Biology subjects

Zuckerberg, B.

Publications and source records attributed to Zuckerberg, B..

6 recordsLinked to original sources

bioRxiv2024

Ecological synchrony in human-modified landscapes under a changing climate

Different aspects of ecological systems, biotic or abiotic, often fluctuate in coordinated patterns over space and time. Such high concordance between ecological processes is often referred to as ecological synchrony. Anthropogenic activities, including and beyond climate change, have the potential to alter ecological synchrony by disrupting or enhancing existing synchrony. Despite many local studies, we have a limited systematic understanding of how ecological synchrony is shaped by management in human-dominated landscapes at regional to continental scales. From a macrosystems perspective, we review how anthropogenic activities, particularly beyond climate change, alter ecological synchrony across levels of ecological organization, from the ecosystem level to the population level. For each level, we use a large-scale case study to demonstrate ways to quantify the impacts of human modifications on synchrony using big data from remote sensing, surveys, and observatory networks. For example, we detected possible homogenization of population dynamics of bird species in North America. These changes in ecological synchrony, although in different forms, often represent challenges to ecological and social systems. Collaborative research efforts that integrate emerging open data streams moving forward will be able to provide insights into the effects of different anthropogenic drivers and the consequences of changes in synchrony.

ecology↗

bioRxiv2024

The vulnerability of overwintering insects to loss of the subnivium

Winter climate change threatens the subnivium (i.e., the microhabitat that exists between the snowpack and the ground), and the community of species that depends on it for overwintering survival. One group of species that will likely exhibit an array of responses to subnivium loss are overwintering insects because they vary in their cold tolerance strategies and lower thermal limits. For an assemblage of eight insect species that range in their cold tolerance strategies and include both pollinators and pests, we investigated species-specific vulnerabilities to shifting subnivium conditions by applying information on each species supercooling point to spatially- and temporally-explicit models of minimum subnivium temperatures for three warming scenarios in the Great Lakes region in the United States: current conditions (i.e., control), +3{degrees}C, and +5{degrees}C. Although species varied in their vulnerabilities, our predictions indicated that exposure to lethal temperatures generally decreased under warming of 3{degrees}C, but increased under warming of 5{degrees}C, indicating that once enough warming happens, a tipping point is reached. We also found that freeze-tolerant species (i.e., species that can survive at temperatures below their supercooling point) possess a more cryptic vulnerability to winter climate change because sustained below-freezing temperatures were sufficient to induce vulnerability (i.e., predicted mortality), even when temperatures were above the supercooling point. This work provides a better understanding of the vulnerability of different insect species to winter climate change, which is critical because overwintering survival and the fitness consequences incurred during overwintering likely represent important bottlenecks for the population dynamics of subnivium-dependent species.

ecology↗

bioRxiv2023

Spatial and seasonal variation in thermal sensitivity within North American bird species

Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity (non-stationarity) given adaptation to local and seasonal environments. Non-stationarity carries important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 20 bird species. Across their ranges, most birds demonstrated spatial and seasonal variation in both thermal optimum and breadth, or the temperature and range of temperatures of peak occurrence. Some birds demonstrated constant thermal optima or breadths (stationarity) while others varied according to local and current environmental conditions (non-stationarity). Across species, birds typically invested in either geographic or seasonal adaptation to climate. Intraspecific variation in thermal sensitivity is likely an important but neglected aspect of organismal responses to climate change.

ecology↗

bioRxiv2022

Rising novelty and homogenization of breeding bird communities in the U.S.

