organisations and farmers we are working with on how to gain carbon credits or payments for ecosystem services. This should help the wildflower meadows to last much longer and support many new resored ecosystems.
How should I modify or expand my data gathering to support this goal? Does anyone have any general advice for us?