Temporal change in urban fish biodiversity-Gains, losses, and drivers of change.

Our aim was to examine temporal change in alpha and beta diversity of freshwater fish communities in rivers that have urbanized over the same period to understand the influence of changes in land use and river connectivity on community change. We used biological (2001-2018), land use (2000-2015), and connectivity data (1987-2017) from Toronto, Ontario, Canada. We used linear mixed effects models to determine the strength of upstream land use, connectivity, and their changes over time to explain temporal change in alpha and beta diversity indices. We examined beta diversity using the temporal beta diversity index (TBI) to assess site-specific community change. The TBI was partitioned into gains and losses, and species-specific changes in abundance were assessed using paired t-tests. There were more gains than losses across the study sites as measured by TBI. We found little to no significant differences in species-specific abundances at aggregated spatial scales (study region, watershed, stream order). We found different relationships between landscape and connectivity variables with the biodiversity indices tested; however, almost all estimated confidence intervals overlapped with zero and had low goodness-of-fit. More fish biodiversity gains than losses were found across the study region, as measured by TBI. We found TBI to be a useful indicator of change as it identifies key sites to further investigate. We found two high value TBI sites gained non-native species, and one site shifted from a cool-water to warm-water species dominated community, both of which have management implications. Upstream catchment land use and connectivity had poor explanatory power for change in the measured biodiversity indices. Ultimately, such spatial-temporal datasets are invaluable and can reveal trends in biodiversity useful for environmental management when considering competing interests involved with urban sprawl in the ongoing "Decade on Restoration."

Movement of an imperiled esocid fish in an agricultural drain.

Animal movement is increasingly affected by human alterations to habitat and climate change. In wetland systems, widespread hydrologic alterations from agriculture have changed the shape, function, and stability of shallow streams and wetland habitats. These changes in habitat quality and quantity may be especially consequential for freshwater fishes such as Grass Pickerel (Esox americanus vermiculatus), a small predatory fish found in disjunct populations across southern Ontario and listed as Special Concern under Canada's Species at Risk Act. To characterize Grass Pickerel movement response to stream-channel alterations, Fisheries and Oceans Canada implemented a tracking study to monitor the movements of a Grass Pickerel population in an agricultural drain on the Niagara Peninsula (Ontario, Canada). From 2009 to 2013, 2007 Grass Pickerel were tagged and tracked in the 37.3 km2 Beaver Creek watershed using a combination of mark-recapture surveys and eight fully automated passive integrated transponder tag antennas. Most individuals moved within 500 m (i.e., stationary fish) while 16% of the fish moved > 500 m (i.e., mobile fish), with a maximum median movement distance of 1.89 km and a maximum movement distance of 13.5 km (a long-tail distribution). Most movements occurred near the largest confluence where only a few were long-distance upstream or downstream movements. Mobile fish were larger than their stationary counterparts. Grass Pickerel in sites with higher abundance had more mobile fish, implying potential density dependence. Our results highlight that, while a long-distance dispersal ability exists in extant Grass Pickerel populations, the current conditions of riverscapes may prevent these dispersals from occurring. For declining Grass Pickerel populations, limitations to their movement ecology may substantially increase the likelihood of local extirpations.

Rapid monitoring of ecological persistence.

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of an ecological community is supported by its underlying network of species interactions. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, only small subsets of these networks can be monitored. There is therefore an urgent need to establish links between the small snapshots of data conservationists can collect, and the "big picture" conclusions about ecosystem health demanded by policymakers, scientists, and societies. Here, we show that the persistence of small subnetworks (motifs) in isolation-that is, their persistence when considered separately from the larger network of which they are a part-is a reliable probabilistic indicator of the persistence of the network as a whole. Our methods show that it is easier to detect if an ecological community is not persistent than if it is persistent, allowing for rapid detection of extinction risk in endangered systems. Our results also justify the common practice of predicting ecological persistence from incomplete surveys by simulating the population dynamics of sampled subnetworks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.

Shortcomings of reusing species interaction networks created by different sets of researchers.

