BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//talks.osgeo.org//foss4g-2026//speaker//GVSAXY
BEGIN:VTIMEZONE
TZID:JST
BEGIN:STANDARD
DTSTART:20000101T000000
RRULE:FREQ=YEARLY;BYMONTH=1
TZNAME:JST
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-foss4g-2026-QWARR9@talks.osgeo.org
DTSTART;TZID=JST:20260903T143000
DTEND;TZID=JST:20260903T150000
DESCRIPTION:Seagrasses are flowering plants (Angiosperms) that have seconda
 rily colonised marine environments\, analogous to the evolutionary return 
 of whales to the sea. Seagrass ecosystems provide essential functions and 
 ecosystem services to coastal areas by introducing structural complexity t
 hrough plant tissue in intertidal zones. These services include habitats f
 or small intertidal organisms\, nursery and feeding grounds for fishery sp
 ecies such as squid spawning aggregations\, shoreline protection through s
 ediment stabilization\, and water purification. \n\nRecently\, seagrasses 
 have been gaining broad attention as a major component of blue carbon. In 
 Japan in particular—where the world's first voluntary blue carbon credit
 s targeting seagrass beds and macroalgal beds were issued—private-sector
  restoration activities have been increasing (Yamakita\, 2025\; Kuwae et a
 l.\, 2026). Yet many seagrass beds worldwide are in decline or unknown sta
 tus (Waycott et al.\, 2009\; McKenzie et al.\, 2020). Adaptive management 
 of these ecosystems requires the ability to detect both long-term trends (
 Yamakita et al.\, 2011) and abrupt collapses across spatial and temporal s
 cales relevant to policy and local management.\n\nContinuous monitoring of
  seagrass faces practical limitations. High-resolution commercial imagery 
 and intensive field surveys provide high accuracy\, but they tend to be pr
 ohibitively expensive\, particularly when long-term time-series data or ex
 tensive coastal areas are involved (Duffy et al.\, 2025). On the other han
 d\, combining historical aerial photographs and recently available low-cos
 t or free satellite data with open-source software (OSS) has the potential
  to enable accessible monitoring by local citizens\, experts from other fi
 elds\, or even countries and organizations with limited budgets. However\,
  this approach remains limited to case studies and has not yet been utiliz
 ed as an integrated monitoring method.\n\nThis study analyses the Ako tida
 l flat in the Seto Inland Sea\, Japan\, where nearly all Zostera marina di
 sappeared within a single year in 2025. Using aerial photographs from the 
 1940s onward\, high-resolution satellite imagery\, GRUS images (2.5–5 m)
 \, and monthly Sentinel‑2 composites (10 m)\, we reconstructed approxima
 tely 80 years of seagrass distribution. YOLO-based segmentation using deep
  learning achieved high accuracy (overall accuracy ≥ 0.9) across these d
 atasets\; although species could not be discriminated\, the models capture
 d the major temporal dynamics in vegetation area. \n\n The long-term mean 
 seagrass area was 6.8 ha\, but values fluctuated widely\, from 3.5 ha in 1
 974 to 41.3 ha in 1989 except 0.2 ha in 2025.  The highest total area was 
 recorded in 1989 (41.3 ha)\, followed by 1999 (14.0 ha) and 1966 (13.6 ha)
 \, indicating that vegetation was most extensively distributed around the 
 1990s. In contrast\, detections in 1974 and 2019 showed considerably small
 er values\, with the total area declining to 3.5 ha in 1974\, 4.5 ha in 20
 19\, and reaching a minimum of 0.2 ha in 2025. \n\nSentinel‑2 composites
  from 2019 to 2026 revealed clear seasonality\, with vegetation increasing
  in early summer and declining from autumn. In 2025\, however\, the area d
 ecreased sharply after summer and remained anomalously low throughout the 
 winter of 2025–2026. \nA distinct seasonal pattern was observed\, with p
 eaks occurring annually from May to July (monthly averages for the entire 
 period: June: 16.0 ha\, July: 17.6 ha)\, followed by a repeated pattern of
  rapid decline from late summer through autumn. However\, observations for
  August and September were limited in many years due to cloud cover. \n\n 
  Field surveys confirmed the absence of living Z. marina shoots\, while Zo
 stera japonica persisted locally\, indicating that the 2025 event was not 
 a normal fluctuation in this area but a rapid ecosystem shift involving lo
 ss of the dominant canopy-forming species\, most plausibly driven by regio
 nally elevated summer water temperatures. \n\nThe findings also have impli
 cations for seagrass Essential Ocean Variables (EOVs) and the State of Nat
 ure (SoN) metrics used in TNFD-aligned nature-related disclosures. Unlike 
 forests\, seagrass meadows require finer temporal resolution because both 
 pronounced seasonality and abrupt collapse strongly influence area-based i
 ndicators. Therefore\, in addition to previously noted issues such as spec
 ies-level classification accuracy\, we recommend that (1) baselines be def
 ined over the longest available record and justified ecologically\, (2) se
 asonal standardization be applied before inter-annual comparisons\, and (3
 ) years with extreme area anomalies be flagged rather than used as referen
 ce points.\n\nThis study demonstrated that\, by integrating historical aer
 ial photographs\, high-resolution satellite imagery\, and satellite conste
 llations using open-source analytical methods\, it is possible to reconstr
 uct both long-term and seasonal variations in seagrass vegetation with hig
 h accuracy\, and to detect sudden ecosystem collapse. Both long-term and s
 easonal variations were significant\, and while the recent disappearance o
 f eelgrass fell within the range of these variations\, it was qualitativel
 y different\; the event was likely influenced by elevated sea surface temp
 eratures across a broad region\, rather than by site-specific factors alon
 e. For reporting frameworks such as TNFD and EOVs\, using seagrass area as
  an indicator requires not only verification using sparse high-resolution 
 images and annual field surveys but also the establishment of an appropria
 te time scale with high-frequency observations and standardized seasons.
DTSTAMP:20260717T225745Z
LOCATION:Cosmos1
SUMMARY:Feasibility to detect rapid change and disappearance of seagrass: L
 essons from nearly 80 years of vegetation change in the Ako\, Seto Inland 
 Sea\, Japan - Takehisa Yamakita
URL:https://talks.osgeo.org/foss4g-2026/talk/QWARR9/
END:VEVENT
END:VCALENDAR