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  • 1
    Online Resource
    Online Resource
    Reimagine fire science for the anthropocene
    Oxford University Press (OUP) ; 2022
    In:  PNAS Nexus Vol. 1, No. 3 ( 2022-07-01)
    Details
    In: PNAS Nexus, Oxford University Press (OUP), Vol. 1, No. 3 ( 2022-07-01)
    Abstract: Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.
    Type of Medium: Online Resource
    ISSN: 2752-6542
    URL: Article
    DOI: 10.1093/pnasnexus/pgac115
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 3120703-0
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  • 2
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    Gradual changes in range size accompany long‐term trends in species richness
    Wiley ; 2017
    In:  Ecology Letters Vol. 20, No. 9 ( 2017-09), p. 1148-1157
    Details
    In: Ecology Letters, Wiley, Vol. 20, No. 9 ( 2017-09), p. 1148-1157
    Abstract: Species richness has long been used as an indicator of ecosystem functioning and health. Global richness is declining, but it is unclear whether sub‐global trends differ. Regional trends are especially understudied, with most focused on island regions where richness is strongly impacted by novel colonisations. We addressed this knowledge gap by testing for multi‐decade trends in species richness in nine open marine regions around North America (197 region‐years) while accounting for imperfect observations and grounding our findings in species‐level range dynamics. We found positive richness trends in eight of nine regions, four of which were statistically significant. Species' range sizes generally contracted pre‐extinction and expanded post‐colonisation, but the ranges of transient species expanded over the long‐term, slowly increasing their regional retention and driving increasing richness. These results provide more evidence that sub‐global richness trends are stable or increasing, and highlight the utility of range size for understanding richness dynamics.
    Type of Medium: Online Resource
    ISSN: 1461-023X , 1461-0248
    URL: Issue
    URL: Article
    DOI: 10.1111/ele.2017.20.issue-9
    DOI: 10.1111/ele.12812
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2020195-3
    SSG: 12
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  • 3
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    Demographic consequences of phenological asynchrony for North American songbirds
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 28 ( 2023-07-11)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 28 ( 2023-07-11)
    Abstract: Changes in phenology in response to ongoing climate change have been observed in numerous taxa around the world. Differing rates of phenological shifts across trophic levels have led to concerns that ecological interactions may become increasingly decoupled in time, with potential negative consequences for populations. Despite widespread evidence of phenological change and a broad body of supporting theory, large-scale multitaxa evidence for demographic consequences of phenological asynchrony remains elusive. Using data from a continental-scale bird-banding program, we assess the impact of phenological dynamics on avian breeding productivity in 41 species of migratory and resident North American birds breeding in and around forested areas. We find strong evidence for a phenological optimum where breeding productivity decreases in years with both particularly early or late phenology and when breeding occurs early or late relative to local vegetation phenology. Moreover, we demonstrate that landbird breeding phenology did not keep pace with shifts in the timing of vegetation green-up over a recent 18-y period, even though avian breeding phenology has tracked green-up with greater sensitivity than arrival for migratory species. Species whose breeding phenology more closely tracked green-up tend to migrate shorter distances (or are resident over the entire year) and breed earlier in the season. These results showcase the broadest-scale evidence yet of the demographic impacts of phenological change. Future climate change–associated phenological shifts will likely result in a decrease in breeding productivity for most species, given that bird breeding phenology is failing to keep pace with climate change.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2221961120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 4
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    Decadal‐scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem
    Wiley ; 2022
    In:  Global Change Biology Vol. 28, No. 16 ( 2022-08), p. 4989-5005
    Details
    In: Global Change Biology, Wiley, Vol. 28, No. 16 ( 2022-08), p. 4989-5005
    Abstract: Species' response to rapid climate change can be measured through shifts in timing of recurring biological events, known as phenology. The Gulf of Maine is one of the most rapidly warming regions of the ocean, and thus an ideal system to study phenological and biological responses to climate change. A better understanding of climate‐induced changes in phenology is needed to effectively and adaptively manage human‐wildlife conflicts. Using data from a 20+ year marine mammal observation program, we tested the hypothesis that the phenology of large whale habitat use in Cape Cod Bay has changed and is related to regional‐scale shifts in the thermal onset of spring. We used a multi‐season occupancy model to measure phenological shifts and evaluate trends in the date of peak habitat use for North Atlantic right ( Eubalaena glacialis ), humpback ( Megaptera novaeangliae ), and fin ( Balaenoptera physalus ) whales. The date of peak habitat use shifted by +18.1 days (0.90 days/year) for right whales and +19.1 days (0.96 days/year) for humpback whales. We then evaluated interannual variability in peak habitat use relative to thermal spring transition dates (STD), and hypothesized that right whales, as planktivorous specialist feeders, would exhibit a stronger response to thermal phenology than fin and humpback whales, which are more generalist piscivorous feeders. There was a significant negative effect of western region STD on right whale habitat use, and a significant positive effect of eastern region STD on fin whale habitat use indicating differential responses to spatial seasonal conditions. Protections for threatened and endangered whales have been designed to align with expected phenology of habitat use. Our results show that whales are becoming mismatched with static seasonal management measures through shifts in their timing of habitat use, and they suggest that effective management strategies may need to alter protections as species adapt to climate change.