AimHuman modification has profound effects on the diversity of ecological communities. Yet, surprisingly little is known about how abiotic novelty due to human modification relates to biological novelty as measured by shifts in species composition from historical baselines. Using space-for-time substitution, we ask a) whether high human modification results in biotic homogenization or heterogenization across different spatial scales; b) if high modification results in the formation of novel, "no-analog" communities; and c) whether changes in bird community composition varies in response to proxies of historical land-use and duration-of-exposure to anthropogenic disturbances. LocationConterminous United States. Time Period2012 - 2016. Major taxa studiedPasseriformes. MethodsWe analyzed continent-wide avian biodiversity data from an online checklist program, eBird, to examine how shifts in breeding bird species composition have been impacted by human modification at regional and continental scales and tested four hypotheses related to how abiotic novelty resulting from human modification generates biological novelty. ResultsAt regional scales, bird communities in highly human-modified areas exhibited similar levels of {beta}-diversity as those in the least modified areas. However, at the continental scale, spatial turnover in community composition was lower in human-modified areas, suggesting that anthropogenic disturbance has a strong homogenizing effect on bird communities at that scale. Lastly, human modification contributed more to community composition in regions where natural disturbance was infrequent and Euro-American settlement occurred later, consistent with the hypothesis that exposure to historical disturbances can shape how contemporary bird communities respond to human modification. Main conclusionsThe observed patterns of increased biotic novelty and homogenization in regions with less frequent disturbances and a longer history of human modification suggests that future extensive human modification could result in further homogenization of bird communities, particularly in the western U.S. We argue that current human-modified environments hold great potential for biodiversity conservation.

ecology↗

bioRxiv2020

Integrating remote sensing and jurisdictional observation networks to improve the resolution of ecological management

The emergence of citizen science, passive sensors (e.g., trail cameras and acoustic monitoring), and satellite remote sensing have enabled biological data to be collected at unprecedented spatial and temporal scales. There is growing interest in networking these datastreams to expedite the collection and synthesis of environmental and biological data to improve broad-scale ecological monitoring, but there are no examples of such networks being developed to directly inform decision-making by managing agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin (SW), that links satellite remote sensing (RS) with a volunteer-based trail camera network to generate new insights into wildlife distributions and improve their management by the state agency. SW relies on citizen scientists to deploy trail cameras across the state and classify images of wildlife. As of early 2020 SW comprises nearly 1800 volunteers hosting >2100 active cameras recording >37 million images across a sampling effort of >2000 combined trap-years at >3300 distinct camera locations. We use a set of case studies to demonstrate the potential power of a JON to monitor wildlife with unprecedented combinations of spatial, temporal, and biological resolution and extent. Specifically, we demonstrate that SW markedly improves the spatial and temporal resolution with which black bear distributions can be monitored or forecast, in turn improving the resolution of decision-making. Enhancing the biological resolution of monitoring (e.g., monitoring the distribution of species traits or behaviors) may provide new insights into population drivers, such as the connection between vegetation productivity and white-tailed deer foraging behaviors. Enhanced taxonomic extent provided by trail cameras and other passive sensor networks provide managers new information for a wide range of species and communities that are not otherwise monitored. Our cases further show that JONs synergize existing monitoring practices by serving as a complementary and independent line of evidence or as a tool to enhance the extent and precision of existing models through integrated modeling approaches. SW and other JONS are a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.

ecology↗

bioRxiv2018

Generalized sample verification models to estimate ecological state variables with detection-nondetection data while accounting for imperfect detection and false positive errors.

Spatially-indexed repeated detection-nondetection data is widely collected by ecologists interested in estimating parameters associated with species distribution, relative abundance, phenology, and more while accounting for imperfect detection. Recent model development has focused on accounting for false positive error as well, given growing recognition that misclassification is common across many sampling protocols. To date, however, the development of model-based solutions to false positive error has been largely restricted to occupancy models. We describe a general form of the observation confirmation protocol originally described for occupancy estimation that permits investigators to flexibly and intuitively extend several models for detection-nondetection data to account for false positive error. Simulation results demonstrate that estimators for relative abundance and arrival time exhibit relative bias greater than 20% under realistic levels of false positive prevalence (e.g., 5% of detections are false positive). Bias increases as true and false positives occur in more distinct places or times, but can also be sensitive to the values of the state variables of interest, sampling design, and sampling efficiency. Results from an empirical study focusing on patterns of gray fox relative abundance across Wisconsin, USA suggest that false positive error can also distort estimated spatial patterns often used to guide decision-making. The extended estimators described within typically improve performance at any level of confirmation, and when false positive error occurs at random and constitutes less than 10% of all detections, the estimators are essentially unbiased when more than 50 observations can be confirmed as true or false positives. The generalized form of the observation-confirmation protocol is a flexible model-based solution to false positive error useful for researchers collecting data with sampling devices like trail or smartphone cameras, acoustic recorders, or other techniques where classifications can be reviewed post-hoc.

ecology↗