Climate-driven regime shifts in a mangrove-salt marsh ecotone over the past 250 years.

Climate change is driving the tropicalization of temperate ecosystems by shifting the range edges of numerous species poleward. Over the past few decades, mangroves have rapidly displaced salt marshes near multiple poleward mangrove range limits, including in northeast Florida. It is uncertain whether such mangrove expansions are due to anthropogenic climate change or natural climate variability. We combined historical accounts from books, personal journals, scientific articles, logbooks, photographs, and maps with climate data to show that the current ecotone between mangroves and salt marshes in northeast Florida has shifted between mangrove and salt marsh dominance at least 6 times between the late 1700s and 2017 due to decadal-scale fluctuations in the frequency and intensity of extreme cold events. Model projections of daily minimum temperature from 2000 through 2100 indicate an increase in annual minimum temperature by 0.5 °C/decade. Thus, although recent mangrove range expansion should indeed be placed into a broader historical context of an oscillating system, climate projections suggest that the recent trend may represent a more permanent regime shift due to the effects of climate change

Mangrove dispersal disrupted by projected changes in global seawater density

The degree to which the distribution of mangrove forests will be impacted by climate change depends on the dispersal and establishment of sea-faring propagules, which drive forest rejuvenation, gene flow and range expansion. Climate change affects sea surface density via changes in temperature and salinity. However, these changes have not been mapped and it remains unclear how these factors may impact mangrove propagule dispersal. Here, we provide evidence for strong warming of coastal mangrove waters and elevated geographic variability in surface ocean density under representative concentration pathway RCP 8.5 by 2100. The largest changes will occur in the Indo West Pacific region, the primary hotspot of mangrove diversity. By comparing propagule densities to predicted sea surface density, we assessed potential effects on mangrove propagule dispersal. In the future, a warmer and fresher ocean is likely to alter dispersal trajectories of mangrove propagules and increase rates of sinking in unsuitable offshore locations, potentially reducing the resilience of mangrove forests

Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas)

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Houskeeper, H. F., Rosenthal, I. S., Cavanaugh, K. C., Pawlak, C., Trouille, L., Byrnes, J. E. K., Bell, T. W., & Cavanaugh, K. C. Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas). Plos One, 17(1), (2022): e0257933, https://doi.org/10.1371/journal.pone.0257933.Giant kelp populations that support productive and diverse coastal ecosystems at temperate and subpolar latitudes of both hemispheres are vulnerable to changing climate conditions as well as direct human impacts. Observations of giant kelp forests are spatially and temporally uneven, with disproportionate coverage in the northern hemisphere, despite the size and comparable density of southern hemisphere kelp forests. Satellite imagery enables the mapping of existing and historical giant kelp populations in understudied regions, but automating the detection of giant kelp using satellite imagery requires approaches that are robust to the optical complexity of the shallow, nearshore environment. We present and compare two approaches for automating the detection of giant kelp in satellite datasets: one based on crowd sourcing of satellite imagery classifications and another based on a decision tree paired with a spectral unmixing algorithm (automated using Google Earth Engine). Both approaches are applied to satellite imagery (Landsat) of the Falkland Islands or Islas Malvinas (FLK), an archipelago in the southern Atlantic Ocean that supports expansive giant kelp ecosystems. The performance of each method is evaluated by comparing the automated classifications with a subset of expert-annotated imagery (8 images spanning the majority of our continuous timeseries, cumulatively covering over 2,700 km of coastline, and including all relevant sensors). Using the remote sensing approaches evaluated herein, we present the first continuous timeseries of giant kelp observations in the FLK region using Landsat imagery spanning over three decades. We do not detect evidence of long-term change in the FLK region, although we observe a recent decline in total canopy area from 2017–2021. Using a nitrate model based on nearby ocean state measurements obtained from ships and incorporating satellite sea surface temperature products, we find that the area of giant kelp forests in the FLK region is positively correlated with the nitrate content observed during the prior year. Our results indicate that giant kelp classifications using citizen science are approximately consistent with classifications based on a state-of-the-art automated spectral approach. Despite differences in accuracy and sensitivity, both approaches find high interannual variability that impedes the detection of potential long-term changes in giant kelp canopy area, although recent canopy area declines are notable and should continue to be monitored carefully.This work was funded by the National Aeronautics and Space Administration as part of the Citizen Science for Earth Systems Program (https://earthdata.nasa.gov/esds/competitive-programs/csesp) with grant #80NSSC18M0103 (awarded to JEKB), which also provided salary to HFH, and by the National Science Foundation through the Santa Barbara Coastal Long-Term Environmental Research (https://sbclter.msi.ucsb.edu) program with grants #OCE 0620276 and 1232779. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Tail-dependent spatial synchrony arises from nonlinear driver–response relationships