Given the requisite cost associated with observing species interactions, ecologists often reuse species interaction networks created by different sets of researchers to test their hypotheses regarding how ecological processes drive network topology. Yet, topological properties identified across these networks may not be sufficiently attributable to ecological processes alone as often assumed. Instead, much of the totality of topological differences between networks-topological heterogeneity-could be due to variations in research designs and approaches that different researchers use to create each species interaction network. To evaluate the degree to which this topological heterogeneity is present in available ecological networks, we first compared the amount of topological heterogeneity across 723 species interaction networks created by different sets of researchers with the amount quantified from non-ecological networks known to be constructed following more consistent approaches. Then, to further test whether the topological heterogeneity was due to differences in study designs, and not only to inherent variation within ecological networks, we compared the amount of topological heterogeneity between species interaction networks created by the same sets of researchers (i.e., networks from the same publication) with the amount quantified between networks that were each from a unique publication source. We found that species interaction networks are highly topologically heterogeneous: while species interaction networks from the same publication are much more topologically similar to each other than interaction networks that are from a unique publication, they still show at least twice as much heterogeneity as any category of non-ecological networks that we tested. Altogether, our findings suggest that extra care is necessary to effectively analyze species interaction networks created by different researchers, perhaps by controlling for the publication source of each network.

Evaluating the evolutionary mechanisms maintaining alternative mating strategies in a simulated bull trout (Salvelinus confluentus) population.

The coexistence of distinct alternative mating strategies (AMS) is often explained by mechanisms involving trade-offs between reproductive traits and lifetime fitness; yet their relative importance remains poorly understood. Here, we used an established individual-based, spatially explicit model to simulate bull trout (Salvelinus confluentus) in the Skagit River (Washington, USA) and investigated the influence of female mating preference, sneaker-specific mortality, and variation in age-at-maturity on AMS persistence using global sensitivity analyses and boosted regression trees. We assumed that two genetically fixed AMS coexisted within the population: sneaker males (characterized by younger age-at-maturity, greater AMS-specific mortality, and lower reproductive fitness) and territorial males. After 300 years, variation in relative sneaker success in the system was explained by sneaker males' reproductive fitness (72%) and, to a lesser extent, the length of their reproductive lifespan (21%) and their proportion in the initial population (8%). However, under a wide range of parameter values, our simulated scenarios predicted the extinction of territorial males or their persistence in small, declining populations. Although these results do not resolve the coexistence of AMS in salmonids, they reinforce the importance of mechanisms reducing sneaker's lifetime reproductive success in favoring AMS coexistence within salmonid populations but also limit the prediction that, without any other selective mechanisms at play, strong female preference for mating with territorial males and differences in reproductive lifespan allow the stable coexistence of distinct AMS.

Scale of population synchrony confirms macroecological estimates of minimum viable range size.

Global ecosystems are facing a deepening biodiversity crisis, necessitating robust approaches to quantifying species extinction risk. The lower limit of the macroecological relationship between species range and body size has long been hypothesized as an estimate of the relationship between the minimum viable range size (MVRS) needed for species persistence and the organismal traits that affect space and resource requirements. Here, we perform the first explicit test of this assumption by confronting the MVRS predicted by the range-body size relationship with an independent estimate based on the scale of synchrony in abundance among spatially separated populations of riverine fish. We provide clear evidence of a positive relationship between the scale of synchrony and species body size, and strong support for the MVRS set by the lower limit of the range-body size macroecological relationship. This MVRS may help prioritize first evaluations for unassessed or data-deficient taxa in global conservation assessments.

Metapopulation persistence can be inferred from incomplete surveys.

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

Generalism drives abundance: A computational causal discovery approach.

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

How network size strongly determines trophic specialisation: A technical comment on Luna et al. (2022).

Luna et al. (2022) concluded that the environment contributes to explaining specialisation in open plant-pollinator networks. When reproducing their study, we instead found that network size alone largely explained the variation in their specialisation metrics. Thus, we question whether empirical network specialisation is driven by the environment.

Managing for the unexpected: Building resilient forest landscapes to cope with global change.

