North American Breeding Research Articles

North American avian species that migrate in flocks show greater long-term non-breeding range shift rates.

Many species are exhibiting range shifts associated with anthropogenic change. For migratory species, colonisation of new areas can require novel migratory programmes that facilitate navigation between independently-shifting seasonal ranges. Therefore, in some cases range-shifts may be limited by the capacity for novel migratory programmes to be transferred between generations, which can be genetically and socially mediated. Here we used 50years of North American Breeding Bird Survey and Audubon Christmas Bird Count data to test the prediction that breeding and/or non-breeding range-shifts are more prevalent among flocking migrants, which possess a capacity for rapid social transmission of novel migration routes. Across 122 North American bird species, social migration was a significant positive predictor for the magnitude of non-breeding centre of abundance (COA) shift within our study region (conterminous United States and Southern Canada). Across a subset of 81 species where age-structured flocking was determined, migrating in mixed-age flocks produced the greatest shifts and solo migrants the lowest. Flocking was not a significant predictor of breeding COA shifts, which were better explained by absolute population trends and migration distance. Our results suggest that social grouping may play an important role in facilitating non-breeding distributional responses to climate change in migratory species. We highlight the need to gain a better understanding of migratory programme inheritance, and how this influences spatiotemporal population dynamics under environmental change.

K-mer genome-wide association study for anthracnose and BCMV resistance in a Phaseolus vulgaris Andean Diversity Panel.

Access to broad genomic resources and closely linked marker-trait associations for common beans (Phaseolus vulgaris L.) can facilitate development of improved varieties with increased yield, improved market quality traits, and enhanced disease resistance. The emergence of virulent races of anthracnose (caused by Colletotrichum lindemuthianum) and bean common mosaic virus (BCMV) highlight the need for improved methods to identify and incorporate pan-genomic variation in breeding for disease resistance. We sequenced the P. vulgaris Andean Diversity Panel (ADP) and performed a genome-wide association study (GWAS) to identify associations for resistance to BCMV and eight races of anthracnose. Historical single nucleotide polymorphism (SNP)-chip and phenotypic data enabled a three-way comparison between SNP-chip, reference-based whole genome shotgun sequence (WGS)-SNP, and reference-free k-mer (short nucleotide subsequence) GWAS. Across all traits, there was excellent concordance between SNP-chip, WGS-SNP, and k-mer GWAS results-albeit at a much higher marker resolution for the WGS data sets. Significant k-mer haplotype variation revealed selection of the linked I-gene and Co-u traits in North American breeding lines and cultivars. Due to structural variation, only 9.1 to 47.3% of the significantly associated k-mers could be mapped to the reference genome. Thus, to determine the genetic context of cis-associated k-mers, we generated draft whole genome assemblies of four ADP accessions and identified an expanded local repertoire of disease resistance genes associated with resistance to anthracnose and BCMV. With access to variant data in the context of a pan-genome, high resolution mapping of agronomic traits for common bean is now feasible.

The Erosion of Seasonality in Avian Communities

ABSTRACTAimSeasonality governs species composition at a given place and time. However, the effects of climate and land‐use change can vary by season, altering species composition. These changes can lead to a loss of distinct seasonal community composition, representing a novel form of biotic homogenisation. We ask if breeding and winter bird communities are becoming more similar over time. If so, is homogenisation occurring more rapidly in winter than in the breeding season, and has the presence of individual species changed between seasons?LocationNortheastern United States.Time Period1989–2019.Major Taxa StudiedTwo hundred thirty‐eight bird species.MethodsWe use data from The National Audubon Society's Christmas Bird Count and the North American Breeding Bird Survey to test if winter and breeding bird communities have become more similar (homogenised). We evaluate this change using the Sørensen dissimilarity index, and its components of turnover (species replacement) and nestedness (a subset of a more species rich community) and describe the mechanism in which the seasonal winter and breeding bird communities are changing.ResultsWe found that winter and breeding bird communities are homogenising, driven by significant decrease in turnover and a marginal decrease nestedness. When viewing breeding and wintering communities separately, we observe different trends. Breeding communities are becoming more unique with decreasing turnover and nestedness. Winter communities are becoming more similar to each other, with decreasing turnover and nestedness. More breeding species are declining and species that are typically found in the winter and year‐round residents are the main contributors to the homogenisation between seasons.Main ConclusionsWe show for the first time homogenisation between winter and breeding bird communities over time across the northeastern United States. This insight into how individual species are faring between seasons, and how they impact community structure, can be used when implementing conservation measures for maintaining ecological functioning and integrity.

