long term time series

why long term observations are needed

• time series as a fundamental tool in marine biology

• key questions time series help answer:

  • how do biomass and primary production change over time?

  • how does species composition change?

  • what are the dominant periodicities in marine systems?

    • daily (light-dark cycles)

    • monthly (tides)

    • annual (seasonality)

    • interannual /decadal (climate variability)

  • do the same species recur every year?

  • what drives year-to-year variability

  • how do we detect long-term climate trends

• short term studies miss essential patterns - only long term observation reveal trends, cycles, and regime shifts

long-term pelagic time series: overview

• many marine ecosystems now have decades-long datasets

• these allow synthesis across:

  • physics

  • biogeochemistry

  • microbial ecology

• reference to Bunse and Pinhassi (2017) on seasonal succession in bacterioplankton

continuous plankton recorder (CPR)

history and scope

• concieved in the 1920s, started in 1931

• operates mainly in the North atlantic

• 280,000 samples collected

• one of the longest biological time series in existence

intrumentation and sampling

• plankton collected behind commercial ships

• measurements include:

  • plankton abundance

  • temperature

  • salinity

  • flouresence

• uses fixed ship routes (ship lines)

what CPR revealed

• strong annual variability in plankton

• detection of global change signals, including:

  • atlantification (northward shift of warm water species

  • changes in dinoflagellate communities

  • regional declines in plankton biomass in parts of the NE atlantic

bermuda atlantic time series

• general characteristics

  • locatted in the sargasso sea

  • started in 1989

  • oligotrophic (nutrient poor) open ocean site

• key processes observed

  • deep winter mixing brings nutrients to the surface

  • winter mixing controls:

    • nutrient concnetration

    • primary production

  • storng coupling between physical mixing and biological responses

hawaii ocean time series (HOTS / station ALOHA)

• site characteristics

  • station ALOHA, north apcific subtropical gyre

  • started in 1989

  • extremely oligotrophic system

• physical and biological strucutre

  • despite being tropical, shows temperate variability

  • seasonal deepening of:

    • chlorphyll maximum

    • primary production

  • long term trends observed in:

    • CO2

    • chlorophyll

    • primary production

• even stable oligotorphic systems show long term change when observed for decades

determining periodicity in plankton communities

• long term data allow identification of recurring seasonal patterns

• focus shifts from biomass to species level dynamics

english channel (roscoff) time series

• site characteristics

  • tidally mixed coastal system

  • strong tides → water column always mixed

  • sampling period: 2009-2016

• metabarcoding approach

  • DNA based identification of protists communities

  • allows detection of

    • high taxonomic diversity

    • rare species

  • taxonomic assignment of DNA sequences

• community dynamics

  • mean community composition shows strong seasonality

  • redundancy analysis (RDA) revelas:

    • annual cycles

    • environemental drivers of community structure

mediterranean sea (blanes bay)

• site characteristics

  • NW mediterranean coastal site

  • sampling period: 2004-2013

  • winter mixing → january bloom

• key questions

  • which phytoplankton group shows periodic recurrence

  • which species reappear every year

  • application of metabarcoding to resolve species-level patterns

how periodicity is quantified

• use of autocorrelation analysis to detect periodic signals

• applied at:

  • class level

  • species

  • level

• allows distinction between

  • strongly recurring species

  • irregular or episodic species

species dynamics: the case of synechococcus

• introduction to synechococcus

  • marine cyanobacterium

  • discovered in 1979

  • abundant and gloobally importnat

  • divides by binarry fission, typically once per day

• growth vs loss processes

  • population change depends on:

    • growht rate (cell division)

    • loss rate (viruses, grazingm cell death)

• observational tools

  • flow cytobot

    • combines imaging and flow cytometry

    • enables high-frequency monitoring of phytoplankton

• annual periodicity and variability

  • synechoccus shows strong annual periodicity

  • however, abundance varies strongly between years

• environemntal drivers

  • temperature is a key control

  • bloom timing matches the day temperature crosses a threshold

  • evidence for hysteresis: growth depends on prior conditions, not just instantaneous temperature

take home messages:

• long term observations are essential to understant:

  • what changes

  • what drives change

• CPR revelaed large scale biogeographic shifts (e.g, atlantification)

• time series allow us to ask fundamental questions

  • which species recur every year?

  • why does one species vary from year to year

• climate impacts can only be detected against long term baseline