## 3 Results
Data for 2022 were not available at the time. The GPP varies depending on precipitation, humidity, and vegetation cover, among other factors. After Hurricane Maria in 2017, temperatures and vegetation cover were relatively high and low, respectively. When LST values were high, we obtained higher values of GPP, as GPP and NDVI are more responsive to precipitation. In 2015, we had an extreme drought period and higher temperatures compared with other years. Therefore, the uptake of CO\({}_{2}\) increased, because plant transpiration increases at higher temperatures. Still, a negative correlation between LST and GPP was estimated. In 2018, the lowest GPP values were observed, even though the values of NDVI and GPP seemed to stabilize following the hurricane of 2017. Therefore, although the value of LST is greater, it will not necessarily produce greater values of GPP, as what happened in 2015 when compared with 2016 and 2018. GPP models tend to have large variability and significant trends. Thus, improving observation-based models is needed to accurately estimate carbon uptake [26]. The correlations of GPP with LST and NDVI are shown in Figures 11 and 12, respectively. GPP points with values of 3276.19 g/C/day were not considered, because these values represent nonterrestrial fill values. Therefore, out of the 50 by 50 grid that was made to extract GPP values, around 1000 points were outside the area of study and around 600 points were nonterrestrial fill values. The correlation tendency between LST and GPP acts like previous LST correlations. As LST increases, GPP decreases, and vice versa. The amount of carbon that plants use during photosynthesis increases when land surface temperature decreases. The effect in our case is more related to available water than it is to surface temperature. After Hurricane Maria in 2017, most ecosystems were affected and vegetation was reduced considerably compared with other years. The difference in land coverage/greenness,  
Figure 8: Correlation between normalized difference vegetation index and actual ET for 2017. NDVI, can be observed for WRC in 2017 (Figure 3) compared with 2022, after Hurricane Fiona passed over the island. GPP is the amount of carbon that is being exchanged by plants, so it is expected that higher vegetation will produce higher exchange. Thus, correlating NDVI and GPP shows that carbon exchange increases with an increase in NDVI, and vice versa. Nevertheless, values for NDVI and GPP were lower for 2017 compared with other years. The precipitation for 2017 affected the values of NDVI and GPP, as the data were taken after a major atmospheric event. Figure 10: Spatial distribution of GPP estimated from MOD17A1; an 8-day composite with a 500 m resolution. Figure 9: Correlation between gross primary production and evapotranspiration for 2015. Correlations between the different parameters evaluated for resilience were also investigated using a correlation matrix, as shown in Figure 4:0 Correlation matrices show the negative and positive correlations between parameters. For the decade evaluated, we saw the same tendency of correlation, where ET positively correlated with NDVI and GPP because these parameters are more responsive to precipitation. On the other hand, LST values negatively correlated with ET, NDVI, and GPP for every year evaluated. In 2013, the matrix value between ET and LST was \(-0.33\), and in 2021, the matrix value was \(-0.48\). In 2015, when the drought period occurred, the correlation values of ET with NDVI and GPP were \(0.1\) and \(0.15\), respectively. For 2015, the correlation value between ET and LST was \(-0.17\) (almost no correlation). Figure 4:1 Correlation between land surface temperature and gross primary production for 2017. Figure 4:2 Correlation between normalized difference vegetation index and gross primary production for 2017.  
correlation due to the low availability of water). In 2017, the negative correlation values of LST with ET, NDVI, and GPP were \(-0.23\), \(-0.25\), and \(-0.17\), respectively.