The land use legacy effect: looking back to see a path forward to improve management


Water quality has suffered as humans have increased nutrient inputs across the landscape. In many cases, management actions to reduce nutrient inputs have not been met with concomitant ecosystem responses. These missed expectations are partly due to the continued slow delivery of nutrient-enriched groundwater pre-dating input reductions resulting from management actions. Land use legacies as expressed through this time lag are important to quantify in order to adjust management expectations. We present a novel coupling of nitrogen source maps with groundwater transport times to create a high-resolution (120 m) fully distributed estimate of the timing and magnitude of groundwater nitrogen deliveries to surface water across Michigan’s Lower Peninsula. This new view of the landscape has been designed around common management timelines for: elected officials looking to make a difference for re-election (<5 years), career managers hoping to see the fruits of their labor (5–30 years), and advocacy groups whose work can span generations (>30 years). One striking result is that after 100 years, in our study area, approximately 50% of the nitrogen that enters the groundwater system remains in transit. This means that actions taken now may not show the expected lower nitrogen loads to receiving ecosystems for decades to centuries. We show that differences in groundwater travel times create a heterogeneous patchwork over which managers can prioritize actions to best match their targeted response times. Across the highest nitrogen inputs in our study region, less than 10% had short enough groundwater legacies to match the management timeline of most government and agency work. Agricultural practices (manure and chemical fertilizer) are the main nitrogen contributors across the top three management classes; however, human contributions through septic tank effluent and lawn fertilizers contribute 5%–8% of nitrogen.

In Environmental Research Letters
Luwen Wan
Luwen Wan
Postdoctoral Fellow

I am passionate about using data science, process-based modeling, remote sensing and machine/deep learning to explore how land use, climate change, and management impact water sustainability across diverse landscapes, and from watershed, regional to global scales.