Radial Density Statistics of the Galaxy Distribution and the Luminosity Function

This paper discusses a connection between the relativistic number counts of cosmological sources and the observed galaxy luminosity function (LF). Observational differential number densities are defined and obtained from published LF data using such connection. We observe a distortion in the observational quantities that increases with higher redshift values as compared to the theoretical predictions. The use of different cosmological distance measures plays a role in such a distortionComment: 3 pages, 3 figures. Abridged version of arXiv:1201.557

Galaxy Cosmological Mass Function

We study the galaxy cosmological mass function (GCMF) in a semi-empirical relativistic approach using observational data provided by galaxy redshift surveys. Starting from the theory of Ribeiro & Stoeger (2003, arXiv:astro-ph/0304094) between the mass-to-light ratio, the selection function obtained from the luminosity function (LF) data and the luminosity density, the average luminosity $L$ and the average galactic mass $\mathcal{M}_g$ are computed in terms of the redshift. $\mathcal{M}_g$ is also alternatively estimated by a method that uses the galaxy stellar mass function (GSMF). Comparison of these two forms of deriving the average galactic mass allows us to infer a possible bias introduced by the selection criteria of the survey. We used the FORS Deep Field galaxy survey sample of 5558 galaxies in the redshift range $0.5 < z < 5.0$ and its LF Schechter parameters in the B-band, as well as this sample's stellar mass-to-light ratio and its GSMF data. Assuming ${\mathcal{M}_{g_0}} \approx 10^{11} \mathcal{M}_\odot$ as the local value of the average galactic mass, the LF approach results in $L_{B} \propto (1+z)^{(2.40 \pm 0.03)}$ and $\mathcal{M}_g \propto (1+z)^{(1.1\pm0.2)}$. However, using the GSMF results produces $\mathcal{M}_g \propto (1+z)^{(-0.58 \pm 0.22)}$. We chose the latter result as it is less biased. We then obtained the theoretical quantities of interest, such as the differential number counts, to calculate the GCMF, which can be fitted by a Schechter function. The derived GCMF follows theoretical predictions in which the less massive objects form first, being followed later by more massive ones. In the range $0.5 < z < 2.0$ the GCMF has a strong variation that can be interpreted as a higher rate of galaxy mergers or as a strong evolution in the star formation history of these galaxies.Comment: In memory of William R. Stoeger (1943-2014). LaTeX, 8 pages, 7 figures. Minor changes to match version sent to publisher. To appear in "Astronomy and Astrophysics

Biophysical suitability, economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R 2 = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R 2 = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage

Global priority areas for ecosystem restoration

Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity1 and stabilizing the climate of the Earth2. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2—30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.Fil: Strassburg, Bernardo B. N.. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal do Rio de Janeiro; BrasilFil: Iribarrem, Alvaro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Beyer, Hawthorne L.. The University of Queensland; Australia. University of Queensland; AustraliaFil: Cordeiro, Carlos Leandro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Crouzeilles, Renato. Universidade Federal do Rio de Janeiro; Brasil. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Jakovac, Catarina C.. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Braga Junqueira, André. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Lacerda, Eduardo. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal Fluminense; BrasilFil: Latawiec, Agnieszka E.. University of East Anglia; Reino Unido. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Balmford, Andrew. University of Cambridge; Estados UnidosFil: Brooks, Thomas M.. University Of The Philippines Los Banos; Filipinas. Institute For Marine And Antarctic Studies; Australia. International Union For Conservation Of Nature And Natural Resources; SuizaFil: Butchart, Stuart H. M.. University of Cambridge; Estados UnidosFil: Chazdon, Robin L.. University Of The Sunshine Coast; Australia. University of Connecticut; Estados UnidosFil: Erb, Karl-Heinz. Universitat Fur Bodenkultur Wien; AustriaFil: Brancalion, Pedro. Universidade de Sao Paulo; BrasilFil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino UnidoFil: Cooper, David. Secretariat Of The Convention On Biological Diversity; CanadáFil: Díaz, Sandra Myrna. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Donald, Paul F.. University of Cambridge; Estados UnidosFil: Kapos, Valerie. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Leclère, David. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Miles, Lera. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Obersteiner, Michael. Oxford Social Sciences Division; Reino Unido. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Plutzar, Christoph. Universitat Fur Bodenkultur Wien; Austria. Universidad de Viena; AustriaFil: de M. Scaramuzza, Carlos Alberto. International Institute For Sustainability; BrasilFil: Scarano, Fabio R.. Universidade Federal do Rio de Janeiro; BrasilFil: Visconti, Piero. International Institute For Applied Systems Analysis, Laxenburg; Austri