Natural disturbances exacerbated by novel climate regimes are increasing worldwide, threatening the ability of forest ecosystems to mitigate global warming through carbon sequestration and to provide other key ecosystem services. One way to cope with unknown disturbance events is to promote the ecological resilience of the forest by increasing both functional trait and structural diversity and by fostering functional connectivity of the landscape to ensure a rapid and efficient self-reorganization of the system. We investigated how expected and unexpected variations in climate and biotic disturbances affect ecological resilience and carbon storage in a forested region in southeastern Canada. Using a process-based forest landscape model (LANDIS-II), we simulated ecosystem responses to climate change and insect outbreaks under different forest policy scenarios-including a novel approach based on functional diversification and network analysis-and tested how the potentially most damaging insect pests interact with changes in forest composition and structure due to changing climate and management. We found that climate warming, lengthening the vegetation season, will increase forest productivity and carbon storage, but unexpected impacts of drought and insect outbreaks will drastically reduce such variables. Generalist, non-native insects feeding on hardwood are the most damaging biotic agents for our region, and their monitoring and early detection should be a priority for forest authorities. Higher forest diversity driven by climate-smart management and fostered by climate change that promotes warm-adapted species, might increase disturbance severity. However, alternative forest policy scenarios led to a higher functional and structural diversity as well as functional connectivity-and thus to higher ecological resilience-than conventional management. Our results demonstrate that adopting a landscape-scale perspective by planning interventions strategically in space and adopting a functional trait approach to diversify forests is promising for enhancing ecological resilience under unexpected global change stressors.

Assessing the current water clarity status of ~100,000 lakes across southern Canada: A remote sensing approach.

Canada has more lakes than any other country, making comprehensive monitoring a huge challenge. As more and more satellite data become readily available, and as faster data processing systems make massive satellite data operations possible, new opportunities exist to use remote sensing to develop comprehensive assessments of water quality at very large spatial scales. In this study, we use a published empirical algorithm to estimate Secchi depth from Landsat 8 reflectance data in order to estimate water clarity in lakes across southern Canada. Combined with ancillary information on lake morphological, hydrological, and watershed geological and landuse characteristics, we were able to assess broad spatial patterns in water clarity for the first time. Ecological zones, underlying geological substrate, and lake depth had particularly strong influences on clarity across the whole country. Lakes in western mountain ecozones had significantly clearer waters than those in the prairies and plains, while lakes in sedimentary rock formations tended to have lower clarity than lakes in intrusive rock. Deep lakes were significantly clearer than shallow lakes over most of the country. Water clarity was also significantly influenced by human impact (urbanization, agriculture, and industry) in the watershed, with most lakes in high impact areas having low clarity or very low clarity. Finally, we used in situ measured data to help interpret the underlying optical water column constituents influencing clarity across Canada, and found that chlorophyll-a, total suspended solids, and color dissolved organic matter all had strong but varying underlying effects on water clarity across different ecozones. This research provides an important step towards further research on the relationship between water column optical properties and the health and vulnerability status of lakes across the country.

Ecological network complexity scales with area.

Larger geographical areas contain more species-an observation raised to a law in ecology. Less explored is whether biodiversity changes are accompanied by a modification of interaction networks. We use data from 32 spatial interaction networks from different ecosystems to analyse how network structure changes with area. We find that basic community structure descriptors (number of species, links and links per species) increase with area following a power law. Yet, the distribution of links per species varies little with area, indicating that the fundamental organization of interactions within networks is conserved. Our null model analyses suggest that the spatial scaling of network structure is determined by factors beyond species richness and the number of links. We demonstrate that biodiversity-area relationships can be extended from species counts to higher levels of network complexity. Therefore, the consequences of anthropogenic habitat destruction may extend from species loss to wider simplification of natural communities.

Conceptualizing ecosystem services using social-ecological networks.

Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.

Fine-scale spatial segregation in a pelagic seabird driven by differential use of tidewater glacier fronts.

