Abstract
Many ecologists have lamented the demise of natural history and have attributed this decline to a misguided view that natural history is outdated and unscientific. Although there is a perception that the focus in ecology and conservation have shifted away from descriptive natural history research and training toward hypothetico-deductive research, we argue that natural history has entered a new phase that we call “next-generation natural history.” This renaissance of natural history is characterized by technological and statistical advances that aid in collecting detailed observations systematically over broad spatial and temporal extents. The technological advances that have increased exponentially in the last decade include electronic sensors such as camera-traps and acoustic recorders, aircraft- and satellite-based remote sensing, animal-borne biologgers, genetics and genomics methods, and community science programs. Advances in statistics and computation have aided in analyzing a growing quantity of observations to reveal patterns in nature. These robust next-generation natural history datasets have transformed the anecdotal perception of natural history observations into systematically collected observations that collectively constitute the foundation for hypothetico-deductive research and can be leveraged and applied to conservation and management. These advances are encouraging scientists to conduct and embrace detailed descriptions of nature that remain a critically important component of the scientific endeavor. Finally, these next-generation natural history observations are engaging scientists and non-scientists alike with new documentations of the wonders of nature. Thus, we celebrate next-generation natural history for encouraging people to experience nature directly.
Highlights
The term natural history is familiar to all biologists, defining its boundaries is challenging. Tewksbury et al (2014) suggested that natural history is “the observation and description of the natural world, with the study of organisms and their linkages to the environment being central.” Barrows et al (2016) more concisely defined it as the “observational study of organisms in their environment.” definitions vary, all share the central theme of “direct observation and description of organisms, communities, and habitats, including attentiveness to associated geology, hydrology, and other physical factors” (Fleischner et al, 2017)
Next-generation natural history is once again encouraging students, scientists, and non-scientists to go into the field to non-invasively observe organisms using their newfound ability to generate many natural history observations at broad spatial and temporal scales. Because these types of biomonitoring and other next-generation natural history observations amplify and build upon natural history from field notebooks into graphical or auditory forms that are viewable by the world, we argue that nextgeneration natural history has the power to inspire enthusiasm and awe, and to motivate scientific and conservation efforts
The development of occupancy models (MacKenzie et al, 2018) has allowed next-generation natural history observations, such as those collected with camera traps, bioacoustics, or environmental DNA, to produce more robust inference by disentangling the probability that a species is detected from the probability that it occurs at a given spatial location or under a given set of environmental conditions
Summary
The term natural history is familiar to all biologists, defining its boundaries is challenging. Tewksbury et al (2014) suggested that natural history is “the observation and description of the natural world, with the study of organisms and their linkages to the environment being central.” Barrows et al (2016) more concisely defined it as the “observational study of organisms in their environment.” definitions vary, all share the central theme of “direct observation and description of organisms, communities, and habitats, including attentiveness to associated geology, hydrology, and other physical factors” (Fleischner et al, 2017). We review how electronic sensors such as camera traps and acoustic recorders, aircraft- and satellite-based remote sensing of nature, animalborne biologgers, advances in genetics and genomics, and burgeoning community science programs have been used to generate robust next-generation natural history datasets (Figure 1).
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