Informative priors can account for location uncertainty in stop-level analyses of the North American Breeding Bird Survey, allowing fine-scale ecological analyses

Abstract Ecological inferences are often based on the locations at which species are present, but many species records have substantial uncertainty in spatial metadata, limiting their utility for fine-scale analyses. This is especially prevalent in historical records such as museum specimens, and in some citizen-science data. For example, the North American Breeding Bird Survey (BBS) has 55+ years of bird data from regular transects (“routes”) across the continent but was not designed to capture the spatial component of point count events, limiting analyses of species-habitat relationships for which it would otherwise be well suited. We present a new methodology for quantifying location uncertainty in BBS records using digitized estimated stop locations, deriving the corresponding environmental covariate uncertainty distributions, and incorporating this information into hierarchical species distribution models using informative Bayesian priors. This approach allows for estimation of species–environment relationships in a way that fully accounts for underlying spatial uncertainty. We quantify stop-location uncertainty in BBS data across the central United States, model bird–land cover relationships in the upper Midwest, and validate our method by comparing posterior land cover estimates to known covariate values for a subset of Global Positioning System (GPS)-digitized stop locations. We provide code for implementing this method in R. Posterior land cover estimates (forest, grass/hay, and developed land cover), based on our informative priors, were highly correlated with known land cover values from GPS-digitized stop locations. Our approach thus makes it possible to responsibly leverage large historical and citizen-science databases, such as the BBS, for fine-scale ecological analyses.

Modeling embryo survival: Genetic and environmental influences on eye-up rate in a north American Atlantic salmon selective breeding program

Selective breeding programs improve target traits but can also unintentionally change genetically correlated traits in the selected strain. The U.S. Department of Agriculture–Agricultural Research Service National Cold Water Marine Aquaculture Center (NCWMAC) in Franklin, Maine maintains a North American Atlantic salmon selective breeding program focused on improving commercially important traits (e.g., carcass weight). However, the program has experienced a significant decline in the percent of eyed embryos over its 14 years of operation, leading to concerns that reproductive performance was being unintentionally changed by selection for the target traits. The aims of this study were to 1) model eye up success as a potentially heritable trait utilizing the recorded pedigree and 2) assess the relationship between eye-up rate and environmental conditions experienced by the broodstock. Over 14 years of data encompassing 1537 full-sib families produced by 1537 dams and 885 sires was analyzed. Counts of eyed embryos and carcass weight were analyzed with a linear multi-trait trait model that included maternal genetic effects and a spawn year effect to determine the strength of genetic and environmental influences on the eyed embryo rate. To investigate the environmental influences in more detail, we assessed the correlation between water quality parameters in the broodstock rearing system observed over the same 14-year time period and the estimated spawn year effects. There was small heritability of the direct genetic effect (0.059 ± 0.009) and the maternal genetic effect (0.039 ± 0.013). Comparatively, the proportion of phenotypic variance explained by the maternal environmental effect was moderate (0.165 ± 0.012). The genetic correlations between carcass weight and eye up rate were very small and had a large amount of uncertainty. The correlation between the direct genetic effects on eye-up and carcass weight was −0.0528 ± 0.1469 while the correlation between the maternal genetic effect on eye-up and the direct genetic effect on carcass weight was 0.2030 ± 0.1791. The correlation between maternal common environmental effects on the two traits was also low at 0.0676 ± −0.0804. The effect of spawn year was statistically significant (p < 0.01), and the values were negatively correlated with mean un-ionized ammonia (mg/L, −0.56, p = 0.04,), nitrate concentrations (mg/L r = −0.65, p = 0.01) and temperature (°C, r = −0.61, p = 0.02) experienced by the broodstock prior to spawning. Overall, the results suggest that the decrease in eyed embryos over time was not caused by inadvertent selection but instead due to increases in water temperature and/or nitrogenous waste concentrations in the broodstock rearing system. Further investigation of the mechanisms behind these apparent environmentally induced declines and potential mitigation measures to prevent decreases in eye-up rates are needed.

