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At least 1,369 records · Page 76Linked to original sources

Attack of the PCR clones: Rates of clonality have little effect on RAD-seq genotype calls

Interpretation of high-throughput sequence data requires an understanding of how decisions made during bioinformatic data processing can influence results. One source of bias that is often cited is PCR clones (or PCR duplicates). PCR clones are common in restriction site-associated sequencing (RAD-seq) data sets, which are increasingly being used for molecular ecology. To determine the influence PCR clones and the bioinformatic handling of clones have on genotyping, we evaluate four RAD-seq data sets. Data sets were compared before and after clones were removed to estimate the number of clones present in RAD-seq data, quantify how often the presence of clones in a data set causes genotype calls to change compared to when clones were removed, investigate the mechanisms that lead to genotype call changes and test whether clones bias heterozygosity estimates. Our RAD-seq data sets contained 30%–60% PCR clones, but 95% of RAD-tags had five or fewer clones. Relatively few genotypes changed once clones were removed (5%–10%), and the vast majority of these changes (98%) were associated with genotypes switching from a called to no-call state or vice versa. PCR clones had a larger influence on genotype calls in individuals with low read depth but appeared to influence genotype calls at all loci similarly. Removal of PCR clones reduced the number of called genotypes by 2% but had almost no influence on estimates of heterozygosity. As such, while steps should be taken to limit PCR clones during library preparation, PCR clones are likely not a substantial source of bias for most RAD-seq studies.

Molecular Ecology Resources↗

Influence of hydrology on life-history parameters of common freshwater fishes from southern Florida

Fishes are essential to the successful functioning of wetland food webs in southern Florida through their roles as prey and predators. Any changes that reduce the population sizes, community composition, or availability of aquatic animals will affect all facets of the ecology of these wetlands. In particular, small and medium-size fishes are important food items for most wading bird species. For this reason, fishes have been recognized by the multi-agency groups responsible for guiding the Everglades restoration process as a key indicator group by which to measure restoration success. Despite the importance of fish for management, gaps in baseline knowledge remain. Basic demographic information, termed life-history parameters, is needed to make predictions about their resilience under alternative management scenarios. These parameters include growth rate, age at maturation, fecundity and life expectancy. However, basic life-history parameters remain to be characterized, even for abundant fish species. Adding to the challenge, life-history characteristics of important Everglades species are known to be plastic in response to environmental conditions and survivorship and recruitment schedules are certain to be influenced by variation in hydroperiod. We intend to study the effect of hydroperiod on recruitment, size/age structure, growth, and fecundity, which, in turn, determine fish population dynamics. At present, data on fish reproduction, age and growth, and other life history characteristics are confined to a few species from a limited area of long-hydroperiod marsh in central Shark River Slough. As we continue the analysis and synthesis of data from the long-term fish collections, life-history information will help explain patterns of fluctuations in the time series. Accurate life-history data are also very important in building credible simulation models like ATLSS. Without empirical life-history data from a range of environments, the model will be simplistic and inadequate.

Florida↗

A global ecological classification of coastal segment units to complement marine biodiversity observation network assessments

A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 30 m Landsat-derived shoreline vector that was segmented into 4 million 1 km or shorter segments. Each segment was attributed with values from 10 variables that represent the ecological settings in which the coastline occurs, including properties of the adjacent water, adjacent land, and coastline itself. The 4 million segments were classified into 81,000 coastal segment units (CSUs) as unique combinations of variable classes. We summarize the process to develop the CSUs and derive summary descriptions for the seven MBON case study sites. We discuss the intended application of the new CSU data for research and management in coastal areas.

Oceanography↗

Final Project Memorandum: Ecological implications of mangrove forest migration in the southeastern U.S.

Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern United States. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. The objective of this research was to better evaluate the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological impacts of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial-nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). This research specifically investigated the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise and carbon storage.