Spatial synchrony may be tail-dependent, that is, stronger when populations are abundant than scarce, or vice-versa. Here, ‘tail-dependent’ follows from distributions having a lower tail consisting of relatively low values and an upper tail of relatively high values. We present a general theory of how the distribution and correlation structure of an environmental driver translates into tail-dependent spatial synchrony through a non-linear response, and examine empirical evidence for theoretical predictions in giant kelp along the California coastline. In sheltered areas, kelp declines synchronously (lower-tail dependence) when waves are relatively intense, because waves below a certain height do little damage to kelp. Conversely, in exposed areas, kelp is synchronised primarily by periods of calmness that cause shared recovery (upper-tail dependence). We find evidence for geographies of tail dependence in synchrony, which helps structure regional population resilience: areas where population declines are asynchronous may be more resilient to disturbance because remnant populations facilitate reestablishment

Disturbance and nutrients synchronise kelp forests across scales through interacting Moran effects

Spatial synchrony is a ubiquitous and important feature of population dynamics, but many aspects of this phenomenon are not well understood. In particular, it is largely unknown how multiple environmental drivers interact to determine synchrony via Moran effects, and how these impacts vary across spatial and temporal scales. Using new wavelet statistical techniques, we characterised synchrony in populations of giant kelp Macrocystis pyrifera, a widely distributed marine foundation species, and related synchrony to variation in oceanographic conditions across 33 years (1987–2019) and >900 km of coastline in California, USA. We discovered that disturbance (storm-driven waves) and resources (seawater nutrients)—underpinned by climatic variability—act individually and interactively to produce synchrony in giant kelp across geography and timescales. Our findings demonstrate that understanding and predicting synchrony, and thus the regional stability of populations, relies on resolving the synergistic and antagonistic Moran effects of multiple environmental drivers acting on different timescales

Using Unoccupied Aerial Vehicles to Map and Monitor Changes in Emergent Kelp Canopy after an Ecological Regime Shift

Kelp forests are complex underwater habitats that form the foundation of many nearshore marine environments and provide valuable services for coastal communities. Despite their ecological and economic importance, increasingly severe stressors have resulted in declines in kelp abundance in many regions over the past few decades, including the North Coast of California, USA. Given the significant and sustained loss of kelp in this region, management intervention is likely a necessary tool to reset the ecosystem and geospatial data on kelp dynamics are needed to strategically implement restoration projects. Because canopy-forming kelp forests are distinguishable in aerial imagery, remote sensing is an important tool for documenting changes in canopy area and abundance to meet these data needs. We used small unoccupied aerial vehicles (UAVs) to survey emergent kelp canopy in priority sites along the North Coast in 2019 and 2020 to fill a key data gap for kelp restoration practitioners working at local scales. With over 4,300 hectares surveyed between 2019 and 2020, these surveys represent the two largest marine resource-focused UAV surveys conducted in California to our knowledge. We present remote sensing methods using UAVs and a repeatable workflow for conducting consistent surveys, creating orthomosaics, georeferencing data, classifying emergent kelp and creating kelp canopy maps that can be used to assess trends in kelp canopy dynamics over space and time. We illustrate the impacts of spatial resolution on emergent kelp canopy classification between different sensors to help practitioners decide which data stream to select when asking restoration and management questions at varying spatial scales. Our results suggest that high spatial resolution data of emergent kelp canopy from UAVs have the potential to advance strategic kelp restoration and adaptive management

