Phenology and Seasonal Ecosystem Productivity in an Amazonian Floodplain Forest


Fonseca LDM, Dalagnol R, Malhi Y, Rifai SW, Costa GB, Silva TSF, Da Rocha HR, Tavares IB & Borma LS (2019) Phenology and Seasonal Ecosystem Productivity in an Amazonian Floodplain Forest. Remote Sensing, 11 (13), Art. No.: 1530.

everal studies have explored the linkages between phenology and ecosystem productivity across the Amazon basin. However, few studies have focused on flooded forests, which correspond to c.a. 14% of the basin. In this study, we assessed the seasonality of ecosystem productivity (gross primary productivity, GPP) from eddy covariance measurements, environmental drivers and phenological patterns obtained from the field (leaf litter mass) and satellite measurements (enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer/multi-angle implementation correction (MODIS/MAIAC)) in an Amazonian floodplain forest. We found that ecosystem productivity is limited by soil moisture in two different ways. During the flooded period, the excess of water limits GPP (Spearman’s correlation; rho = −0.22), while during non-flooded months, GPP is positively associated with soil moisture (rho = 0.34). However, GPP is maximized when cumulative water deficit (CWD) increases (rho = 0.81), indicating that GPP is dependent on the amount of water available. EVI was positively associated with leaf litter mass (Pearson’s correlation; r = 0.55) and with GPP (r = 0.50), suggesting a coupling between new leaf production and the phenology of photosynthetic capacity, decreasing both at the peak of the flooded period and at the end of the dry season. EVI was able to describe the inter-annual variations on forest responses to environmental drivers, which have changed during an observed El Niño-Southern Oscillation (ENSO) year (2015/2016).

tropical wetlands; floodplain phenology; eddy covariance; GPP; MODIS; MAIAC; seasonality

Remote Sensing: Volume 11, Issue 13

Publication date28/06/2019
Publication date online28/06/2019
Date accepted by journal24/06/2019
PublisherMDPI AG