Integrating both restoration and regeneration potentials into real-world forest restoration planning: A case study of Hong Kong.

Forest restoration is a vital nature-based solution for mitigating climate change and land degradation. To ensure restoration effectiveness, the costs and benefits of alternative restoration strategies (i.e., active restoration vs. natural regeneration) need to be evaluated. Existing studies generally focus on maximum restoration potential, neglecting the recovery potential achievable through natural regeneration processes, leading to incomplete understanding of the true benefits and doubts about the necessity of active restoration. In this study, we introduce a multi-stage framework incorporating both restoration and regeneration potential into prioritized planning for ecosystem restoration. We used the vegetated landscape of Hong Kong (covering 728 km2) as our study system due to its comprehensive fine-resolution data and unique history of vegetation recovery, making it an ideal candidate to demonstrate the importance of this concept and inspire further research. We analyzed vegetation recovery status (i.e., recovering, degrading, and stable) over the past decade based on the canopy height data derived from multi-temporal airborne LiDAR. We assessed natural regeneration potential and maximum restoration potential separately, producing spatially-explicit predictions. Our results show that 44.9% of Hong Kong's vegetated area has showed evidence of recovery, but remaining gains through natural regeneration are limited, constituting around 4% of what could be attained through active restoration. We further estimated restoration priority by maximizing the restoration gain. When prioritizing 5% of degraded areas, the increment in canopy height could be up to 10.9%. Collectively, our findings highlight the importance of integrating both restoration and regeneration potential into restoration planning. The proposed framework can aid policymakers and land managers in optimizing forest restoration options and promoting the protection and recovery of fragile ecosystems.

Does plant ecosystem thermoregulation occur? An extratropical assessment at different spatial and temporal scales.

To what degree plant ecosystems thermoregulate their canopy temperature (Tc ) is critical to assess ecosystems' metabolisms and resilience with climate change, but remains controversial, with opinions from no to moderate thermoregulation capability. With global datasets of Tc , air temperature (Ta ), and other environmental and biotic variables from FLUXNET and satellites, we tested the 'limited homeothermy' hypothesis (indicated by Tc & Ta regression slope < 1 or Tc < Ta around midday) across global extratropics, including temporal and spatial dimensions. Across daily to weekly and monthly timescales, over 80% of sites/ecosystems have slopes ≥1 or Tc > Ta around midday, rejecting the above hypothesis. For those sites unsupporting the hypothesis, their Tc -Ta difference (ΔT) exhibits considerable seasonality that shows negative, partial correlations with leaf area index, implying a certain degree of thermoregulation capability. Spatially, site-mean ΔT exhibits larger variations than the slope indicator, suggesting ΔT is a more sensitive indicator for detecting thermoregulatory differences across biomes. Furthermore, this large spatial-wide ΔT variation (0-6°C) is primarily explained by environmental variables (38%) and secondarily by biotic factors (15%). These results demonstrate diverse thermoregulation patterns across global extratropics, with most ecosystems negating the 'limited homeothermy' hypothesis, but their thermoregulation still occurs, implying that slope < 1 or Tc < Ta are not necessary conditions for plant thermoregulation.

Estimating changes and trends in ecosystem extent with dense time-series satellite remote sensing.

Quantifying trends in ecosystem extent is essential to understanding the status of ecosystems. Estimates of ecosystem loss are widely used to track progress toward conservation targets, monitor deforestation, and identify ecosystems undergoing rapid change. Satellite remote sensing has become an important source of information for estimating these variables. Despite regular acquisition of satellite data, many studies of change in ecosystem extent use only static snapshots, which ignores considerable amounts of data. This approach limits the ability to explicitly estimate trend uncertainty and significance. Assessing the accuracy of multiple snapshots also requires time-series reference data which is often very costly and sometimes impossible to obtain. We devised a method of estimating trends in ecosystem extent that uses all available Landsat satellite imagery. We used a dense time series of classified maps that explicitly accounted for covariates that affect extent estimates (e.g., time, cloud cover, and seasonality). We applied this approach to the Hukaung Valley Wildlife Sanctuary, Myanmar, where rapid deforestation is greatly affecting the lowland rainforest. We applied a generalized additive mixed model to estimate forest extent from more than 650 Landsat image classifications (1999-2018). Forest extent declined significantly at a rate of 0.274%/year (SE = 0.078). Forest extent declined from 91.70% (SE = 0.02) of the study area in 1999 to 86.52% (SE = 0.02) in 2018. Compared with the snapshot method, our approach improved estimated trends of ecosystem loss by allowing significance testing with confidence intervals and incorporation of nonlinear relationships. Our method can be used to identify significant trends over time, reduces the need for extensive reference data through time, and provides quantitative estimates of uncertainty.