Why 'blended finance' could help transitions to sustainable landscapes: Lessons from the Unlocking Forest Finance project

status: publishe

Data from: Ecological restoration success is higher for natural regeneration than for active restoration in tropical forests

Is active restoration the best approach to achieve ecological restoration success (the return to a reference condition, that is, old-growth forest) when compared to natural regeneration in tropical forests? Our meta-analysis of 133 studies demonstrated that natural regeneration surpasses active restoration in achieving tropical forest restoration success for all three biodiversity groups (plants, birds, and invertebrates) and five measures of vegetation structure (cover, density, litter, biomass, and height) tested. Restoration success for biodiversity and vegetation structure were 34 to 56% and 19 to 56% higher in natural regeneration than in active restoration systems, respectively, after controlling for key biotic and abiotic factors (forest amount, precipitation, time elapsed since restoration started, and past disturbance). Biodiversity responses were based primarily on ecological metrics of abundance and species richness (74%), both of which take far less time to achieve restoration success than similarity and composition. This finding challenges the widely held notion that natural forest regeneration has limited conservation value and that active restoration should be the default ecological restoration strategy. The proposition that active restoration achieves greater restoration success than natural regeneration may have arisen because of comparisons lacking controlled biotic and abiotic factors. We did not find any difference between active restoration and natural regeneration outcomes for vegetation structure when we did not control for these factors. Future policy priorities should align the identified patterns of biophysical and ecological conditions where each or both restoration approaches are more successful, cost-effective, and compatible with socioeconomic incentives for tropical forest restoration

Costs and carbon benefits of mangrove conservation and restoration: A global analysis

Blue carbon in mangroves represents one of highest values of carbon stocks per hectare, and could play an important role in climate change mitigation. In this study we estimated the carbon prices needed to promote mangrove conservation and restoration under mechanisms of payment for ecosystem services (PES). We mapped the remaining and deforested mangroves across the globe in 2017, and crossed this information with carbon stocks in the biomass and soil and with land opportunity and restoration costs. In accordance with previous studies we found that Southeast Asia holds the largest opportunities for blue carbon programs to support conservation and restoration. Conserving remaining mangroves would avoid the release of up to 15.51 PgCO2 to the atmosphere, and could be achieved at carbon prices between 3.0 and 13.0 US$per tCO2 for 90$ per tCO2 could support the restoration of 90% of deforested mangroves. Such prices, however, may not apply to contexts of high-profit alternative land-uses. In such contexts, the valuation of co-benefits and the combination of carbon-based mechanisms and sustainable management may be a viable pathway

Corrigendum to costs and carbon benefits of mangrove conservation and restoration: a global analysis (Ecological Economics

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Early response of soil properties under different restoration strategies in tropical hotspot

The Brazilian Atlantic Forest has undergone adverse land-use change due to deforestation for urbanization and agriculture. Numerous restoration initiatives have been taken to restore its ecosystem services. Deforested areas have been restored through active intervention or natural regeneration. Understanding the impact of those different reforestation approaches on soil quality should provide important scientific and practical conclusions on increasing forest cover in the Brazilian Atlantic Forest biome. However, studies evaluating active planting versus natural regeneration in terms of soil recovery are scarce. We evaluate soil dynamics under those two contrasting strategies at an early stage (<10 years). Reforestation was conducted simultaneously on degraded lands previously used for cattle grazing and compared to an abandoned pasture as a reference system. We examined soil physicochemical properties such as: PH, soil organic matter content, soil moisture, N, P, K, Ca, Mg, Na, Fe, Mn, Cu, Al, and soil texture. We also present the costs of both methods. We found significant differences in restored areas regarding pH, Na, Fe, Mn content, and the cost. Soil moisture was significantly higher in pasture. Our research can contribute to better decision-making about which restoration strategy to adopt to maximize restoration success regarding soil quality and ecosystem services in the tropics