Two listeners detect slightly more birds than a single listener when interpreting acoustic recordings

ABSTRACT Acoustic recorders are increasingly important for monitoring bird populations and have potential to augment existing monitoring programs such as the North American Breeding Bird Survey (BBS). An advantage of acoustic recordings is that they can be reviewed multiple times by multiple experts, potentially yielding improved estimates of species abundance and community richness. Yet, few studies have examined how frequently successive listeners disagree on acoustic interpretations and how strongly estimates of species richness and abundance are altered when multiple experts review each recording. We assigned multiple expert listeners to interpret recordings at 690 BBS stops, and subsequently assigned second listeners to conduct a review of first listeners’ interpretations. We examined the extent to which listeners agreed with each other and quantified the effect of disagreements on resultant estimates of species occurrence, abundance, and stop-level richness. We also compared estimates from acoustic recordings to those obtained during simultaneous field surveys. Estimates were highly correlated for number of species per stop (r = 0.92) and detection probabilities of species (r = 0.97) based on first and second-listener data. Second listeners disagreed with ~9% of first listeners’ interpretations and added an average of ~15% additional species and 16% additional birds not reported by first listeners. Estimates based on acoustic recordings were also highly correlated with those obtained from field surveys, though listeners were unable to count flocks. A single expert reviewer can provide a reasonable approximation of the relative abundance and species composition of birds available for acoustic detection during BBSs. However, acoustic review by multiple listeners may still be important for species that are rare, difficult to identify, or of high conservation concern.

Integrating counts from rigorous surveys and participatory science to better understand spatiotemporal variation in population processes

Abstract Knowledge of variation in population processes (e.g. population growth) across broad spatiotemporal scales is fundamental to population ecology and critical for conservation decision‐making. Count data from rigorous surveys (e.g. surveys with probabilistic sampling design and distance sampling information) can inform population processes but are often limited in space and time. Participatory science data cover broader spatiotemporal extents but are prone to bias due to limited to no sampling design and lack of distance sampling information, hindering their capability of informing population processes. Here, we developed an integrated dynamic N‐mixture model that jointly analyses rigorous survey and participatory science data to inform population growth at broad spatiotemporal extents. The model contains a flexible scaling parameter that allows fixed and random effects to account for biases and errors in participatory science data. We conducted simulations to evaluate the inference performance of this model across a broad range of spatial and temporal overlap between rigorous survey and participatory science data. We also conducted a case study of Baird's Sparrow (Centronyx bairdii), a species of conservation concern, to illustrate the application of the integrated model with rigorous survey data from the Integrated Monitoring in Bird Conservation Regions programme and participatory science North American Breeding Bird Survey and eBird data. Simulations showed that the integrated model improved precision without biasing parameter estimates, in comparison with a model informed by rigorous survey data alone. The case study further demonstrated the utility of the integrated model for quantifying range‐wide, long‐term population processes and environmental drivers despite limited spatiotemporal extent of rigorous survey data. In particular, we found that population growth rate peaked under medium temperature, which were only apparent in the integrated model. The integrated model developed in this study is useful for understanding wildlife population processes at broad spatiotemporal scales with count data. The flexible structure of this model, in particular the scaling parameter, makes it highly adaptable to a broad range of ecological systems and survey procedures. These properties make this modelling approach highly relevant for both population ecology and conservation practice.

Ecological scales of effect vary across space and time

The spatial scale at which an environmental variable is summarized can have considerable impacts on ecological inference of species distribution and abundance. While several analytical approaches have emerged to determine biologically relevant spatial scales – the spatial scale that most strongly influences the ecological patterns observed – identifying key ecological drivers of scale of effect is still underway. Additionally, several predicted ecological drivers of scale of effect can vary across space and time, but little research on spatiotemporal patterns has occurred. Here, I assessed spatial and temporal variation in scales of effect across 32 North American bird species using 18 years of empirical data from the North American breeding bird survey. Scale estimation was then coupled with trait‐based analyses and hypotheses testing of underlying processes of spatial and temporal variation in scales of effect. All 32 species tested exhibited varied scales of effect across years (average annual scales of effect ranging from 0.2 to 4.97 km) and Bird Conservation Regions (BCR), with spatial variability being the most pronounced. Trait‐based analyses revealed a contrary relationship between hand‐wing index, body size, and scale of effect, though the strength of this relationship was contingent on migratory status. Temporal variation in scales of effect was best explained by changes in human development over time, indicating that avian space use can be explained by an increasing human footprint. Additionally, relative population size, consistent with theoretical predictions stemming from density‐dependent population dynamics, explained notable variation in spatial and temporal scales of effect. These findings contribute to the growing landscape ecology literature by providing empirical evidence for hypothesized drivers of scales of effect. By delineating species‐specific scales of effect and elucidating their ecological drivers, this study enhances our understanding of spatial and temporal scales in ecological processes, aiding conservation efforts in a rapidly changing world.

