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The spread of nonindigenous species by shipping is a large and growing global problem that harms coastal ecosystems and economies and may blur coastal biogeographical patterns. This study coupled eukaryotic environmental DNA (eDNA) metabarcoding with dissimilarity regression to test the hypothesis that ship‐borne species spread homogenizes port communities. We first collected and metabarcoded water samples from ports in Europe, Asia, Australia and the Americas. We then calculated community dissimilarities between port pairs and tested for effects of environmental dissimilarity, biogeographical region and four alternative measures of ship‐borne species transport risk. We predicted that higher shipping between ports would decrease community dissimilarity, that the effect of shipping would be small compared to that of environment dissimilarity and shared biogeography, and that more complex shipping risk metrics (which account for ballast water and stepping‐stone spread) would perform better. Consistent with our hypotheses, community dissimilarities increased significantly with environmental dissimilarity and, to a lesser extent, decreased with ship‐borne species transport risks, particularly if the ports had similar environments and stepping‐stone risks were considered. Unexpectedly, we found no clear effect of shared biogeography, and that risk metrics incorporating estimates of ballast discharge did not offer more explanatory power than simpler traffic‐based risks. Overall, we found that shipping homogenizes eukaryotic communities between ports in predictable ways, which could inform improvements in invasive species policy and management. We demonstrated the usefulness of eDNA metabarcoding and dissimilarity regression for disentangling the drivers of large‐scale biodiversity patterns. We conclude by outlining logistical considerations and recommendations for future studies using this approach. [ABSTRACT FROM AUTHOR]

This research investigates ecological responses to drought by developing a conceptual framework of vegetation response and investigating how multiple measures of drought can improve regional drought monitoring. We apply this approach to a case study of a recent drought in Guanacaste, Costa Rica. First, we assess drought severity with the Standard Precipitation Index (SPI) based on a 64‐yr precipitation record derived from a combination of Global Precipitation Climatology Center data and satellite observations from Tropical Rainfall Measuring Mission and Global Precipitation Measurement. Then, we examine spatial patterns of precipitation, vegetation greenness, evapotranspiration (ET), potential evapotranspiration (PET), and evaporative stress index (ESI) during the drought years of 2013, 2014, and 2015 relative to a baseline period (2002–2012). We compute wet season (May–October) anomalies for precipitation at 0.25° spatial resolution, normalized difference vegetation index (NDVI) at 30‐m spatial resolution, and ET, PET and ESI derived with the Priestley‐Taylor Jet Propulsion Laboratory (PT‐JPL) model at 1‐km spatial resolution. We assess patterns of landscape response across years and land cover types including three kinds of forest (deciduous, old growth, and secondary), grassland, and cropland. Results show that rainfall in Guanacaste reached an all‐time low in 2015 over a 64‐yr record (wet season SPI = −3.46), resulting in NDVI declines. However, ET and ESI did not show significant anomalies relative to a baseline, drought‐free period. Forests in the region exhibited lower water stress compared to grasslands and had smaller declines, and even some increases, in NDVI and ET during the drought period. This work highlights the value of using multiple measures to assess ecosystem responses to drought. It also suggests that agricultural land management has an opportunity to integrate these findings by emulating some of the characteristics of drought‐resilient ecosystems in managed systems. [ABSTRACT FROM AUTHOR]