Spatiotemporal Dynamics and Driving Factors of Vegetation Gross Primary Productivity in a Typical Coastal City: A Case Study of Zhanjiang, China

Abstract

Highlights: What are the main findings? Driver Shift with Natural Dominance: While natural factors generally remain dominant, the driving mechanism is shifting toward anthropogenic factors, with Nighttime Light (NTL) rapidly escalating to become the most significant individual driving factor. “Pseudo-Growth Effect”: A counterintuitive GPP increase was observed in degraded wetlands, stemming from the remote sensing underestimation of sparse wetland vegetation and their subsequent conversion into land types with higher estimated GPP (e.g., cropland). What are the implications of the main findings? Policy Transition: Conservation strategies in coastal–urban complex ecosystems must transition from passive climate adaptation to the proactive regulation of human activities, strictly controlling the encroachment of urbanization and agriculture on coastal zones. Assessment Caution: Relying solely on satellite-derived GPP is insufficient for assessing coastal wetland health due to sparse vegetation estimation errors; a holistic framework integrating high-resolution data and hydrological metrics is required to avoid misleading conclusions. Coastal wetlands, situated at the critical land–sea ecotone, play a vital role in sustaining ecological balance and supporting human activities. Currently, these ecosystems face dual stresses from climate change and intensified anthropogenic activities, making the quantitative assessment of ecosystem functions—represented by Gross Primary Productivity (GPP)—essential for their protection and management. However, a knowledge gap remains regarding coastal–urban complex ecosystems, and existing studies on coastal wetlands often overlook macro-environmental drivers beyond sea-level rise. This study leveraged the MOD17A2H V006 dataset to generate a 500 m GPP product for Zhanjiang City. We analyzed the spatiotemporal dynamics of GPP, utilized land use data to examine the evolution of coastal wetlands, and employed the Geodetector model to quantify the contributions of various factors to GPP in Zhanjiang and its coastal wetlands. The results indicate that: (1) GPP in Zhanjiang exhibited an overall steady upward trend, increasing at an average rate of (Formula presented.). However, it displayed strong spatial heterogeneity, characterized by higher values in the southwest and lower values in the northern and coastal regions. (2) The land use pattern in Zhanjiang underwent significant transformations over the past two decades. Cropland and impervious surfaces expanded markedly, increasing by 194.6 km2 and 290.42 km2, respectively, while coastal wetland areas showed a continuous decline, with degraded and newly formed areas of 101.5 km2 and 42 km2, respectively. (3) The Geodetector results revealed that the q-value of Nighttime Light (NTL) increased from negligible values to over 0.1, emerging as a dominant driving factor. Although the driving force of anthropogenic activity factors on Zhanjiang and its coastal wetlands has steadily increased, natural factors currently remain the dominant forces. These findings unravel the driving mechanisms of natural and anthropogenic factors on GPP in Zhanjiang, providing valuable scientific evidence for the sustainable development of coastal ecosystems.