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Abstract AimAlthough species richness globally is likely to be declining, patterns in diversity at the regional scale depend on species gains within new habitats and species losses from previously inhabited areas. Our understanding of the processes associated with gains or losses remains poor, including whether these events exhibit immediate or delayed responses to environmental change. LocationThe study focuses on nine temperate marine ecosystems in North America. Time periodThe study period varies by region, but overall encompasses observations from 1970 to 2014. Major taxa studiedWe identified regional gains and losses for 577 marine fish and invertebrate species. MethodsFrom a total of 166,213 sampling events from bottom trawls across North America that informed 17,997 independent observations of species gains and losses, we built generalized linear mixed effects models to test whether lagged temperature can explain instances of gains and losses of marine fishes and invertebrates in North American continental shelf habitats. ResultsWe found that gains were less likely in years with high seasonality, consistent with seasonal extremes as a strong constraint on species occurrence. Losses were also negatively associated with high seasonality, but the response was delayed by 3 years. Main conclusionsEnvironmental conditions play a role in species occupancy across diverse temperate marine ecosystems. Immediate gains paired with delayed losses can drive transient increases in species richness during times of environmental change. Identifying the dynamics behind regional species gains and losses is an important step towards prediction of biodiversity changes across ecosystems. 

Abstract Patterns of population connectivity shape ecological and evolutionary phenomena from population persistence to local adaptation and can inform conservation strategy. Connectivity patterns emerge from the interaction of individual behavior with a complex and heterogeneous environment. Despite ample observation that dispersal patterns vary through time, the extent to which variation in the physical environment can explain emergent connectivity variation is not clear. Empirical studies of its contribution promise to illuminate a potential source of variability that shapes the dynamics of natural populations. We leveraged simultaneous direct dispersal observations and oceanographic transport simulations of the clownfishAmphiprion clarkiiin the Camotes Sea, Philippines, to assess the contribution of oceanographic variability to emergent variation in connectivity. We found that time‐varying oceanographic simulations on both annual and monsoonal timescales partly explained the observed dispersal patterns, suggesting that temporal variation in oceanographic transport shapes connectivity variation on these timescales. However, interannual variation in observed mean dispersal distance was nearly 10 times the expected variation from biophysical simulations, revealing that additional biotic and abiotic factors contribute to interannual connectivity variation. Simulated dispersal kernels also predicted a smaller scale of dispersal than the observations, supporting the hypothesis that undocumented abiotic factors and behaviors such as swimming and navigation enhance the probability of successful dispersal away from, as opposed to retention near, natal sites. Our findings highlight the potential for coincident observations and biophysical simulations to test dispersal hypotheses and the influence of temporal variability on metapopulation persistence, local adaptation, and other population processes. 

Abstract Genetic diversity is a fundamental component of biodiversity. Examination of global patterns of genetic diversity can help highlight mechanisms underlying species diversity, though a recurring challenge has been that patterns may vary by molecular marker. Here, we compiled 6862 observations of genetic diversity from 492 species of marine fish and tested among hypotheses for diversity gradients: the founder effect hypothesis, the kinetic energy hypothesis, and the productivity‐diversity hypothesis. We fit generalized linear mixed effect models (GLMMs) and explored the extent to which various macroecological drivers (latitude, longitude, temperature (SST), and chlorophyll‐a concentration) explained variation in genetic diversity. We found that mitochondrial genetic diversity followed geographic gradients similar to those of species diversity, being highest near the Equator, particularly in the Coral Triangle, while nuclear genetic diversity did not follow clear geographic patterns. Despite these differences, all genetic diversity metrics were correlated with chlorophyll‐a concentration, while mitochondrial diversity was also positively associated with SST. Our results provide support for the kinetic energy hypothesis, which predicts that elevated mutation rates at higher temperatures increase mitochondrial but not necessarily nuclear diversity, and the productivity‐diversity hypothesis, which posits that resource‐rich regions support larger populations with greater genetic diversity. Overall, these findings reveal how environmental variables can influence mutation rates and genetic drift in the ocean, caution against using mitochondrial macrogenetic patterns as proxies for whole‐genome diversity, and aid in defining global gradients of genetic diversity. 

Abstract Society increasingly demands accurate predictions of complex ecosystem processes under novel conditions to address environmental challenges. However, obtaining the process‐level knowledge required to do so does not necessarily align with the burgeoning use in ecology of correlative model selection criteria, such as Akaike information criterion. These criteria select models based on their ability to reproduce outcomes, not on their ability to accurately represent causal effects. Causal understanding does not require matching outcomes, but rather involves identifying model forms and parameter values that accurately describe processes. We contend that researchers can arrive at incorrect conclusions about cause‐and‐effect relationships by relying on information criteria. We illustrate via a specific example that inference extending beyond prediction into causality can be seriously misled by information‐theoretic evidence. Finally, we identify a solution space to bridge the gap between the correlative inference provided by model selection criteria and a process‐based understanding of ecological systems. 

Abstract Understanding how community composition is reshaped by changing climate is important for interpreting and predicting patterns of community assembly through time or across space. Community composition often does not perfectly correspond to expectations from current environmental conditions, leading to community‐climate mismatches. Here, we combine data analysis and theory development to explore how species climate response curves affect the community response to climate change. We show that strong mismatches between community and climate can appear in the absence of demographic delays or limited species pools. Communities simulated using species response curves showed temporal changes of similar magnitude to those observed in natural communities of fishes and plankton, suggesting no overall delays in community change despite substantial unexplained variation from community assembly and other processes. Our approach can be considered as a null model that will be important to use when interpreting observed community responses to climate change and variability. 

