North American Breeding Bird Survey Underestimates Regional Bird Richness Compared to Breeding Bird Atlases

Standardized data on large-scale and long-term patterns of species richness are critical for understanding the consequences of natural and anthropogenic changes in the environment. The North American Breeding Bird Survey (BBS) is one of the largest and most widely used sources of such data, but so far, little is known about the degree to which BBS data provide accurate estimates of regional richness. Here, we test this question by comparing estimates of regional richness based on BBS data with spatially and temporally matched estimates based on state Breeding Bird Atlases (BBA). We expected that estimates based on BBA data would provide a more complete (and therefore, more accurate) representation of regional richness due to their larger number of observation units and higher sampling effort within the observation units. Our results were only partially consistent with these predictions: while estimates of regional richness based on BBA data were higher than those based on BBS data, estimates of local richness (number of species per observation unit) were higher in BBS data. The latter result is attributed to higher land-cover heterogeneity in BBS units and higher effectiveness of bird detection (more species are detected per unit time). Interestingly, estimates of regional richness based on BBA blocks were higher than those based on BBS data even when differences in the number of observation units were controlled for. Our analysis indicates that this difference was due to higher compositional turnover between BBA units, probably due to larger differences in habitat conditions between BBA units and a higher likelihood of observing geographically restricted species. Our overall results indicate that estimates of regional richness based on BBS data suffer from incomplete detection of a large number of rare species, and that corrections of these estimates based on standard extrapolation techniques are not sufficient to remove this bias. Future applications of BBS data in ecology and conservation, and in particular, applications in which the representation of rare species is important (e.g., those focusing on biodiversity conservation), should be aware of this bias, and should integrate BBA data whenever possible

Cryptosporidium Priming Is More Effective than Vaccine for Protection against Cryptosporidiosis in a Murine Protein Malnutrition Model

Cryptosporidium is a major cause of severe diarrhea, especially in malnourished children. Using a murine model of C. parvum oocyst challenge that recapitulates clinical features of severe cryptosporidiosis during malnutrition, we interrogated the effect of protein malnutrition (PM) on primary and secondary responses to C. parvum challenge, and tested the differential ability of mucosal priming strategies to overcome the PM-induced susceptibility. We determined that while PM fundamentally alters systemic and mucosal primary immune responses to Cryptosporidium, priming with C. parvum (106 oocysts) provides robust protective immunity against re-challenge despite ongoing PM. C. parvum priming restores mucosal Th1-type effectors (CD3+CD8+CD103+ T-cells) and cytokines (IFNγ, and IL12p40) that otherwise decrease with ongoing PM. Vaccination strategies with Cryptosporidium antigens expressed in the S. Typhi vector 908htr, however, do not enhance Th1-type responses to C. parvum challenge during PM, even though vaccination strongly boosts immunity in challenged fully nourished hosts. Remote non-specific exposures to the attenuated S. Typhi vector alone or the TLR9 agonist CpG ODN-1668 can partially attenuate C. parvum severity during PM, but neither as effectively as viable C. parvum priming. We conclude that although PM interferes with basal and vaccine-boosted immune responses to C. parvum, sustained reductions in disease severity are possible through mucosal activators of host defenses, and specifically C. parvum priming can elicit impressively robust Th1-type protective immunity despite ongoing protein malnutrition. These findings add insight into potential correlates of Cryptosporidium immunity and future vaccine strategies in malnourished children

Constructing a Comprehensive National Wildfire Database from Incomplete Sources: Israel as a Case Study

In many regions, the frequency and extent of wildfires has increased in recent years, a trend which is expected to continue. Hence, there is a need for effective fire management strategies. Such strategies need to be based on accurate and complete data on vegetation condition and post-fire effects, collected in the field as well as by remote sensing approaches. Unfortunately, wildfire databases are often incomplete in terms of their spatial and temporal coverage, as well as the documentation of fire outcomes. The aim of this study was to devise a methodology to construct a comprehensive national wildfire database. We developed and tested this methodology for Israel, as a case study. The methodology combines data on wildfires in Israel from two sources: remote sensing and field data collected by governmental agencies, representing the period between 2015 and 2022. The resulting database contains 2276 wildfires larger than 10 ha with information (where and when available) on their occurrence date, fire duration, ignition cause, and more. The methodology presented here provides a blueprint for developing large-scale and comprehensive fire databases elsewhere, and facilitates future studies on wildfire risk by providing a robust, unified database of the fire history of Israel from 2015 onwards