In colonially breeding marine predators, individual movements and colonial segregation are influenced by seascape characteristics. Tidewater glacier fronts are important features of the Arctic seascape and are often described as foraging hotspots. Albeit their documented importance for wildlife, little is known about their structuring effect on Arctic predator movements and space use. In this study, we tested the hypothesis that tidewater glacier fronts can influence marine bird foraging patterns and drive spatial segregation among adjacent colonies. We analysed movements of black-legged kittiwakes (Rissa tridactyla) in a glacial fjord by tracking breeding individuals from five colonies. Although breeding kittiwakes were observed to travel up to ca. 280 km from the colony, individuals were more likely to use glacier fronts located closer to their colony and rarely used glacier fronts located farther away than 18 km. Such variation in the use of glacier fronts created fine-scale spatial segregation among the four closest (ca. 7 km distance on average) kittiwake colonies. Overall, our results support the hypothesis that spatially predictable foraging patches like glacier fronts can have strong structuring effects on predator movements and can modulate the magnitude of intercolonial spatial segregation in central-place foragers.

Network ecology in dynamic landscapes.

Network ecology is an emerging field that allows researchers to conceptualize and analyse ecological networks and their dynamics. Here, we focus on the dynamics of ecological networks in response to environmental changes. Specifically, we formalize how network topologies constrain the dynamics of ecological systems into a unifying framework in network ecology that we refer to as the 'ecological network dynamics framework'. This framework stresses that the interplay between species interaction networks and the spatial layout of habitat patches is key to identifying which network properties (number and weights of nodes and links) and trade-offs among them are needed to maintain species interactions in dynamic landscapes. We conclude that to be functional, ecological networks should be scaled according to species dispersal abilities in response to landscape heterogeneity. Determining how such effective ecological networks change through space and time can help reveal their complex dynamics in a changing world.

The geography of metapopulation synchrony in dendritic river networks.

Dendritic habitats, such as river ecosystems, promote the persistence of species by favouring spatial asynchronous dynamics among branches. Yet, our understanding of how network topology influences metapopulation synchrony in these ecosystems remains limited. Here, we introduce the concept of fluvial synchrogram to formulate and test expectations regarding the geography of metapopulation synchrony across watersheds. By combining theoretical simulations and an extensive fish population time-series dataset across Europe, we provide evidence that fish metapopulations can be buffered against synchronous dynamics as a direct consequence of network connectivity and branching complexity. Synchrony was higher between populations connected by direct water flow and decayed faster with distance over the Euclidean than the watercourse dimension. Likewise, synchrony decayed faster with distance in headwater than mainstem populations of the same basin. As network topology and flow directionality generate fundamental spatial patterns of synchrony in fish metapopulations, empirical synchrograms can aid knowledge advancement and inform conservation strategies in complex habitats.

Incorporating putatively neutral and adaptive genomic data into marine conservation planning.

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype-environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.

Incorporación de Datos Genómicos Putativamente Neutros y Adaptativos dentro de la Planeación de la Conservación Marina Resumen La disponibilidad de los datos genómicos para un número creciente de especies posibilita la incorporación de los procesos evolutivos dentro de los planes de conservación. Los estudios recientes muestran cómo los datos genéticos pueden informar a la priorización de la conservación espacial (PCE) pero tienden a enfocarse más en las medidas de la diversidad y la distinción derivadas principalmente de los conjuntos de datos genéticos neutrales. La identificación de los marcadores genéticos adaptativos puede proporcionar información importante con respecto a la capacidad de las poblaciones para adaptarse al cambio ambiental. Aun así, no se ha explorado el efecto de la inclusión de las medidas basadas en los datos genéticos adaptativos dentro de la PCE y cómo se comparan con las medidas genéticas neutrales de uso más amplio. Usamos datos genómicos existentes sobre una especie de explotación comercial, el pepino de mar gigante de California (Parastichopus californicus), para realizar la PCE para la región costera de la Columbia Británica (BC) en Canadá. Usamos un conjunto de datos RAD-seq para 717 individuos de la especie P. californicus en 24 localidades de muestreo para identificar los polimorfismos de un solo nucleótido (PSNs) putativamente adaptativos (es decir, candidatos) con base en las asociaciones genotipo-ambiente manifestadas con la temperatura del fondo marino. Calculamos varias medidas para los PSNs neutrales y los PSNs candidatos y comparamos los resultados de la PCE con medidas independientes y con combinaciones de medidas. Las áreas prioritarias variaron dependiendo de si se usaron los SNP neutrales o los candidatos y de la medida específica que se utilizó. Por ejemplo, enfocarse en sitios con una frecuencia alta de alelos asociados con agua cálida para fortalecer la persistencia frente al futuro calentamiento prioriza las áreas en la región del sur de la costa. Al contrario, enfocarse en sitios con una alta heterocigosidad esperada en los loci de los candidatos para fortalecer la persistencia frente a la incertidumbre ambiental prioriza las áreas en la parte norte de la costa. Cuando combinamos las medidas, todos los escenarios generaron soluciones intermedias, protegiendo así los sitios que abarcan gradientes latitudinales y gradientes térmicos. Nuestros resultados demuestran que la distinción entre los marcadores neutrales y los adaptativos puede afectar las soluciones de conservación y también enfatizan la importancia de la definición de los objetivos cuando se elige entre varias medidas genómicas para la PCE.

