Communities face the challenge of finding restoration strategies in the aftermath of disasters. In particular, independent and self-interested utility managers devise such strategies for infrastructure through a heuristic decentralized process. This paper takes a game-theoretic approach to model the decentralized and strategic restoration decision making with application to interdependent infrastructure. Particularly, we model the decision process using simultaneous games to investigate decision makers\' conflicting preferences. We employ Bayesian games to incorporate the realistic assumptions of poor interagent communication, resulting in incomplete information. Also, we account for behavioral biases such as bounded rationality, cooperative behavior or lack thereof, and equality-driven resource allocations. We test our models using ideal, synthetic interdependent networks, and the realistic infrastructure of Shelby County, TN. Results show that cooperation leads to the best-performing decisions even if others are not cooperative. The necessity of cooperation is even higher when there is a dominant player whose service is vital to other players. Our sensitivity results highlight the significant influence of resource availability and allocation on the performance of restoration plans. Our approach enhances the practicality of decision models for community resilience, and unravels novel policy strategies such as cooperation incentives.

Vegetation restoration is an eco-friendly strategy for countering land degradation and biodiversity loss. Since 2000-2001, large-scale restoration projects have been performed in Southwest China, with the net primary productivity (NPP) increasing over the past two decades. However, negative ecohydrological impacts, including streamflow decline and soil moisture deficit, have been reported following afforestation. Current understanding of the permissible NPP capacity (NPPcap) and NPP potential (NPPpot) under karst and non-karst areas or planted and natural vegetations constrained by environmental factors remains unclear. Here multiple environmental drivers characterizing the heterogeneous landscape in the Xijiang River Basin (Southwest China) were employed to predict the NPPcap using a random forest model. Results showed that 85% of the area exhibited an increasing trend in NPPcap during 2001-2018. Overall, 3.50% of the area has exceeded the NPPcap, implying an excessive plantation and potential water deficit in these areas. Excluding agriculture activities, urban areas, and water bodies, we found there is room for an average extra 22.85% of NPP enhancement. The NPPpot was spatially imbalanced, with high NPPpot located in the northeast, indicating these areas as a target area for future vegetation restoration. Moreover, the NPPpot reduction in karst areas (1.12 g C m-2 a-1) was more pronounced than in non-karst areas (0.26 g C m-2 a-1), highlighting a stronger negative impact on NPPpot in karst areas. Furthermore, significant NPPpot differences were found between planted vegetation and natural vegetation for both karst and non-karst areas. According to the findings, we identified four separate restoration sub-zones and proposed tailored strategies to guide the implementation of future restoration efforts. Our study highlights restoration potential and where land is available for reforestation but also the urgent need for future restoration activities towards ecosystem sustainability.

In landscape-scale ecological restoration, there is an urgent need to develop participatory systematic planning strategies and prioritization schemes that are operational under current technical and legal constraints. Different stakeholder groups may differ in their choice of criteria to define critical areas for restoration. Analyzing the correspondence between stakeholder characteristics and their expressed preferences is key to understand their values and facilitate consensus among the different groups. We analyzed the participatory identification of critical areas for restoration in a Mediterranean semiarid landscape of southeastern Spain by means of two Spatial Multicriteria Analyses. The first one included 33 ecological and socioeconomic prioritization criteria. The second included 24 ecosystem services. Prioritization criteria and services and their weights were based on the preferences of 46 stakeholders. We distinguished three stakeholder groups, according to their approach to ecological restoration. Stakeholders showed similarities regarding the most important criteria and services assessed. Yet, we found contrasted opinions between the group labeled as Biodiversity, who showed preference for Regulating Services and Ecosystem Functions, and the two groups labeled as Environment, and Agriculture & other occupations who assigned the highest importance to Provisioning and Cultural Services, along with highly Anthropized Environments. Maps integrating criteria and services weighted by the different groups of stakeholders were largely coincident, because of their overall agreement and the high number of criteria and services included in the analysis. Our approach allowed the identification of consensual critical areas for restoration, which were mainly covered by shrublands and rainfed crops, and mostly characterized by low to medium supply of ecosystem services. Our study emphasizes the need to recognize and integrate different social perspectives when identifying critical areas for restoration and highlights the importance of using complementary approaches as decision-making support tools to define these areas.