    Type of Medium: Online Resource
    ISSN: 1354-1013 , 1365-2486
    URL: Issue
    URL: Article
    DOI: 10.1111/gcb.v28.16
    DOI: 10.1111/gcb.16225
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2020313-5
    SSG: 12
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  • 5
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    Standards and Best Practices for Monitoring and Benchmarking Insects
    Frontiers Media SA ; 2021
    In:  Frontiers in Ecology and Evolution Vol. 8 ( 2021-1-15)
    Details
    In: Frontiers in Ecology and Evolution, Frontiers Media SA, Vol. 8 ( 2021-1-15)
    Abstract: Benchmark studies of insect populations are increasingly relevant and needed amid accelerating concern about insect trends in the Anthropocene. The growing recognition that insect populations may be in decline has given rise to a renewed call for insect population monitoring by scientists, and a desire from the broader public to participate in insect surveys. However, due to the immense diversity of insects and a vast assortment of data collection methods, there is a general lack of standardization in insect monitoring methods, such that a sudden and unplanned expansion of data collection may fail to meet its ecological potential or conservation needs without a coordinated focus on standards and best practices. To begin to address this problem, we provide simple guidelines for maximizing return on proven inventory methods that will provide insect benchmarking data suitable for a variety of ecological responses, including occurrence and distribution, phenology, abundance and biomass, and diversity and species composition. To track these responses, we present seven primary insect sampling methods—malaise trapping, light trapping, pan trapping, pitfall trappings, beating sheets, acoustic monitoring, and active visual surveys—and recommend standards while highlighting examples of model programs. For each method, we discuss key topics such as recommended spatial and temporal scales of sampling, important metadata to track, and degree of replication needed to produce rigorous estimates of ecological responses. We additionally suggest protocols for scalable insect monitoring, from backyards to national parks. Overall, we aim to compile a resource that can be used by diverse individuals and organizations seeking to initiate or improve insect monitoring programs in this era of rapid change.
    Type of Medium: Online Resource
    ISSN: 2296-701X
    URL: Article
    DOI: 10.3389/fevo.2020.579193
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2745634-1
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  • 6
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    Spatial thinning and class balancing: Key choices lead to variation in the performance of species distribution models with citizen science data
    Wiley ; 2021
    In:  Methods in Ecology and Evolution Vol. 12, No. 2 ( 2021-02), p. 216-226
    Details
    In: Methods in Ecology and Evolution, Wiley, Vol. 12, No. 2 ( 2021-02), p. 216-226
    Abstract: Spatial biases are a common feature of presence–absence data from citizen scientists. Spatial thinning can mitigate errors in species distribution models (SDMs) that use these data. When detections or non‐detections are rare, however, SDMs may suffer from class imbalance or low sample size of the minority (i.e. rarer) class. Poor predictions can result, the severity of which may vary by modelling technique. To explore the consequences of spatial bias and class imbalance in presence–absence data, we used eBird citizen science data for 102 bird species from the northeastern USA to compare spatial thinning, class balancing and majority‐only thinning (i.e. retaining all samples of the minority class). We created SDMs using two parametric or semi‐parametric techniques (generalized linear models and generalized additive models) and two machine learning techniques (random forest and boosted regression trees). We tested the predictive abilities of these SDMs using an independent and systematically collected reference dataset with a combination of discrimination (area under the receiver operator characteristic curve; true skill statistic; area under the precision‐recall curve) and calibration (Brier score; Cohen's kappa) metrics. We found large variation in SDM performance depending on thinning and balancing decisions. Across all species, there was no single best approach, with the optimal choice of thinning and/or balancing depending on modelling technique, performance metric and the baseline sample prevalence of species in the data. Spatially thinning all the data was often a poor approach, especially for species with baseline sample prevalence 〈 0.1. For most of these rare species, balancing classes improved model discrimination between presence and absence classes using machine learning techniques, but typically hindered model calibration. Baseline sample prevalence, sample size, modelling approach and the intended application of SDM output—whether discrimination or calibration—should guide decisions about how to thin or balance data, given the considerable influence of these methodological choices on SDM performance. For prognostic applications requiring good model calibration (vis‐à‐vis discrimination), the match between sample prevalence and true species prevalence may be the overriding feature and warrants further investigation.