Estimación de los Cambios y Tendencias en la Extensión de los Ecosistemas Mediante Teledetección Satelital de Series Temporales Densas Resumen Las tendencias de cuantificación de la extensión de los ecosistemas es esencial para el entendimiento de su estado. Las estimaciones de pérdidas de los ecosistemas se usan con amplitud para rastrear el progreso hacia los objetivos de conservación, monitorear la deforestación e identificar a los ecosistemas que están experimentando un cambio rápido. La teledetección satelital se ha transformado en una fuente importante de información para la estimación de estas variables. A pesar de la obtención de datos satelitales, muchos estudios sobre el cambio en la extensión de los ecosistemas usan solamente capturas estáticas, lo cual ignora cantidades considerables de datos. Esta estrategia limita la habilidad que se tiene para estimar explícitamente la incertidumbre e importancia de la tendencia. La valoración de la precisión de múltiples capturas también requiere datos de referencia de series temporales, lo cual es muy costoso e imposible de conseguir en algunos casos. Diseñamos un método para estimar las tendencias en la extensión de los ecosistemas que usa todas las imágenes satelitales disponibles en Landsat. Usamos una serie temporal densa de los mapas clasificados que considera explícitamente a las covarianzas que afectan a las estimaciones de la extensión (p.ej.: tiempo, cobertura de nubes y estacionalidad). Aplicamos esta estrategia en el Santuario de Vida Silvestre del Valle de Huakaung en Myanmar, en donde la deforestación acelerada está afectando enormemente a la selva de tierras bajas. Aplicamos también un modelo mixto, aditivo y generalizado para estimar la extensión del bosque a partir de más de 650 clasificaciones de imágenes en Landsat (1999 - 2018). La extensión del bosque declinó significativamente a una tasa de 0.274%/año (SE 0.078). La extensión del bosque declinó del 91.70% (SE 0.02) del área de estudio en 1999 a 86.52% (SE 0.02) en 2018. Si la comparamos con la estrategia de las capturas, nuestra estrategia mejoró las tendencias estimadas de la pérdida del ecosistema al permitir la evaluación de significancia con intervalos de confianza y la incorporación de relaciones no lineales. Nuestro método puede usarse para identificar las tendencias significativas a lo largo del tiempo; también reduce la necesidad de tener datos de referencia extensos a lo largo del tiempo y proporciona estimaciones cuantitativas de la incertidumbre.

In vitro-matured rat oocytes have low mitochondrial deoxyribonucleic acid and adenosine triphosphate contents and have abnormal mitochondrial redistribution.

OBJECTIVE: To study the development and function of mitochondria in in vitro-matured rat oocytes derived from follicles of different sizes. DESIGN: Experimental animal study. SETTING: Department of Anatomy at the University of Hong Kong. ANIMAL(S): Immature female Sprague-Dawley rats that were 25 days of age. INTERVENTION(S): Immature oocytes were collected from rat ovarian follicles of different sizes and were induced to mature in vitro. MAIN OUTCOME MEASURE(S): The number of copies of mitochondrial DNA, mitochondrial activity, adenosine triphosphate content of matured oocytes, and rates of fertilization and blastulation were determined. RESULT(S): The mitochondrial DNA copy number of oocytes increased linearly with the diameter of antral follicles. The mitochondrial DNA copy number, adenosine triphosphate content, and proportion of oocytes with peripheral distribution of mitochondria in in vitro-matured oocytes from small antral follicles were significantly lower than those from preovulatory follicles and in vivo-matured oocytes. Compared with in vitro-matured oocytes from small antral follicles, those from preovulatory follicles and in vivo-matured oocytes also had significantly better fertilization potential and higher blastulation rate. CONCLUSION(S): The inferior developmental potential of in vitro-matured oocytes may be attributed partly to a reduced number of mitochondria, resulting in insufficient production of adenosine triphosphate for required developmental events.