Network analysis can guide resilience-based management in forest landscapes under global change.

Forests are projected to undergo dramatic compositional and structural shifts prompted by global changes, such as climatic changes and intensifying natural disturbance regimes. Future uncertainty makes planning for forest management exceptionally difficult, demanding novel approaches to maintain or improve the ability of forest ecosystems to respond and rapidly reorganize after disturbance events. Adopting a landscape perspective in forest management is particularly important in fragmented forest landscapes where both diversity and connectivity play key roles in determining resilience to global change. In this context, network analysis and functional traits combined with ecological dynamic modeling can help evaluate changes in functional response diversity and connectivity within and among forest stands in fragmented landscapes. Here, we coupled ecological dynamic modeling with functional traits analysis and network theory to analyze forested landscapes as an interconnected network of forest patches. We simulated future forest landscape dynamics in a large landscape in southern Quebec, Canada, under a combination of climate, disturbance, and management scenarios. We depicted the landscape as a functional network, assessed changes in future resilience using indicators at multiple spatial scales, and evaluated if current management practices are suitable for maintaining resilience to simulated changes in regimes. Our results show that climate change would promote forest productivity and favor heat-adapted deciduous species. Changes in natural disturbances will likely have negative impacts on native conifers and will drive changes in forest type composition. Climate change negatively impacted all resilience indicators and triggered losses of functional response diversity and connectivity across the landscape with undesirable consequences on the capacity of these forests to adapt to global change. Also, current management strategies failed to promote resilience at different spatial levels, highlighting the need for a more active and thoughtful approach to forest management under global change. Our study demonstrates the usefulness of combining dynamic landscape-scale simulation modeling with network analyses to evaluate the possible impacts of climate change as well as human and natural disturbances on forest resilience under global change.

Fire and biodiversity in the Anthropocene.

Fire has been a source of global biodiversity for millions of years. However, interactions with anthropogenic drivers such as climate change, land use, and invasive species are changing the nature of fire activity and its impacts. We review how such changes are threatening species with extinction and transforming terrestrial ecosystems. Conservation of Earth's biological diversity will be achieved only by recognizing and responding to the critical role of fire. In the Anthropocene, this requires that conservation planning explicitly includes the combined effects of human activities and fire regimes. Improved forecasts for biodiversity must also integrate the connections among people, fire, and ecosystems. Such integration provides an opportunity for new actions that could revolutionize how society sustains biodiversity in a time of changing fire activity.

Ecological Dynamics: Integrating Empirical, Statistical, and Analytical Methods.

Understanding ecological processes and predicting long-term dynamics are ongoing challenges in ecology. To address these challenges, we suggest an approach combining mathematical analyses and Bayesian hierarchical statistical modeling with diverse data sources. Novel mathematical analysis of ecological dynamics permits a process-based understanding of conditions under which systems approach equilibrium, experience large oscillations, or persist in transient states. This understanding is improved by combining ecological models with empirical observations from a variety of sources. Bayesian hierarchical models explicitly couple process-based models and data, yielding probabilistic quantification of model parameters, system characteristics, and associated uncertainties. We outline relevant tools from dynamical analysis and hierarchical modeling and argue for their integration, demonstrating the value of this synthetic approach through a simple predator-prey example.