    Type of Medium: Online Resource
    ISSN: 2041-210X , 2041-210X
    URL: Issue
    URL: Article
    DOI: 10.1111/mee3.v12.2
    DOI: 10.1111/2041-210X.13525
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2528492-7
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  • 7
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    Migratory strategy drives species-level variation in bird sensitivity to vegetation green-up
    Springer Science and Business Media LLC ; 2021
    In:  Nature Ecology & Evolution Vol. 5, No. 7 ( 2021-04-29), p. 987-994
    Details
    In: Nature Ecology & Evolution, Springer Science and Business Media LLC, Vol. 5, No. 7 ( 2021-04-29), p. 987-994
    Type of Medium: Online Resource
    ISSN: 2397-334X
    URL: Article
    DOI: 10.1038/s41559-021-01442-y
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2879715-2
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  • 8
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    Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat
    Wiley ; 2023
    In:  Diversity and Distributions Vol. 29, No. 9 ( 2023-09), p. 1141-1156
    Details
    In: Diversity and Distributions, Wiley, Vol. 29, No. 9 ( 2023-09), p. 1141-1156
    Abstract: Citizen science is a cost‐effective potential source of invasive species occurrence data. However, data quality issues due to unstructured sampling approaches may discourage the use of these observations by science and conservation professionals. This study explored the utility of low‐structure iNaturalist citizen science data in invasive plant monitoring. We first examined the prevalence of invasive taxa in iNaturalist plant observations and sampling biases associated with these data. Using four invasive species as examples, we then compared iNaturalist and professional agency observations and used the two datasets to model suitable habitat for each species. Location Hawai'i, USA. Methods To estimate the prevalence of invasive plant data, we compared the number of species and observations recorded in iNaturalist to botanical checklists for Hawai'i. Sampling bias was quantified along gradients of site accessibility, protective status and vegetation disturbance using a bias index. Habitat suitability for four invasive species was modelled in Maxent, using observations from iNaturalist, professional agencies and stratified subsets of iNaturalist data. Results iNaturalist plant observations were biased towards invasive species, which were frequently recorded in areas with higher road/trail density and vegetation disturbance. Professional observations of four example invasive species tended to occur in less accessible, native‐dominated sites. Habitat suitability models based on iNaturalist versus professional data showed moderate overlap and different distributions of suitable habitat across vegetation disturbance classes. Stratifying iNaturalist observations had little effect on how suitable habitat was distributed for the species modelled in this study. Main Conclusions Opportunistic iNaturalist observations have the potential to complement and expand professional invasive plant monitoring, which we found was often affected by inverse sampling biases. Invasive species represented a high proportion of iNaturalist plant observations, and were recorded in environments that were not captured by professional surveys. Combining the datasets thus led to more comprehensive estimates of suitable habitat.
    Type of Medium: Online Resource
    ISSN: 1366-9516 , 1472-4642
    URL: Issue
    URL: Article
    DOI: 10.1111/ddi.v29.9
    DOI: 10.1111/ddi.13749
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2020139-4
    detail.hit.zdb_id: 1443181-6
    SSG: 12
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  • 9
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    The importance of accounting for imperfect detection when estimating functional and phylogenetic community structure
    Wiley ; 2018
    In:  Ecology Vol. 99, No. 9 ( 2018-09), p. 2103-2112
    Details
    In: Ecology, Wiley, Vol. 99, No. 9 ( 2018-09), p. 2103-2112
    Abstract: Incorporating imperfect detection when estimating species richness has become commonplace in the past decade. However, the question of how imperfect detection of species affects estimates of functional and phylogenetic community structure remains untested. We used long‐term counts of breeding bird species that were detected at least once on islands in a land‐bridge island system, and employed multi‐species occupancy models to assess the effects of imperfect detection of species on estimates of bird diversity and community structure by incorporating species traits and phylogenies. Our results showed that taxonomic, functional, and phylogenetic diversity were all underestimated significantly as a result of species’ imperfect detection, with taxonomic diversity showing the greatest bias. The functional and phylogenetic structure calculated from observed communities were both more clustered than those from the detection‐corrected communities due to missed distinct species. The discrepancy between observed and estimated diversity differed according to the measure of biodiversity employed. Our study demonstrates the importance of accounting for species’ imperfect detection in biodiversity studies, especially for functional and phylogenetic community ecology, and when attempting to infer community assembly processes. With datasets that allow for detection‐corrected community structure, we can better estimate diversity and infer the underlying mechanisms that structure community assembly, and thus make reliable management decisions for the conservation of biodiversity.
    Type of Medium: Online Resource
    ISSN: 0012-9658 , 1939-9170
    URL: Issue
    URL: Article
    DOI: 10.1002/ecy.2018.99.issue-9
    DOI: 10.1002/ecy.2438
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1797-8
    detail.hit.zdb_id: 2010140-5
    SSG: 12
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  • 10
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    The pet trade's role in defaunation
    American Association for the Advancement of Science (AAAS) ; 2017
    In:  Science Vol. 356, No. 6341 ( 2017-06-02), p. 916-916
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 356, No. 6341 ( 2017-06-02), p. 916-916
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.aan5158
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2017
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
    SSG: 11
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