Variance reflects resilience to disturbance along a stress gradient: Experimental evidence from coastal marshes.

Quantifying ecosystem resilience to disturbance is important for understanding the effects of disturbances on ecosystems, especially in an era of rapid global change. However, there are few studies that have used standardized experimental disturbances to compare resilience patterns across abiotic gradients in real-world ecosystems. Theoretical studies have suggested that increased return times are associated with increasing variance during recovery from disturbance. However, this notion has rarely been explicitly tested in field, in part due to the challenges involved in obtaining long-term experimental data. In this study, we examined resilience to disturbance of 12 coastal marsh sites (five low-salinity and seven polyhaline [=salt] marshes) along a salinity gradient in Georgia, USA. We found that recovery times after experimental disturbance ranged from 7 to >127 months, and differed among response variables (vegetation height, cover and composition). Recovery rates decreased along the stress gradient of increasing salinity, presumably due to stress reducing plant vigor, but only when low-salinity and polyhaline sites were analyzed separately, indicating a strong role for traits of dominant plant species. The coefficient of variation of vegetation cover and height in control plots did not vary with salinity. In disturbed plots, however, the coefficient of variation (CV) was consistently elevated during the recovery period and increased with salinity. Moreover, higher CV values during recovery were correlated with slower recovery rates. Our results deepen our understanding of resilience to disturbance in natural ecosystems, and point to novel ways that variance can be used either to infer recent disturbance, or, if measured in areas with a known disturbance history, to predict recovery patterns.

BERM: a Belowground Ecosystem Resiliency Model for estimating Spartina alterniflora belowground biomass.

Spatiotemporal patterns of Spartina alterniflora belowground biomass (BGB) are important for evaluating salt marsh resiliency. To solve this, we created the BERM (Belowground Ecosystem Resiliency Model), which estimates monthly BGB (30-m spatial resolution) from freely available data such as Landsat-8 and Daymet climate summaries. Our modeling framework relied on extreme gradient boosting, and used field observations from four Georgia salt marshes as ground-truth data. Model predictors included estimated tidal inundation, elevation, leaf area index, foliar nitrogen, chlorophyll, surface temperature, phenology, and climate data. The final model included 33 variables, and the most important variables were elevation, vapor pressure from the previous four months, Normalized Difference Vegetation Index (NDVI) from the previous five months, and inundation. Root mean squared error for BGB from testing data was 313 g m-2 (11% of the field data range), explained variance (R2 ) was 0.62-0.77. Testing data results were unbiased across BGB values and were positively correlated with ground-truth data across all sites and years (r = 0.56-0.82 and 0.45-0.95, respectively). BERM can estimate BGB within Spartina alterniflora salt marshes where environmental parameters are within the training data range, and can be readily extended through a reproducible workflow. This provides a powerful approach for evaluating spatiotemporal BGB and associated ecosystem function.

Climate research priorities for policy-makers, practitioners, and scientists in Georgia, USA.

Climate change has far-reaching effects on human and ecological systems, requiring collaboration across sectors and disciplines to determine effective responses. To inform regional responses to climate change, decision-makers need credible and relevant information representing a wide swath of knowledge and perspectives. The southeastern U. S. State of Georgia is a valuable focal area for study because it contains multiple ecological zones that vary greatly in land use and economic activities, and it is vulnerable to diverse climate change impacts. We identified 40 important research questions that, if answered, could lay the groundwork for effective, science-based climate action in Georgia. Top research priorities were identified through a broad solicitation of candidate research questions (180 were received). A group of experts across sectors and disciplines gathered for a workshop to categorize, prioritize, and filter the candidate questions, identify missing topics, and rewrite questions. Participants then collectively chose the 40 most important questions. This cross-sectoral effort ensured the inclusion of a diversity of topics and questions (e.g., coastal hazards, agricultural production, ecosystem functioning, urban infrastructure, and human health) likely to be important to Georgia policy-makers, practitioners, and scientists. Several cross-cutting themes emerged, including the need for long-term data collection and consideration of at-risk Georgia citizens and communities. Workshop participants defined effective responses as those that take economic cost, environmental impacts, and social justice into consideration. Our research highlights the importance of collaborators across disciplines and sectors, and discussing challenges and opportunities that will require transdisciplinary solutions.

Ascomycete fungal communities associated with early decaying leaves of Spartina spp. from central California estuaries.

Ascomycetous fungi play an important role in the early stages of decomposition of Spartina alterniflora, but their role in the decomposition of other Spartina species has not been investigated. Here we use fingerprint (terminal restriction fragment length polymorphism) and phylogenetic analyses of the 18S to 28S internal transcribed spacer region to compare the composition of the ascomycete fungal communities on early decay blades of Spartina species (Spartina alterniflora, Spartina densiflora, Spartina foliosa, and a hybrid (S. alterniflora x S. foliosa)) collected from three salt marshes in San Francisco Bay and one in Tomales Bay, California, USA. Phaeosphaeria spartinicola was found on all samples collected and was often dominant. Two other ascomycetes, Phaeosphaeria halima and Mycosphaerella sp. strain 2, were also common. These three species are the same ascomycetes previously identified as the dominant fungal decomposers on S. alterniflora on the east coast. Ascomycetes appeared to exhibit varying degrees of host specificity, demonstrated by grouping patterns on phylogenetic trees. Neither the exotic S. alterniflora nor the hybrid supported fungal flora different from that of the native S. foliosa. However, S. densiflora had a significantly different fungal community than the other species, and hosted at least two unique ascomycetes. Significant differences in the fungal decomposer communities were also detected within species (two clones of S. foliosa), but these were minor and may be due to morphological differences among the plants.