In forested catchments, the exceedance of rainfall and antecedent water storage thresholds is often required for runoff generation, yet to our knowledge these threshold relationships remain undescribed in tropical dry forest catchments. We, therefore, identified the controls of streamflow activation and the timing and magnitude of runoff in a tropical dry forest catchment near the Pacific coast of central Mexico. During a 52 day transition phase from the dry to wet season, soil water movement was dominated by vertical flow which continued until a threshold soil moisture content of 26% was reached at 100 cm below the surface. This satisfied a 162 mm storage deficit and activated streamflow, likely through lateral subsurface flow pathways. High antecedent soil water conditions were maintained during the wet phase but had a weak influence on stormflow. We identified a threshold value of 289 mm of summed rainfall and antecedent soil water needed to generate >4 mm of stormflow per event. Above this threshold, stormflow response and magnitude was almost entirely governed by rainfall event characteristics and not antecedent soil moisture conditions. Our results show that over the course of the wet season in tropical dry forests the dominant controls on runoff generation changed from antecedent soil water and storage to the depth of rainfall.

Spatial heterogeneity is a universal phenomenon existing in ecological systems at all scales. In the humid tropics, soil sampling and characterization are complex due to high spatial variability. The inability of researchers to capture this spatial variability inhibits the effective management of resources in terrestrial ecosystems. Hence, simple sampling approaches that are labor and cost-efficient but generate representative samples are required to optimize soil sampling and characterization. In this paper, we used a combination of descriptive statistics and geostatistics to characterize the spatial variability of soil under two land uses. One-way ANOVA and a Student t-test were also used to assess the effectiveness of three distinct sampling designs at capturing the variation in the soil’s physicochemical properties. The wetland soils generally exhibited low spatial variability, whereas the variability of the agroforest ranged from low (coefficient of variance (CV) < 25%) to highly variable (CV > 75%). Results show that in the wetland, CVs of samples obtained using the random sampling design (RSD) and response surface directed design (RSDD) were highly correlated (pearson correlation coefficient (r) = 0.98). Similarly, in the agroforest, the CVs of the stratified random sampling design (SRSD) and RSDD gave almost the same accuracy (r = 0.97). Thus, it is recommended that in this and similar humid-tropical wetland and agroforest ecosystems, the RSD and the RSDD, which require the least samples, can be used, respectively. However, more comprehensive testing is required on a broader range of soils before its more widespread application in other climatic conditions.