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The North American beaver Castor canadensis is an invasive species in the Tierra del Fuego Archipelago. Due to this biological invasion, Argentina and Chile signed an agreement to restore affected ecosystems by eradicating beavers. In southern Patagonia, the beavers' ecological impacts are well studied, but there is a relative lack of information on how their invasion (and potential removal) could affect bird communities.In the southern portion of Tierra del Fuego's 'big island' (Isla Grande), we conducted passive acoustic monitoring and avian point counts in intact riparian forests, beaver ponds and beaver meadows (i.e. drained ponds) to assess spatial and seasonal differences in acoustic activity and avian abundance, species diversity and functional diversity.During spring and summer, acoustic activity was significantly higher in meadows than in forests, with ponds exhibiting intermediate values.Abundance and species diversity exhibited similar patterns, driven largely by resident passerines, while functional diversity tended to be highest in ponds, largely due to ducks and raptors. Effects were weaker in fall and winter.Acoustic metrics exhibited moderate to strong correlations with all point‐count‐derived metrics.Synthesis and applications. At the patch level, the avian community was more abundant and diverse in beaver‐modified habitats than in intact riparian forests, though communities in modified patches may not differ substantially from those in analogous natural open and wetland habitats. Dam breaching and pond drainage did not yield a return to an intact forest bird community, indicating that active reforestation may be necessary to restore avian communities to pre‐beaver conditions in the short to medium term, as sought by the binational agreement. Given the immense challenges of eradication and restoration, its social‐ecological costs and benefits—including those related to avifauna—should be thoroughly considered in establishing goals or indicators of success. [ABSTRACT FROM AUTHOR]

Freshwater systems are globally threatened and in need of enhanced monitoring and assessment. We applied soundscape recording and analysis—which presents an opportunity for long‐term, high‐resolution animal community monitoring and assessment—to a freshwater context to better understand the acoustic diversity and dynamics of these systems.We recorded the aquatic soundscape of a Neotropical freshwater swamp in Costa Rica for 23 days in January and February 2015 during the dry season. We classified biological sound types in these recordings and developed measurements of richness and occupancy based on this classification. We also calculated six complementary acoustic indices to assess soundscape diversity and daily and longer‐term soundscape dynamics, and we examined correlations between these acoustic indices and sound type metrics.We found rich soundscapes in which biological sounds were almost always present, and we classified 18 sound types that we attribute to aquatic insects. These sound types showed distinct daily patterns and exhibited temporal and spectral acoustic niche partitioning. Sound type richness was most correlated with the number of peaks index (correlation =.36; p <.001), while sound type occupancy was most correlated with the Bioacoustic Index (correlation =.92; p <.001). In contrast to generally high levels of acoustic activity, there were brief (approximately 1 hr), unexpected quiet periods around dawn and dusk.This study represents an early attempt to comprehensively describe tropical freshwater soundscapes in a systematic and quantitative manner. We demonstrate that sound type classification and the quantification of acoustic occupancy capture aspects of soundscape diversity and dynamics that are complementary to those assessed by acoustic indices. Our analyses reveal that the soundscapes of this tropical wetland were diverse and exhibited daily dynamics that differed from those found in other ecosystems. [ABSTRACT FROM AUTHOR]

Urban change (urbanization) has dominated land change science for several decades. However, few studies have focused on what many scholars call the urban densification process (i.e., urban intensity expansion) despite its importance to both planning and subsequent impacts to the environment and local economies. This paper documents past urban densification patterns and uses this information to predict future densification trends in southeastern Wisconsin (SEWI) by using a rich dataset from the United States and by adapting the well-known Land Transformation Model (LTM) for this purpose. Urban densification is a significant and progressive process that often accompanies urbanization more generally. The increasing proportion of lower density areas, rather than higher density areas, was the main characteristic of the urban densification in SEWI from 2001 to 2011. We believe that improving urban land use efficiency to maintain rational densification are effective means toward a sustainable urban landscape. Multiple goodness-of-fit metrics demonstrated that the reconfigured LTM performed relatively well to simulate urban densification patterns in 2006 and 2011, enabling us to forecast densification to 2016 and 2021. The predicted future urban densification patterns are likely to be characterized by higher densities continue to increase at the expense of lower densities. We argue that detailed categories of urban density and specific relevant predictor variables are indispensable for densification prediction. Our study provides researchers working in land change science with important insights into urban densification process modeling. The outcome of this model can help planners to identify the current trajectory of urban development, enabling them to take informed action to promote planning objectives, which could benefit sustainable urbanization definitely. [ABSTRACT FROM AUTHOR]

