Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

High-Resolution Global Maps of 21st-Century Forest Cover Change

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.

/pdf/the-global-distribution-and-burden-of-dengue-4d1crnic4u.pdf

The global distribution and burden of dengue

Google Earth Engine: Planetary-scale geospatial analysis for everyone

Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

/pdf/climate-change-2007-the-physical-science-basis-1x93ttz9jt.pdf

Climate Change 2007: The Physical Science Basis.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/98JD00234

Reply [to “Comment on ‘Comparison of atmospheric correction models for thermal bands of the advanced very high resolution radiometer over FIFE’ by S. N. Kalluri and R. O. Dubayah”]

In his Letter to the Editor, Timoney (2022) suggests that Berner and Goetz's (2022) remote sensing assessment of an emerging boreal forest biome shift is “problematic” due to the sample size, exclusion of recently burned areas, and lack of ground validation data, as well as inconsistent with a recent study focused on western and central Canada (Timoney & Mamet, 2020). Here, we address these concerns. We analyzed 41.6 million crosscalibrated Landsat multispectral surface reflectance measurements at 100,000 randomly sampled sites across the circumboreal forest for the 1985– 2019 growing seasons. Each sample site was 900 m2. While the total sampling footprint was small (~90 km2), this broadly distributed statistical sample nevertheless enabled us to robustly infer largescale vegetation

Response to letter to the editor on “Satellite observations document trends consistent with a boreal biome shift”

The NOAA-AVHRR satellite record has provided a new view of terrestrial vegetation processes but has been exploited relatively little for the recovery of physical environment variables such as surface wetness, air temperature, or near-surface humidity. Recent advances in techniques to recover these variables over large areas has permitted the development of improved terrestrial primary production models. The authors report on the development of techniques to recover physical environment variables from 8-year time series of AVHRR observations. The recovery algorithms incorporate visible, near-infrared and thermal infrared radiation measurements in a contextual array. The accuracy of the recovered variables, when compared to surface meteorological stations over a broad range of environments, was shown to be within 95% confidence limits of /spl plusmn/6.8/spl deg/C for a 36/spl deg/C air temperature range; /spl plusmn/1.28 cm for a 3.6 cm atmospheric water vapor range; and /spl plusmn/11.2 mb for a 58 mb vapor pressure deficit range. Recovered values of surface soil moisture explained 77% of the observed variability at a temperate grassland site. Maps of retrieved variables for several study areas had good relative accuracy when compared to spatially interpolated surface observations. Multi-temporal global maps of these variables are presented and spatially analyzed relative to other information sources.

Recovery of surface environmental variables over large areas using AVHRR observations

Ecoacoustic monitoring has proliferated as autonomous recording units (ARU) have become more accessible. ARUs provide a non-invasive, passive method to assess ecosystem dynamics related to vocalizing animal behavior and human activity. With the ever-increasing volume of acoustic data, the field has grappled with summarizing ecologically meaningful patterns in recordings. Almost 70 acoustic indices have been developed that offer summarized measurements of bioacoustic activity and ecosystem conditions. However, their systematic relationships to ecologically meaningful patterns in varying sonic conditions are inconsistent and lead to non-trivial interpretations. We used an acoustic dataset of over 725,000 min of recordings across 1,195 sites in Sonoma County, California, to evaluate the relationship between 15 established acoustic indices and sonic conditions summarized using five soundscape components classified using a convolutional neural network: anthropophony (anthropogenic sounds), biophony (biotic sounds), geophony (wind and rain), quiet (lack of emergent sound), and interference (ARU feedback). We used generalized additive models to assess acoustic indices and biophony as ecoacoustic indicators of avian diversity. Models that included soundscape components explained acoustic indices with varying degrees of performance (avg. adj-R2 = 0.61 ± 0.16; n = 1,195). For example, we found the normalized difference soundscape index was the most sensitive index to biophony while being less influenced by ambient sound. However, all indices were affected by non-biotic sound sources to varying degrees. We found that biophony and acoustic indices combined were highly predictive in modeling bird species richness (deviance = 65.8%; RMSE = 3.9 species; n = 1,185 sites) for targeted, morning-only recording periods. Our analyses demonstrate the confounding effects of non-biotic soundscape components on acoustic indices, and we recommend that applications be based on anticipated sonic environments. For instance, in the presence of extensive rain and wind, we suggest using an index minimally affected by geophony. Furthermore, we provide evidence that a measure of biodiversity (bird species richness) is related to the aggregate biotic acoustic activity (biophony). This established relationship adds to recent work that identifies biophony as a reliable and generalizable ecoacoustic measure of biodiversity.

/pdf/soundscape-components-inform-acoustic-index-patterns-and-3da7ulpz.pdf

Scott J. Goetz

Papers

Reply [to “Comment on ‘Comparison of atmospheric correction models for thermal bands of the advanced very high resolution radiometer over FIFE’ by S. N. Kalluri and R. O. Dubayah”]

Response to letter to the editor on “Satellite observations document trends consistent with a boreal biome shift”

Recovery of surface environmental variables over large areas using AVHRR observations

Soundscape components inform acoustic index patterns and refine estimates of bird species richness