Sensitivity of mangrove range limits to climate variability

Aim: Correlative distribution models have been used to identify potential climatic controls of mangrove range limits, but there is still uncertainty about the relative importance of these factors across different regions. To provide insights into the strength of climatic control of different mangrove range limits, we tested whether temporal variability in mangrove abundance increases near range limits and whether this variability is correlated with climatic factors thought to control large scale mangrove distributions. Location: North and South America. Time period: 1984–2011. Major taxa studied: Avicennia germinans, Avicennia schuaeriana, Rhizophora mangle, Laguncularia racemosa. Methods: We characterized temporal variability in the enhanced vegetation index (EVI) at mangrove range limits using Landsat satellite imagery collected between 1984–2011. We characterized greening trends at each range limit, examined variability in EVI along latitudinal gradients near each range limit, and assessed correlations between changes in EVI and temperature and precipitation. Results: Spatial variability in mean EVI was generally correlated with temperature and precipitation, but the relationships were region specific. Greening trends were most pronounced at range limits in eastern North America. In these regions variability in EVI increased toward the range limit and was sensitive to climatic factors. In contrast, EVI at range limits on the Pacific coast of North America and both coasts of South America was relatively stable and less sensitive to climatic variability. Main conclusions: Our results suggest that range limits in eastern North America are strongly controlled by climate factors. Mangrove expansion in response to future warming is expected to be rapid in regions that are highly sensitive to climate variability (e.g. eastern North America), but the response in other range limits (e.g. South America) is likely to be more complex and modulated by additional factors such as dispersal limitation, habitat constraints, and/or changing climatic means rather than just extremes

A regional map of mangrove extent for Myanmar, Thailand, and Cambodia shows losses of 44% by 1996

Southeast Asia is home to some of the planet’s most carbon-dense and biodiverse mangrove ecosystems. There is still much uncertainty with regards to the timing and magnitude of changes in mangrove cover over the past 50 years. While there are several regional to global maps of mangrove extent in Southeast Asia over the past two decades, data prior to the mid-1990s is limited due to the scarcity of Earth Observation (EO) data of sufficient quality and the historical limitations to publicly available EO. Due to this literature gap and research demand in Southeast Asia, we conducted a classification of mangrove extent using Landsat 1-2 MSS Tier 2 data from 1972 to 1977 for three Southeast Asian countries: Myanmar, Thailand, and Cambodia. Mangrove extent land cover maps were generated using a Random Forest machine learning algorithm that effectively mapped a total of 15,420.51 km2. Accuracy assessments indicated that the classification for the mangrove and non-mangrove class had a producer’s accuracy of 80% and 98% user’s accuracy of 90% and 96%, and an overall accuracy of 95%. We found a decline of 6,830 km2 between the 1970s and 2020, showing that 44% of the mangrove area in these countries has been lost in the past 48 years. Most of this loss occurred between the 1970s and 1996; rates of deforestation declined dramatically after 1996. This study also elaborated on the nature of mangrove change within the context of the social and political ecology of each case study country. We urge the remote sensing community to empathetically consider the local need of those who depend on mangrove resources when discussing mangrove loss drivers

A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cavanaugh, K. C., Bell, T., Costa, M., Eddy, N. E., Gendall, L., Gleason, M. G., Hessing-Lewis, M., Martone, R., McPherson, M., Pontier, O., Reshitnyk, L., Beas-Luna, R., Carr, M., Caselle, J. E., Cavanaugh, K. C., Miller, R. F., Hamilton, S., Heady, W. N., Hirsh, H. K., Hohman R., Lee L. C., Lorda J., Ray J., Reed D. C., Saccomanno V. R., Schroeder, S. B. A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps. Frontiers in Marine Science, 8, (2021): 753531, https://doi.org/10.3389/fmars.2021.753531.Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.Funding was provided by the Nature Conservancy (Grant No. 02042019-5719), the U.S. National Science Foundation (Grant No. OCE 1831937), and the U.S. Department of Energy ARPA-E (Grant No. DE-AR0000922)