Applying cumulative effects to strategically advance large-scale ecosystem restoration

International efforts to restore degraded ecosystems will continue to expand over the coming decades, yet the factors contributing to the effectiveness of long-term restoration across large areas remain largely unexplored. At large scales, outcomes are more complex and synergistic than the additive impacts of individual restoration projects. Here, we propose a cumulative-effects conceptual framework to inform restoration design and implementation and to comprehensively measure ecological outcomes. To evaluate and illustrate this approach, we reviewed long-term restoration in several large coastal and riverine areas across the US: the greater Florida Everglades; Gulf of Mexico coast; lower Columbia River and estuary; Puget Sound; San Francisco Bay and Sacramento–San Joaquin Delta; Missouri River; and northeastern coastal states. Evidence supported eight modes of cumulative effects of interacting restoration projects, which improved outcomes for species and ecosystems at landscape and regional scales. We conclude that cumulative effects, usually measured for ecosystem degradation, are also measurable for ecosystem restoration. The consideration of evidence-based cumulative effects will help managers of large-scale restoration capitalize on positive feedback and reduce countervailing effects

Global dataset of soil organic carbon in tidal marshes

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies

Global dataset of soil organic carbon in tidal marshes.

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha-1 in the top 30 cm and 231 ± 134 Mg SOC ha-1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies

Priming Analogical Reasoning with False Memories

Like true memories, false memories are capable of priming answers to insight-based problems. Recent research has attempted to extend this paradigm to more advanced problem-solving tasks, including those involving verbal analogical reasoning. However, these experiments are constrained inasmuch as problem solutions could be generated via spreading activation mechanisms (much like false memories themselves) rather than using complex reasoning processes. In three experiments we examined false memory priming of complex analogical reasoning tasks in the absence of simple semantic associations. In Experiment 1, we demonstrated the robustness of false memory priming in analogical reasoning when backward associative strength among the problem terms was eliminated. In Experiments 2a and 2b, we extended these findings by demonstrating priming on newly created homonym analogies that can only be solved by inhibiting semantic associations within the analogy. Overall, the findings of the present experiments provide evidence that the efficacy of false memory priming extends to complex analogical reasoning problems

Global dataset of soil organic carbon in tidal marshes

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies

The structural heterogeneity of an urbanised mangrove forest area in southeastern Brazil: Influence of environmental factors and anthropogenic stressors

Abstract The objective of this study is to evaluate the characteristics of the forest in an urbanised mangrove using vegetation structure and abiotic conditions to distinguish habitat heterogeneity/quality. A total of 16 points in Vitória Bay were selected in the fringe and basin forests. The variables evaluated were height and diameter of the individual trees, basal area, density, dominance, interstitial water, litter mass, grain size, organic matter and anthropogenic influences. The results indicated that the mangrove area, due to suffering intensely from various anthropogenic effects, forests with varying degrees of maturity. Areas more distant from direct human effects had a higher degree of development and environmental quality relative to points closer to urban pressures. Intermediate development levels were also observed, which indicated pulses of environmental change. Human interventions caused alterations in the development of the forest which increased the mortality rate and reduced the diameter and height of the trees. The environmental variables of salinity, organic matter, litter mass, grain size and anthropogenic stressors contributed to the structural patterns. Our data suggest that an analysis of the vegetation structure and the abiotic factors are useful indicators to evaluate habitat quality, thus providing a basis for future management

State of the world’s plants and fungi 2020

Kew’s State of the World’s Plants and Fungi project provides assessments of our current knowledge of the diversity of plants and fungi on Earth, the global threats that they face, and the policies to safeguard them. Produced in conjunction with an international scientific symposium, Kew’s State of the World’s Plants and Fungi sets an important international standard from which we can annually track trends in the global status of plant and fungal diversity