Functional diversity loss and taxonomic delays of European freshwater fish and North American breeding birds

Abstract Biodiversity is temporally dynamic, reflecting historical environmental conditions and influencing ecosystem stability. Colonisation and extinction dynamics frequently exhibit asynchronous patterns, resulting in net imbalances and thus to long‐lasting richness trends. If these trends are not functionally random, functional net imbalances between colonisations and extinctions (fNICE) are likely to emerge. Using community time series data of European freshwater fish and North American breeding birds, we investigated how fNICE differs from its taxonomic equivalent (tNICE), to provide a comprehensive picture of biodiversity dynamics. Our findings reveal that taxonomic and functional delays are a prevalent feature, challenging the assumption of an immediate response to environmental changes. Taxonomic delays manifest as extinction debts and colonisation credits, while functional delays indicate a shift in the balance between functional gains and losses over time. Moreover, we found that taxonomic and functional imbalances are not always directly correlated, although some specific patterns were found consistently for fish and birds. Early colonisations outpaced functional gains, indicating that although new species arrived earlier than the extinction of other species, the acquisition of new functional traits lagged. Although this may temporarily stabilise communities, as functional redundancy can mitigate loss of function via local extinctions, excessive redundancy can compromise biodiversity's capacity to respond to environmental variations, thereby undermining long‐term resilience. In conclusion, understanding the intricate temporal dynamics of biodiversity responses is paramount for effective conservation practices. While short‐term observations may suggest an equilibrium between diversity and the environmental conditions, our results underscore the importance of considering long‐term dynamics and the interplay between species traits and changing environments. The metrics tNICE and fNICE are valuable tools for quantifying these temporal dynamics and unravelling their consequences for ecosystem stability. Incorporating these insights into conservation strategies can aid in proactively preserving biodiversity and safeguarding the integrity of ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

Range and climate niche shifts in European and North American breedingbirds.

Species respond dynamically to climate change and exhibit time lags. Consequently, species may not occupy their full climatic niche during range shifting. Here, we assessed climate niche tracking during recent range shifts of European and UnitedStates (US) birds. Using data from two European bird atlases and from the North American Breeding Bird Survey betweenthe 1980s and 2010s, we analysed range overlap and climate niche overlap based on kernel density estimation. Phylogenetic multiple regression was used to assess the effect of species morphological, ecological and biogeographic traits on range and niche metrics. European birds shifted their ranges north and north-eastwards, US birds westwards. Range unfilling was lower than expected by null models, and niche expansion was more common than niche unfilling. Also, climate niche tracking was generally lower in US birds and poorly explained by species traits. Overall, our results suggest that dispersal limitations were minor in range shifting birds in Europe and theUSA while delayed extinctions from unfavourable areas seem more important. Regional differences could be related to differences in land use history and monitoring schemes. Comparative analyses of range and niche shifts provide a useful screening approach for identifying the importance of transient dynamics and time-lagged responses to climate change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Estimation and interpretation problems and solutions when using proportion covariates in linear regression models.

Proportion variables, also known as compositional data, are very common in ecology. Unfortunately, few scientists are aware of how compositional data, when used as covariates, can adversely impact statistical analysis. We describe here how proportion covariates result in multicollinearity and parameter identifiability problems. Using simulated data on bird species richness as a function of land use, we show how these problems manifest when fitting a wide range of models in R, both in a frequentist and Bayesian framework. In particular, we show that similar models can often generate substantially different parameter estimates, leading to very different conclusions. Dropping a covariate or the intercept from the model can solve the multicollinearity and parameter identifiability problems. Unfortunately, these solutions do not fix the inherent challenges associated with interpreting parameter estimates. To this end, we propose focusing the interpretation on the difference of slope parameters to avoid the inherent unidentifiability of individual parameters. We also propose conditional plots with two x-axes and marginal plots as visualization techniques that can help users better interpret their modeling results. We illustrate these problems and proposed solutions using empirical data from the North American Breeding Bird Survey. The practical and straightforward approaches suggested in this article will help the fitting of linear models and interpretation of its results when some of the covariates are proportions.