• Continuous soundscape recordings were made in eight ecosystems on four continents. • Temporal variability of soundscapes was quantified using two distinct measures. • Daytime exhibited high temporal variability relative to dusk and nighttime. • Increasing evenness of subsampling distribution reduces error in representation. • Marginal precision gains diminish substantially beyond 1/3 recording time. Unprecedented rates of biodiversity loss and intensifying human attempts to rectify the biodiversity crisis have heightened the need for standardized, large-scale, long-duration biodiversity monitoring at fine temporal resolution. While some innovative technologies such as passive acoustic monitoring are well suited for such monitoring challenges, many questions remain as to how they should be scaled out and optimally implemented across ecosystems. Our research questions center on temporal sampling regimes—how frequently and how long one should collect data to represent biodiversity conditions over a given timeframe. Addressing this concern in the context of passive acoustic monitoring, we investigated whether temporal soundscape variability—the characteristic short-term acoustic change in an environment—is consistent across ecosystems and times of day, and we considered how various temporal subsampling schemes affect the representativeness of resultant acoustic index values, relative to continuous sampling. We quantified soundscape variability at eight sites across four continents based on temporal autocorrelation ranges and standard deviations of acoustic index values, and we created a heuristic model to classify types of soundscape variability based on those two variables. Drawing on values derived from three distinct acoustic indices, we found that the characteristic temporal variability of soundscapes varied between sites and times of day (dawn, daytime, dusk, and nighttime). Some sites exhibited little difference in variability between times of day whereas other sites exhibited greater within-site differences between times of day than many inter-site differences. Daytime soundscapes generally tended to exhibit more temporal variability than nighttime soundscapes. We also compared potential subsampling schemes that could be advantageous in terms of power, data storage, and data analysis costs by modeling subsample error as a function of total analysis time and number of subsamples within a larger block of time. Greater numbers of evenly distributed subdivisions drastically increased the representativeness of a sampling scheme, while increases in subsample duration yielded fairly minimal gains in representativeness between 33 and 67% of the full time one wishes to represent. Generally, our results show that for a long-term, fine temporal resolution monitoring program, one should record in evenly distributed durations at least as short as 1 min while only recording up to a third of the time one wishes to represent. While more continuous monitoring can be advantageous and necessary in many cases, current economic and logistical limitations in power, data storage, and analysis capabilities will often warrant optimized subsampling designs. [ABSTRACT FROM AUTHOR]

• Soundscapes can help to measure dimensions of ecological resilience. • Degree of soundscape alteration correlated with disturbance magnitude. • Degree of soundscape alteration corresponded with distance to shoreline. • Soundscapes became more variable after Hurricane Maria. • Maria impacted animal communities at dry forest sites more than at coral reefs sites. Disturbance regimes and biodiversity—two factors that govern the stability of ecosystems—are changing rapidly due to anthropogenic forces including climate change. Determining whether ecosystems retain their structure and function through intensifying disturbance regimes is an urgent task. However, quantitatively assessing the resilience of natural systems is a complex and challenging endeavor, especially for animal communities, for which datasets around disturbance events are scarce. Here, we apply an emerging remote sensing technology—the recording and analysis of soundscapes—to quantify the resilience of Puerto Rican coral reef and dry forest animal communities in relation to Hurricane Maria, which struck the island in September 2017. Using recordings collected between March 2017 and January 2018 at three terrestrial and three marine sites, we measured three dimensions of resilience—the magnitude of the impacts (resistance), the spatial pattern of the impacts (heterogeneity), and the diversity and timeline of functional responses (recovery)—across eight sound types representing different broad taxonomic groups. While the coral reef communities exhibited high resistance to the storm, all sound types within the dry forest were significantly impacted, with two of the three insect choruses and bird vocalizations at dawn declining approximately 50% in the weeks following Hurricane Maria. The mid-frequency insect sound type returned to pre-storm levels after 56 days, while bird vocalizations returned after 67 days, though seasonal and lunar patterns underscored the importance of long-term data for accurately measuring trajectories of recovery. This study demonstrates that soundscape methodologies can help to quantify elusive dimensions of animal community resilience in order to better understand how biodiversity and ecosystem functioning will change under novel disturbance regimes. [ABSTRACT FROM AUTHOR]