Abstract Dispersal drives diverse processes from population persistence to community dynamics. However, the amount of temporal variation in dispersal and its consequences for metapopulation dynamics is largely unknown for organisms with environmentally driven dispersal (e.g., many marine larvae, arthropods and plant seeds). Here, we used genetic parentage analysis to detect larval dispersal events in a common coral reef fish,Amphiprion clarkii, along 30 km of coastline consisting of 19 reef patches in Ormoc Bay, Leyte, Philippines. We quantified variation in the dispersal kernel across seven years (2012–2018) and monsoon seasons with 71 parentage assignments from 791 recruits and 1,729 adults. Connectivity patterns differed significantly among years and seasons in the scale and shape but not in the direction of dispersal. This interannual variation in dispersal kernels introduced positive temporal covariance among dispersal routes that theory predicts is likely to reduce stochastic metapopulation growth rates below the growth rates expected from only a single or a time‐averaged connectivity estimate. The extent of variation in mean dispersal distance observed here among years is comparable in magnitude to the differences across reef fish species. Considering dispersal variation will be an important avenue for further metapopulation and metacommunity research across diverse taxa. 

Abstract Rapid evolution of advantageous traits following abrupt environmental change can help populations recover from demographic decline. However, for many introduced diseases affecting longer‐lived, slower reproducing hosts, mortality is likely to outpace the acquisition of adaptive de novo mutations. Adaptive alleles must therefore be selected from standing genetic variation, a process that leaves few detectable genomic signatures. Here, we present whole genome evidence for selection in bat populations that are recovering from white‐nose syndrome (WNS). We collected samples both during and after a WNS‐induced mass mortality event in two little brown bat populations that are beginning to show signs of recovery and found signatures of soft sweeps from standing genetic variation at multiple loci throughout the genome. We identified one locus putatively under selection in a gene associated with the immune system. Multiple loci putatively under selection were located within genes previously linked to host response to WNS as well as to changes in metabolism during hibernation. Results from two additional populations suggested that loci under selection may differ somewhat among populations. Through these findings, we suggest that WNS‐induced selection may contribute to genetic resistance in this slowly reproducing species threatened with extinction. 

Abstract Species around the world are shifting their ranges in response to climate change. To make robust predictions about climate‐related colonizations and extinctions, it is vital to understand the dynamics of range edges. This study is among the first to examine annual dynamics of cold and warm range edges, as most global change studies average observational data over space or over time. We analyzed annual range edge dynamics of marine fishes—both at the individual species level and pooled into cold‐ and warm‐edge assemblages—in a multi‐decade time‐series of trawl surveys conducted on the Northeast US Shelf during a period of rapid warming. We tested whether cold edges show stronger evidence of climate tracking than warm edges (due to non‐climate processes or time lags at the warm edge; thebiogeography hypothesisorextinction debt hypothesis), or whether they tracked temperature change equally (due to the influence of habitat suitability; theecophysiology hypothesis). In addition to exploring correlations with regional temperature change, we calculated species‐ and assemblage‐specific sea bottom and sea surface temperature isotherms and used them to predict range edge position. Cold edges shifted further and tracked sea surface and bottom temperature isotherms to a greater degree than warm edges. Mixed‐effects models revealed that for a one‐degree latitude shift in isotherm position, cold edges shifted 0.47 degrees of latitude, and warm edges shifted only 0.28 degrees. Our results suggest that cold range edges are tracking climate change better than warm range edges, invalidating the ecophysiology hypothesis. We also found that even among highly mobile marine ectotherms in a global warming hotspot, few species are fully keeping pace with climate. 

Abstract Fishing communities are increasingly required to adapt to environmentally driven changes in the availability of fish stocks. Here, we examined trends in the distribution and biomass of five commercial target species (dover sole, thornyheads, sablefish, lingcod, and petrale sole) on the US west coast to determine how their availability to fishing ports changed over 40 years. We show that the timing and magnitude of stock declines and recoveries are not experienced uniformly along the coast when they coincide with shifts in species distributions. For example, overall stock availability of sablefish was more stable in southern latitudes where a 40% regional decline in biomass was counterbalanced by a southward shift in distribution of >200 km since 2003. Greater vessel mobility and larger areal extent of fish habitat along the continental shelf buffered northerly ports from latitudinal changes in stock availability. Landings were not consistently related to stock availability, suggesting that social, economic, and regulatory factors likely constrain or facilitate the capacity for fishers to adapt to changes in fish availability. Coupled social–ecological analyses such as the one presented here are important for defining community vulnerability to current and future changes in the availability of important marine species. 

Recent research has revealed the diversity and biomass of life across ecosystems, but how that biomass is distributed across body sizes of all living things remains unclear. We compile the present-day global body size-biomass spectra for the terrestrial, marine, and subterranean realms. To achieve this compilation, we pair existing and updated biomass estimates with previously uncatalogued body size ranges across all free-living biological groups. These data show that many biological groups share similar ranges of body sizes, and no single group dominates size ranges where cumulative biomass is highest. We then propagate biomass and size uncertainties and provide statistical descriptions of body size-biomass spectra across and within major habitat realms. Power laws show exponentially decreasing abundance (exponent -0.9±0.02 S.D.,R²= 0.97) and nearly equal biomass (exponent 0.09±0.01,R²= 0.56) across log size bins, which resemble previous aquatic size spectra results but with greater organismal inclusivity and global coverage. In contrast, a bimodal Gaussian mixture model describes the biomass pattern better (R²= 0.86) and suggests small (~10⁻¹⁵g) and large (~10⁷g) organisms outweigh other sizes by one order magnitude (15 and 65 Gt versus ~1 Gt per log size). The results suggest that the global body size-biomass relationships is bimodal, but substantial one-to-two orders-of-magnitude uncertainty mean that additional data will be needed to clarify whether global-scale universal constraints or local forces shape these patterns.