Floods in coastal areas are caused by a range of complex factors such as typhoons and heavy rainfall, and this issue has become increasingly serious as interference has occurred in the social-ecological system in recent years. Given the structural limitations and high maintenance costs of the existing gray infrastructure, the need for a nature-based restoration plan utilizing green infrastructure has been raised. The purpose of this study is to simulate the restoration process through the quantification of green infrastructure effects along with resilience in disaster-prone coastal areas, and to present it as nature-based restoration planning. For this purpose, first, a disaster-prone area was derived from Haeundae-gu, Busan, Republic of Korea, which was affected by typhoons. In order to simulate the runoff from typhoon \"Chaba\" in the target area and the effects of reducing the runoff of green infrastructure, relevant data was collected and a model constructed. Finally, the effects of the green infrastructure as applied to the disaster-prone area were quantified by means of resilience and a nature-based restoration plan was presented. As a result of this study, first, the runoff reduction effect was greatest when the maximum biotope area ratio of 30% was applied to the artificial ground. In the case of the green roof, the effect was the greatest 6 h following the typhoon passing through, and the effects of the infiltration storage facility was greater 9 h following the same. Porous pavement exhibited the lowest runoff reduction effect. In terms of resilience, it was found that the system was restored to its original state after the biotope area ratio of 20% was applied. This study is significant in that it analyzes the effects of green infrastructure based upon the concept of resilience and connects them to nature-based restoration planning. Based on this, it will be provided as an important tool for planning policy management to effectively respond to future coastal disasters.

Ex situ seed banking is critical for plant conservation globally, especially for threatened floras in tropical ecosystems like Hawai\'i. Seed bank managers must maximize longevity, and species managers must plan restoration before seeds lose viability. Previous observations suggested some native Hawaiian seeds lost viability in frozen storage (-18°C). We investigated seed storage behavior in the Hawaiian flora to optimize storage conditions and recommend re-collection intervals (RCI) to maximize viability of stored seeds.
Using 20+ years of real-time seed storage viability data, we tested freeze sensitivity for 197 species and calculated RCIs for 295 species. Using paired tests of accessions stored >2 yr at 5°C and -18°C, we developed an index of relative performance to determine freeze sensitivity. We calculated RCIs at 70% of highest germination (P70).
We identified four families (Campanulaceae, Cyperaceae, Rubiaceae, and Urticaceae) and four genera with seed freeze sensitivity and six additional genera with likely freeze sensitivity. Storage longevity was variable, but 195 species had viability >70% at the most recent tests (1 to 20+ yr), 123 species had RCIs >10 yr, and 45 species had RCIs <5 yr.
Freeze sensitive storage behavior is more widely observed in Hawai\'i than any other regional flora, perhaps due to insufficient testing elsewhere. We present a new protocol to test seed freeze sensitivity, which is often not evident until 2-5 years of storage. Re-collection intervals will guide restoration practices in Hawai\'i, and results inform seed conservation efforts globally, especially tropical and subtropical regions.

Ecological restoration has widely variable outcomes from successes to partial or complete failures, and there are diverse perspectives on the factors that influence the likelihood of success. However, not much is known about how these factors are perceived, and whether people\'s perceptions match realities. We surveyed 307 people involved in the restoration of native vegetation across Australia to identify their perceptions on the factors influencing the success of restoration projects. We found that weather (particularly drought and flooding) has realized impacts on the success of restoration projects, but is not perceived to be an important risk when planning new projects. This highlights the need for better recognition and management of weather risk in restoration and a potential role of seasonal forecasting. We used restoration case studies across Australia to assess the ability of seasonal forecasts provided by the Predictive Ocean Atmosphere Model for Australia, version M24 (POAMA-2) to detect unfavorable weather with sufficient skill and lead time to be useful for restoration projects. We found that rainfall and temperature variables in POAMA-2 predicted 88% of the weather issues encountered in restoration case studies apart from strong winds and cyclones. Of those restoration case studies with predictable weather issues, POAMA-2 had the forecast skill to predict the dominant or first-encountered issue in 67% of cases. We explored the challenges associated with uptake of forecast products through consultation with restoration practitioners and developed a prototype forecast product using a local case study. Integrating seasonal forecasting into decision making through (1) identifying risk management strategies during restoration planning, (2) accessing the forecast a month prior to revegetation activities, and (3) adapting decisions if extreme weather is forecasted, is expected to improve the establishment success of restoration.