Incorporating weather in counts and trends of migrating Common Nighthawks.

Effective conservation planning for species of concern requires long-term monitoring data that can accurately estimate population trends. Supplemental or alternative methods for estimating population trends are necessary for species that are poorly sampled by traditional breeding bird survey methods. Counts of migrating birds are commonly used to assess raptor population trends and could be useful for additional taxa that migrate diurnally and are difficult to monitor during the breeding season. In North America, the Common Nighthawk (Chordeiles minor) is challenging to detect during comprehensive dawn surveys like the North American Breeding Bird Survey and is considered a species of conservation concern because of steep population declines across its range. We conducted standardized evening counts of migrating Common Nighthawks at a fixed survey location along western Lake Superior each autumn from 2008 to 2022. To document peak migration activity, counts spanned ~3 hours each evening from mid-August to early September for a mean of 19.4 ± 2.4 days. These count data were then used to assess the effects of weather on daily counts and high-count days and to calculate population trends over this 15-year period. We used generalized linear mixed effects models to determine the relationship between daily counts and high-count days (i.e., ≥1000 migrating nighthawks) and weather variables. Additionally, using our 15-year dataset, we calculated a geometric mean passage rate that accounted for annual differences in weather to estimate count trends. Annual counts averaged ~18,000 (min = 2514, max = 32,837) individuals and high-count days occurred 56 times throughout the course of the study. Model results indicated lighter, westerly winds and warmer temperatures were associated with higher daily counts and greater probability of a large migratory flight. Results from the trend analyses suggest stable or non-significantly increasing trends for Common Nighthawks during this monitoring period; however, the trend models explained a relatively low percentage of the variation in the counts. Results from a power analysis suggest that continued monitoring efforts and adjustments with weather covariates will be necessary to effectively use visible migration count data to estimate Common Nighthawk trends. Establishing annual monitoring programs that use standardized visual counts to document Common Nighthawk migration at key sites across North America may provide supplemental information useful for population trend estimates of this species. Therefore, we advocate for the use of visible migration counts to monitor Common Nighthawks in North America and emphasize the value of long-term monitoring efforts.

Mapping multiscale breeding bird species distributions across the United States and evaluating their conservation applications.

Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, community-level maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992 and 2019. We developed ensemble models for each species at three spatial resolutions-0.5, 2.5, and 5 km-across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at 5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km resolution. However, the species we could model represent only 28%-56% of species found in the conterminous US BBSs across resolutions owing to data limitations. We found that stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States and support community-level conservation when used in tandem with guild maps. However, there remain data scarcity issues for many species of conservation concern when using the BBS for single-species models.

Spatially explicit Bayesian hierarchical models improve estimates of avian population status and trends

Abstract Population trend estimates form the core of avian conservation assessments in North America and indicate important changes in the state of the natural world. The models used to estimate these trends would be more efficient and informative for conservation if they explicitly considered the spatial locations of the monitoring data. We created spatially explicit versions of some standard status and trend models applied to long-term monitoring data for birds across North America. We compared the spatial models to simpler non-spatial versions of the same models, fitting them to simulated data and real data from 3 broad-scale monitoring programs: the North American Breeding Bird Survey (BBS), the Christmas Bird Count, and a collection of programs we refer to as Migrating Shorebird Surveys. All the models generally reproduced the simulated trends and population trajectories when there were many data, and the spatial models performed better when there were fewer data and in locations where the local trends differed from the range-wide means. When fit to real data, the spatial models revealed interesting spatial patterns in trend, such as recent population increases along the Appalachian Mountains for the Eastern Whip-poor-will (Antrostomus vociferus), that were much less apparent in results from the non-spatial versions. The spatial models also had higher out-of-sample predictive accuracy than the non-spatial models for a selection of species using BBS data. The spatially explicit sharing of information allows fitting the models with much smaller strata, allowing for finer-grained patterns in trends. Spatially informed trends will facilitate more locally relevant conservation, highlight areas of conservation successes and challenges, and help generate and test hypotheses about the spatially dependent drivers of population change.

