diff --git a/src/data/papers-citing-parcels.ts b/src/data/papers-citing-parcels.ts
index db5819a..74d9bfa 100644
--- a/src/data/papers-citing-parcels.ts
+++ b/src/data/papers-citing-parcels.ts
@@ -3178,4 +3178,13 @@ export const papersCitingParcels: Paper[] = [
     abstract:
       'Accurate multi-day forecasting of floating-object trajectories on the ocean surface is critical for applications ranging from search-and-rescue to environmental tracking. This task remains however challenging due to the complex interplay of influencing factors such as ocean currents and winds. In this work, we frame trajectory prediction as a denoising task and present Conditional Diffusion models for Trajectories (CoDiT), which adapts the denoising diffusion framework, originally developed for image synthesis, to the problem of trajectory forecasting. CoDiT generates realistic trajectory forecasts, conditioned on heterogeneous context data: ocean currents and winds from reanalysis products, bathymetry, and the initial position. We train and evaluate CoDiT on two global, specialized datasets focusing on the open ocean and coastal regions, using GPS trajectories from the Global Drifter Program as ground truth. We compare CoDiT rigorously against various baselines, including a convolutional neural network that predicts velocity fields, and physical forecasts generated directly from the current and wind fields. Quantitative evaluations show that CoDiT achieves the lowest position error across both datasets and all forecast horizons, and the best probabilistic forecast quality among all methods, as measured by the energy score. Notably, in the coastal setting, CoDiT is the only method to surpass the naive persistence baseline in position error.',
   },
+  {
+    title:
+      'Regional redistribution of Japanese glass eel recruitment around Taiwan linked to Kuroshio intrusion variability',
+    published_info: 'Regional Studies in Marine Science, 102, 105408',
+    authors: 'Hsiung, K-M, Y-S Han, Y-F Lin (2026)',
+    doi: 'https://doi.org/10.1016/j.rsma.2026.105408',
+    abstract:
+      'Japanese eel (Anguilla japonica) recruitment around Taiwan is influenced by regional ocean circulation, but how variability in Kuroshio intrusion shapes its spatial distribution remains unclear. We examined the relationship between winter Kuroshio intrusion strength and the redistribution of Japanese glass eel recruitment using reported recruitment records from the Pingtung region and Yilan (Toucheng) during 11 consecutive recruitment seasons spanning 2009–2010 through 2019–2020 (labeled by ending years 2010–2020). Intrusion strength was represented by a DJF-averaged, sign-reversed Kuroshio intrusion index (KI*) derived from the Luzon Strait region. The southern reported recruitment proportion increased significantly with KI* (R² = 0.68, p = 0.002), and a stronger relationship was observed for the natural-log-transformed relative reported recruitment ratio between the Pingtung region and Yilan (Toucheng) (R² = 0.76, p < 0.001). Satellite-derived sea level anomaly and geostrophic surface currents showed structures consistent with enhanced westward exchange across the Luzon Strait during the high southern-recruitment year. Spatial correlations indicated coherent circulation variability around Taiwan and in the downstream Kuroshio region. Passive Lagrangian particle-tracking experiments showed enhanced transport connectivity toward southern and northeastern Taiwan under stronger-intrusion conditions, with a larger relative increase toward the Pingtung region. El Niño–Southern Oscillation (ENSO) variability was significantly associated with KI*, whereas its direct relationship with recruitment redistribution was weaker, suggesting that KI* is a more proximal regional circulation indicator than ONI alone. These results link Kuroshio intrusion variability to circulation-dependent redistribution of Japanese glass eel recruitment around Taiwan.',
+  },
 ]