## 4 Conclusions  
In this study, we conducted a global assessment of bioclimatic controls affecting ecosystem productivity using both globally comprehensive productivity observations from satellite SIF retrievals and in situ GPP observations from sparse tower sites representing a diverse set of global biomes. Moisture and temperature related controls influencing productivity were defined using VPD, SM, and Tmin from global reanalysis data. The satellite based SIF observations were adjusted by PAR (SIF\({}_{\text{P}}\)) to distinguish temperature and moisture related controls on productivity apart from solar radiation effects. Our results show that the satellite SIF observations provide an effective proxy for ecosystem GPP and can be used with other ancillary information to clarify environmental controls driving spatial and seasonal variations in global vegetation growth. The SIF observations also provide an independent assessment and confirmation of prescribed environmental response characteristics used in global productivity model assessments.  
Satellite remote sensing based vegetation greenness indices have been used to monitor global vegetation cover and productivity for more than three decades. However, satellite data driven productivity models generally require additional information to define environmental restrictions on vegetation activity and growth. The effect of bio-climatic factors on plant phenology and productivity has been empirically analyzed before, but has been limited to a relatively small number of in situ observation sites such as carbon flux towers. Our study results indicate large regional and seasonal variations in ecosystem productivity that are strongly influenced by underlying moisture and temperature related controls. Soil moisture provides effective information on water supply related controls to productivity that extend beyond atmosphere moisture demand drivers and constraints represented by VPD, particularly in drier climate zones. Our findings also suggest that despite large variability in the \(\text{SIF}_{\text{P}}\) response to environmental controls in different ecosystems, the mean response characteristicsindicated from the global satellite record were largely consistent with LUE model defined response characteristics used in the SMAP-L4C carbon product and defined from sparse tower observations. The satellite based SIF observations from GOME-2 were found to be an effective surrogate for GPP and sensitive to environmental factors influencing ecosystem productivity as derived from the global reanalysis data. The satellite SIF observations appear to provide an effective means for verifying model assumptions and representations of critical environmental response characteristics that may lead to better understanding and more reliable model predictions.  
The following are available online at www.mdpi.com/2072-4292/9/6/530/s1, Table S1: List of all the fluxnet sites used for the analysis.  
This study was supported by funding from the NASA Earth Science program (NNX14 AI50G, NNX15 AB59G). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarbolItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the ICOS Ecosystem Thematic Center, AmeriFlux Management Project and Fluadata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux, and AsiaFlux offices.  
[PERSON] led in the design, analysis, and writing of the paper. All authors contributed significantly to the design, writing, and revisions of the manuscript.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.