Mixed population trends inside a California protected area: Evidence from long‐term community science monitoring

Protected areas are one of the most widespread and accepted conservation interventions, yet population trends of species within protected areas are rarely compared with regional trends to gain insight into their effectiveness. Here, we leverage two long‐term community science datasets, finding mixed effects of protected areas on long‐term bird population trends. We analysed 31 years of bird transect data recorded by community volunteers across all major habitats of Stanford University's Jasper Ridge Biological Preserve to determine the population trends for a sample of 66 species. We found that nearly a third of species experienced long‐term declines, and on average, species declined by 12%. Further, we averaged species trends by conservation status and key life history attributes to identify correlates and possible drivers of these trends. Observed increases in some cavity‐nesters and declines of scrub‐associated species suggest that long‐term fire suppression may be a key driver, reshaping bird communities through changes in forest and chaparral structure and composition. Additionally, we compared our results with those of the North American Breeding Bird Survey's Central California Coast region (n = 55 species) to place Jasper Ridge in a broader context. Most species experienced similar directional population trends inside and outside of the preserve and only eight species (14.5%) did better inside this small protected area. Therefore, we must identify relevant management strategies for declining populations and explicitly consider how existing protected areas target and manage each species. Further, this analysis underlines the importance of local and national community science for revealing long‐term bird population trends.

Temporal changes in the individual size distribution modulate the long‐term trends of biomass and energy use of North American breeding bird communities

AbstractAimThe frequency of different body sizes in an ecological community (the individual size distribution, or ISD) is a key link between the number of individual organisms present in a community and community function—total biomass or total energy use. If the ISD changes over time, the dynamics of community function may become decoupled from trends in abundance. Understanding how, and how often, the ISD modulates the relationship between abundance, biomass and energy use is of critical importance to understand biodiversity trends in the Anthropocene. Here, we conduct the first macroecological‐scale analysis of this type for avian communities.LocationNorth America, north of Mexico.Time Period1989–2018.Major Taxa StudiedBreeding birds.MethodsWe used species' traits to generate annual ISDs for bird communities in the North American Breeding Bird Survey. We compared the long‐term trends in total biomass and energy use to the trends generated from a null model of an unchanging ISD.ResultsTrends in biomass have been evenly split between increases and decreases, but the trends predicted by the null model were dominated by decreases. A substantial number of communities have undergone a shift in the ISD favouring larger bodied species, resulting in a less negative trend in biomass than would be expected had the ISD remained static. Trends in energy use more closely paralleled the null model.Main ConclusionsTaking changes in the ISD into account qualitatively changes the continental‐scale picture of how biomass and energy use have changed over the past 30 years. For North American breeding birds, shifts in species composition favouring larger bodied species may have partially offset declines in standing biomass driven by losses of individuals over the past 30 years.

Substituting space for time: Bird responses to forest loss in space provide a general picture of responses over time.

The practice of space-for-time substitution assumes that the responses of species or communities to land-use change over space represents how they will respond to that same change over time. Space-for-time substitution is commonly used in both ecology and conservation, but whether the assumption produces reliable insights remains inconclusive. Here, we tested space-for-time substitution using data from the North American Breeding Bird Survey (BBS) and Global Forest Change (GFC) to compare the effects of landscape-scale forest cover on bird richness and abundance over time and space, for 25 space-time comparisons. Each comparison consisted of a landscape that experienced at least 20% forest loss over 19 years (temporal site) and a set of 15-19 landscapes (spatial sites) that represented the same forest cover gradient over space in 2019 as experienced over time in their corresponding temporal site. Across the 25 comparisons, the observed responses of forest and open-habitat birds to forest cover over time generally aligned with their responses to forest cover over space, but with comparatively higher variability in the magnitude and direction of effect across the 25 temporal slopes than across the 25 spatial slopes. On average, the mean differences between the spatial and temporal slopes across the 25 space-time comparisons frequently overlapped with zero, suggesting that the spatial slopes are generally informative of the temporal slopes. However, we observed high variability around these mean differences, indicating that a single spatial slope is not strongly predictive of its corresponding temporal slope. We suggest that our results may be explained by annual variability in other relevant environmental factors that combine to produce complex effects on population abundances over time that are not easily captured by snapshots in space. While not being a 1:1 proxy, measuring bird responses to changes in habitat amount in space provides an idea on how birds might be expected to eventually equilibrate to similar changes in habitat amount over time. Further, analyses such as this could be potentially used to screen for cases of regional space-time mismatches where population-limiting factors other than habitat could be playing a more important role in the population trends observed there.

