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Richard A. MacKenzie

Publications and source records attributed to Richard A. MacKenzie.

7 recordsLinked to original sources

Four decades of data indicate that planted mangroves stored up to 75% of the carbon stocks found in intact mature stands

Mangroves’ ability to store carbon (C) has long been recognized, but little is known about whether planted mangroves can store C as efficiently as naturally established (i.e., intact) stands and in which time frame. Through Bayesian logistic models compiled from 40 years of data and built from 684 planted mangrove stands worldwide, we found that biomass C stock culminated at 71 to 73% to that of intact stands ~20 years after planting. Furthermore, prioritizing mixed-species planting including Rhizophora spp. would maximize C accumulation within the biomass compared to monospecific planting. Despite a 25% increase in the first 5 years following planting, no notable change was observed in the soil C stocks thereafter, which remains at a constant value of 75% to that of intact soil C stock, suggesting that planting effectively prevents further C losses due to land use change. These results have strong implications for mangrove restoration planning and serve as a baseline for future C buildup assessments.

Science Advances

Relative effectiveness of a radionuclide (210Pb), surface elevation table (SET), and LiDAR at monitoring mangrove forest surface elevation change

Sea-level rise (SLR) is one of the greatest future threats to mangrove forests. Mangroves have kept up with or paced past SLR by maintaining their forest floor elevation relative to sea level through root growth, sedimentation, and peat development. Monitoring surface elevation change (SEC) or accretion rates allows us to understand mangrove response to SLR and prioritizes resilient ecosystems for conservation or vulnerable ecosystems for restoration. We compared three methods to measure SEC and accretion in mangrove forests: 210 Pb, surface elevation tables (SETs), and a terrestrial light detection and ranging system (compact biomass LiDAR—CBL). Lead-210 accretion rates were not significantly different than SET SEC rates and differences between the two methods (− 2 to 2 mm/year) were within the error of our measurements. Lead-210 only measures accretion in the upper meter of sediment and cannot capture deeper subsurface processes (e.g., subsidence, compaction) that SETs can. The lack of differences suggests the following: (1) surface processes in the active root zone are influencing forest floor elevation more than subsurface processes, (2) subsurface processes were not large enough to effect elevation, or (3) the SETs were not installed deep enough to capture subsurface processes. CBL SEC rates did not differ significantly from SET SEC rates. The larger spatial scale of the CBL scans resulted in significantly different SEC rates from some of the plots. This was due to the CBL measuring areas missed by the SET. The greater number of points measured by CBL (~ 30,000 vs 36) increased precision and lowered standard error. The traditional SET/rSET method is currently 3–10 × cheaper than the 210 Pb or CBL method, respectively, and can accurately track changes in forest floor elevation. Costs of the use of LiDAR are likely to decrease in the future with the advent of newer and more cost-effective technology.

Estuaries and Coasts

A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia

Mangrove forests are the most important ecosystems on Pohnpei Island, Federated States of Micronesia, as the island communities of the central Pacific rely on the forests for many essential services including protection from sea-level rise that is occurring at a greater pace than the global average. As part of a multi-component assessment to evaluate vulnerabilities of mangrove forests on Pohnpei, mangrove forests were mapped at two points in time: 1983 and 2018. In 2018, the island had 6,426 ha of mangrove forest. Change analysis indicated a slight (0.76%) increase of mangrove area between 1983 and 2018, contrasting with global mangrove area declines. Forest structure and aboveground carbon (AGC) stocks were inventoried using a systematic sampling of field survey plots and extrapolated to the island using k-nearest neighbor and random forest species models. A gridded or wall to wall approach is suggested when possible for defining carbon stocks of a large area due to high variability seen in our data. The k-nearest neighbor model performed better than random forest models to map species dominance in these forests. Mean AGC was 167 ± 11 MgC ha -1 , which is greater than the global average of mangroves (115 ± 7 MgC ha -1 ) but within their global range (37–255 MgC ha -1 ) Kauffman et al. (2020). In 2018, Pohnpei mangroves contained over 1.07 million MgC in AGC pools. By assigning the mean AGC stock per species per area to the map, carbon stock distributions were visualized spatially, allowing future conservation efforts to be directed to carbon dense stands.

