Southward decrease in the protection of persistent giant kelp forests in the northeast Pacific

Mapping kelp persistence

The study area for this analysis encompasses the region where Macrocystis pyrifera is the dominant canopy kelp species in the Northeast Pacific Ocean. The region extends from Año Nuevo Island in the north (latitude ~37.1°), California, USA, to Punta Prieta in the south (latitude ~27°), Baja California Sur, Mexico. We mapped the distribution of giant kelp canopy and characterized persistence using a 30-m resolution satellite-based time series covering our entire study area²⁷. These data provide quarterly estimates of kelp canopy area across the study region from 1984 to 2018. We estimated giant kelp canopy from three Landsat sensors: Landsat 5 Thematic Mapper (1984–2011), Landsat 7 Enhanced Thematic Mapper+ (1999–present), and Landsat 8 Operational Land Imager (2013–present). We downloaded all imagery as atmospherically corrected Landsat Collection 1 Level-2 products. Each Landsat sensor has a pixel resolution of 30 × 30 m and a repeat time of 16 days (8 days when two Landsat sensors were operational). Since Landsat imagery can be obscured by cloud cover, we obtained a clear estimate of kelp areas ~16 times per year from 1984 to 2018 (mean = 16.2, std = 4.1). The repeated observations across the time series avoid missing kelp canopy due to physical processes such as tides and currents. Multiple Landsat passes over seasonal timescales are successful at mitigating the effect of tide and tidal currents on Landsat kelp canopy detection²⁷.

While the pixel resolution of Landsat sensors is 30 × 30 m, we were able to observe the presence and density of kelp canopy on subpixel scales using a fully automation procedure. We first masked all land areas using a global 30 m resolution digital elevation model (asterweb.jpl.nasa. gov/gdem.asp) and classified the remaining pixels as seawater, cloud, or kelp canopy using a binary decision tree classifier trained on a diverse array of pixels within the study region²⁷. We then used Multiple Endmember Spectral Mixture Analysis³⁹ to model each pixel as the linear combination of seawater and kelp canopy. This method can accurately obtain kelp canopy presence as long as kelp canopy covers ~13% of a 30 m pixel. These methods were validated using 15 years of monthly kelp canopy surveys by the Santa Barbara Coastal Long Term Ecological Research project at two sites in Southern California. We filtered errors of commission (such as free-floating kelp paddies) by removing any pixels classified as kelp canopy in <1% of the image time series.

We characterized kelp persistence as the fraction of years occupied by kelp canopy (at least during one quarter in a year) in each pixel (O_i) that the satellite detected kelp (n = 408,906) for the past 35 years. A pixel with zero value means the satellite never detected kelp forest (these values were not included); while a value of one means, it detected kelp forest for all years. Then, we used kelp persistence data to group pixels into three persistence classes. We classified pixels as low persistence in the 25th percentile, with kelp found in less than 0.24 years. Mid persistence among the 25th and 75th percentile, with kelp found between 0.24 and 0.59 years. High persistence over the 75th percentile, with kelp, found over 0.59 years. To obtain the vectorial maps of kelp forest distribution for the three persistence levels, we rasterized the data points and converted them to polygons in ESRI ArcGIS Pro v10.8.

Kelp representation inside marine protected areas

We obtained data on marine protected area location, boundary, and type for California from the National Oceanic and Atmospheric Administration (NOAA, 2020 version) and for community-based marine reserves in the Baja California Peninsula from Comunidad y Biodiversidad, an NGO that has been supporting the local fishing cooperatives in establishing the voluntary reserves. We performed a spatial overlay analysis to estimate the representation of kelp habitats in marine protected areas. We performed the analysis using ESRI ArcGIS Pro v10.8, calculating coverage through spatial intersections of two marine protected area categories (no-take and multiple-use) and kelp forest persistence (high, mid, and low) for our region. We combined and merged marine protected areas based on the two levels of protection: no-take areas are the most restrictive type where all extractive uses are prohibited (full protection), and multiple-use areas where some restrictions apply to recreational and commercial fishing (partial protection). We divided our region into four areas, Central and Southern California, and Northern and Central Baja California. These four regions represent distinct biogeographic areas⁴⁰ where species composition varies because of oceanographic forcing, or geographic borders (USA and Mexico border). We conducted the analysis for the entire region and separately for each of the four regions.

Present kelp representation inside marine reserves

We estimate the representation of kelp habitats, in marine reserves, that are present, rather than just detected in the time series for each of the four regions and for the Northeast Pacific Ocean. We define present kelp as the probability that a pixel will be occupied by kelp in any given year, thus maintaining the habitat structure they provide. We define kelp as a pixel that the satellite detected kelp (at least once during the time series, n = 408,906). We estimate the probability of present kelp (P), for all pixels protected in marine reserves, as the average persistence value:

where O_i is the fraction of years occupied by kelp habitat for protected pixel i and n the number of pixels with kelp. Then we estimated the representation of present kelp (R_p) as a product of the representation of kelp (R) and the probability of present kelp (P):

where R is the fraction of kelp protected in marine reserves, and P the probability of present kelp. R_p gives an estimate of the percentage of kelp protected and expected to be present in any given year.

Adjusting representation targets for present kelp

We adjust representation targets to protect present kelp for each of the four regions and for the Northeast Pacific Ocean. We first estimate the probability of present kelp (P) for all kelp pixels (rather than for protected pixels). Then, we adjust the representation targets to protect present kelp by applying a multiplier, M:

which adjusts the representation target (T_a):

where T is the representation target and M is the multiplier applied to adjust the representation target (T_a) to protect present kelp. Now we can ensure that the representation of present kelp (R_p) meets the representation target (T) (e.g., 10%).

Unfixed representation targets for present kelp

The previous approach uses fixed representation targets without accounting for the classification of kelp based on their persistence. However, we can adjust representation targets for specific persistence classes. As an example, we can only adjust the representation target for highly persistence kelp. We can then use the previous equation for each level of persistence (low, mid, high), leaving constant the representation target (R) (note that we substitute R for T from Eq. (2)) for low and mid persistence, and estimate the adjusted representation target for highly persistence kelp (T_h):

where R_l, is the representation of low, R_m mid, and R_h high persistence kelp. Then P_l is the probability of present kelp for low, P_m for mid, and P_h for high persistence kelp. Finally, n is the number of detected kelp pixels, n_l is the number of pixels with low, n_m with mid, and n_h with high persistence kelp. We can then estimate the multiplier required to adjust representation targets of high persistence kelp M_h:

Worked example for adjusting the representation targets of present kelp

We estimate the probability of present kelp (P) for the Northeast Pacific Ocean and the adjusting multiplier (M) required to protect 10%³ of present kelp (R_p):

where the probability of present kelp (P) is 0.43 and the representation target (T) is 0.1. By protecting 10% of kelp, only 4.3% of the present kelp is protected in the Northeast Pacific Ocean. We can now estimate the multiplier (M):

which suggests that we need to apply a multiplier (M) of 2.31 to protect 10% of present kelp in the Northeast Pacific Ocean. Finally, we can adjust the representation target (T_a):

which suggests that we need to protect 23.1% of kelp to ensure we protect 10% of kelp expected to be present in any given year.

Unfixed targets

We also provide an example by estimating the adjusted representation target of highly persistence kelp, (T_h) required to represent 10% of present kelp in the Northeast Pacific Ocean:

which suggests that we need to protect 40.7% of highly persistence kelp to meet representation target (T) and apply a multiplier for highly persistence kelp (M_h):

of 4.07.

See values from Table 2 in the main text.

Source: Ecology - nature.com