Challenging the geographic bias in recognising large‐scale patterns of diversity change

AbstractAimGeographic structure is a fundamental organising principle in ecological and Earth sciences, and our planet is conceptually divided into distinct geographic clusters (e.g. ecoregions and biomes) demarcating unique diversity patterns. Given recent advances in technology and data availability, however, we ask whether geographically clustering diversity time‐series should be the default framework to identify meaningful patterns of diversity change.LocationNorth America.TaxonAves.MethodsWe first propose a framework that recognises patterns of diversity change based on similarities in the behaviour of diversity time‐series, independent of their specific or relative spatial locations. Specifically, we applied an artificial neural network approach, the self‐organising map (SOM), to group time‐series of over 0.9 million observations from the North American Breeding Birds Survey (BBS) data from 1973 to 2016. We then test whether time‐series identified as having similar behaviour are geographically structured.ResultsWe find little evidence of strong geographic structure in patterns of diversity change for North American breeding birds. The majority of the recognised diversity time‐series patterns tend to be indistinguishable from being independently distributed in space.Main ConclusionsOur results suggest that geographic proximity may not correspond to shared temporal trends in diversity; assuming that geographic clustering is the basis for analysis may bias diversity trend estimation. We suggest that approaches that consider variability independently of geographic structure can serve as a useful addition to existing organising rules of biodiversity time‐series.

Trending against the grain: Bird population responses to expanding energy portfolios in the US Northern Great Plains.

Future global energy demand may be met through increased extraction of fossil fuels and production of renewable energy such as biofuels. Renewable energy from biofuels is often proposed as an environmentally friendly alternative to fossil fuels; however, impacts of renewable energy sources on wildlife populations have rarely been evaluated in working landscapes. We used North American Breeding Bird Survey data (1998 to 2021) to assess whether the joint effects of oil and gas and biofuel crop production explained grassland bird population declines. We modeled location-specific effects of land use on grassland bird habitat use for four grassland bird species (bobolink [Dolichonyx oryzivorus], grasshopper sparrow [Ammodramus savannarum], Savannah sparrow [Passerculus sandwichensis], and western meadowlark [Sturnella neglecta]) in North Dakota, a state experiencing rapid growth in both energy sectors. Our analysis showed that grassland birds responded more negatively to biofuel feedstocks (i.e., corn and soybeans) on the landscape compared with oil and gas development. Furthermore, we found that the effect of feedstocks was not generalizable to other forms of agricultural land use. When combined, these land use changes resulted in distributional shifts of grassland birds, with use by birds being lower in regions dominated by biofuel production, which appears partially responsible for observed abundance trends at the state level. Our results indicate that expansion of oil and gas development has negatively affected habitat use by some grassland birds, but this impact was more localized when compared to biofuel crops. Conservation practitioners may need to adapt their conservation strategies to account for widespread and rapid land use change driven by United States energy policies.

The observation of birds from a citizen science leisure project to systematic research

This article analyses historical data from observations made of birds in breeding season, throughout two routes with urban characteristics. The data were collected during a consecutive period of 10 years (2009-2018), following a precise methodology designed by the North American Breeding Bird Survey. The analyzed routes are officially registered in the Mexican Commission for Biodiversity’s Knowledge and Use, the United States Geological Survey Patuxent Wildlife Research Center, and the Canadian Wildlife Service Research Centre. The observations were made by citizens without formal professional education; hence the results may be considered within the framework of citizen science. Their contributions provided important data for decision-making regarding environmental issues, since the presence of birds is considered one of the main indicators of the health conditions of an ecosystem. Data analysis identified two basic conditions: (i) a reduction of the 23% in the number of species found, many of which disappeared during counting; and (ii) the significant increase in population of other species, including three species of pigeons. Apart from the study of variations in the numbers of bird species present in the routes with urban characteristics, the article acknowledges the lack of connection and use of this citizen science for decision-making and education regarding environmental issues. Therefore, we consider it crucial to create scientific observations that are available to both experts in the field and to the general population, which is the essence of citizen science.