Pohnpei Island

Mangrove species’ response to sea-level rise across Pohnpei, Federated States of Micronesia

Mangrove forests are likely vulnerable to accelerating sea-level rise; however, we lack the tools necessary to understand their future resilience. On the Pacific island of Pohnpei, Federated States of Micronesia, mangroves are habitat to endangered species and provide critical ecosystem services that support local communities. We developed a generalizable modeling framework for mangroves that accounts for species interactions and the belowground processes that dictate soil elevation. The modeling framework was calibrated with extensive field datasets, including accretion rates derived from thirty 1-meter-deep soil cores dated with lead-210, more than 300 forest inventory plots, water-level monitoring, and differential leveling elevation surveys. We applied the model using a community of five mangrove species and across seven regions around Pohnpei to identify which regions are most vulnerable to sea-level rise. The responses of mean elevation and the mangrove community composition were analyzed under four global sea-level rise scenarios: an increase of 37, 52, 67, or 117 centimeters by 2100. The model was validated against a 20-year surface elevation table record (1999–2019) and showed good agreement when driven by observed water levels. The model projected that mangroves around Pohnpei can build their elevations relative to moderate rates of sea-level rise to prevent submergence, with limited changes in mangrove community composition through 2060. By 2100, however, the model projected a decreasing abundance of high-elevation mangrove species and an increasing abundance of lower elevation species adapted to more persistent flooding. Under higher sea-level rise scenarios, forest elevation decreased substantially relative to mean sea level and there were more drastic changes in the tree community composition and loss of suitable mangrove habitat by 2100. Variation in accretion rates, water levels, and initial forest elevation led to differential vulnerability around the island, such that mangroves on the leeward side of the island generally were the most at-risk to higher rates of sea-level rise. Our findings indicate that the relatively undisturbed state of the mangrove forests and the surrounding landscape is an important factor in their ability to keep pace with sea-level rise.

Pohnpei

Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner

Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.

Limnology and Oceanography Methods

Wetland and hydric soils

Soil and the inherent biogeochemical processes in wetlands contrast starkly with those in upland forests and rangelands. The differences stem from extended periods of anoxia, or the lack of oxygen in the soil, that characterize wetland soils; in contrast, upland soils are nearly always oxic. As a result, wetland soil biogeochemistry is characterized by anaerobic processes, and wetland vegetation exhibits specific adaptations to grow under these conditions. However, many wetlands may also have periods during the year where the soils are unsaturated and aerated. This fluctuation between aerated and nonaerated soil conditions, along with the specialized vegetation, gives rise to a wide variety of highly valued ecosystem services.

Book chapter

Impacts of climate change on mangrove ecosystems: A region by region overview

Inter-related and spatially variable climate change factors including sea level rise, increased storminess, altered precipitation regime and increasing temperature are impacting mangroves at regional scales. This review highlights extreme regional variation in climate change threats and impacts, and how these factors impact the structure of mangrove communities, their biodiversity and geomorphological setting. All these factors interplay to determine spatially variable resiliency to climate change impacts, and because mangroves are varied in type and geographical location, these systems are good models for understanding such interactions at different scales. Sea level rise is likely to influence mangroves in all regions although local impacts are likely to be more varied. Changes in the frequency and intensity of storminess are likely to have a greater impact on N and Central America, Asia, Australia, and East Africa than West Africa and S. America. This review also highlights the numerous geographical knowledge gaps of climate change impacts, with some regions particularly understudied (e.g., Africa and the Middle East). While there has been a recent drive to address these knowledge gaps especially in South America and Asia, further research is required to allow researchers to tease apart the processes that influence both vulnerability and resilience to climate change. A more globally representative view of mangroves would allow us to better understand the importance of mangrove type and landscape setting in determining system resiliency to future climate change.

Ecosystem Health and Sustainability