Report↗

Assessing streamflow sensitivity to variations in glacier mass balance

The mountains ringing the Gulf of Alaska (GOA) receive upwards of 4–8 m yr −1 of precipitation (Simpson et al.2005; Weingartner et al. 2005; O’Neel 2012), much of which runs off into productive coastal waters. The alpine landscape is heavily glacierized, and storage and turnover of water by glaciers substantially influences the regional surface water balance (Neal et al. 2010). In turn, the land-to-ocean flux of freshwater impacts the biogeochemistry, physical oceanography, freshwater and marine ecology of the downstream components of the GOA ecosystem (e.g., Royer et al. 2001; Hood and Scott 2008). In this way, the links between terrestrial and ocean ecosystems along the GOA have widespread impacts on regional socioeconomic issues including water and hydropower resources, fish populations, and sea level change (Dorava and Milner 2000; Royer and Grosch 2006; Cherry et al. 2010; Gardner et al. 2013). Moreover, predicting future changes in physical, chemical and biological processes in near-shore ecosystems along the GOA hinges, in part, on developing a robust understanding of water storage and transfer by glaciers through streams to the ocean. Glacierized basins (i.e. presently ice covered as opposed to glaciated, or historically ice covered) are very efficient producers of runoff, yielding 2–10 times greater runoff than similarly sized, non-glacierized basins (Mayo 1984). The unique energy balance that characterizes these basins (Jansson et al. 2003; Hock 2005) results in substantial alterations to streamflow, even when fractional ice coverage is very small (Stahl and Moore 2006). Consistent and precise treatment of glacier runoff is key to accurate assessment of hydrologic, ecological and socioeconomic impacts, but previously used definitions for glacier runoff are variable. They include: 1) meltwater produced as negative annual mass balance (e.g., Fountain and Tangborn 1985); 2) storage changes in the monthly water budget, where solid precipitation is balanced by melt and evaporation (Huss 2011, concept #2); 3) meltwater derived from melting ice only (irrespective of melting snow or mass balance) (Nolin et al. 2010; Huss 2011, concept #1); 4) all meltwater derived from the glacier surface (Cogley et al. 2011, meltwater runoff); 5) total runoff from the glacier surface (meltwater runoff plus rain on the glacier) (Neal et al. 2010). Total glacier runoff (Definitions 4 and 5 above) includes a contribution from annual mass balance, i.e. the sum of accumulation and ablation through a mass balance year (Definition 1), or what has historically been referred to as the “net” balance (Cogley et al. 2011). Indeed, annual balance has been shown to be an important driver of streamflow trends in glacierized basins, with periods of persistent negative annual balance resulting in statistically significant increases in streamflow (e.g., Pellicciotti et al. 2010). However, in maritime climates, anomalies in glacier runoff can be disconnected from annual balance because of the high variability in winter precipitation. For example, positive anomalies in winter accumulation can result in elevated levels of glacier runoff in times of positive annual mass balance (Thayyen and Gergan 2010). Quantifying the impacts of changing glacier geometries (annual balance) on glacier runoff is essential for predicting future changes in streamflow in glacierized basins. However, determining the role that this component plays in total glacier runoff (Definition 5) requires consistent measurements of seasonal (or shorter period) mass balances, measurements of precipitation at multiple locations within a basin, and streamflow measurements in close proximity to a glacier’s terminus. Practical and logistical challenges associated with assembling such data sets typically preclude such partitioning. As a result, most analyses of the relationship between annual mass balance and streamflow rely on some component of model output to compute glacier runoff (e.g. Huss et al. 2008; Kaser et al. 2010). Ultimately, developing an understanding of how total glacier runoff will change in the future is critical for predicting downstream ecological impacts associated with changes in riverine fluxes of water, sediment, and solutes (e.g., metals and nutrients) to near-shore coastal ecosystems. The purpose of this paper is to evaluate relationships among seasonal and annual glacier mass balances, glacier runoff and streamflow in two glacierized basins in different climate settings. We use long-term glacier mass balance and streamflow datasets from the United States Geological Survey (USGS) Alaska Benchmark Glacier Program to compare and contrast glacier-streamflow interactions in a maritime climate (Wolverine Glacier) with those in a continental climate (Gulkana Glacier). Our overall goal is to improve our understanding of how glacier mass balance processes impact streamflow, ultimately improving our conceptual understanding of the future evolution of glacier runoff in continental and maritime climates.

Alaska↗

Foundations of translational ecology

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today's complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist–practitioner partnerships. The creativity and context‐specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use‐driven, actionable science. Moreover, addressing research questions that arise from on‐the‐ground management issues – as opposed to the top‐down or expert‐oriented perspectives of traditional science – can foster the high levels of trust and commitment that are critical for long‐term, sustained engagement between partners.

Frontiers in Ecology and the Environment↗

The genetic network of greater sage-grouse: Range-wide identification of keystone hubs of connectivity

Genetic networks can characterize complex genetic relationships among groups of individuals, which can be used to rank nodes most important to the overall connectivity of the system. Ranking allows scarce resources to be guided toward nodes integral to connectivity. The greater sage-grouse (Centrocercus urophasianus) is a species of conservation concern that breeds on spatially discrete leks that must remain connected by genetic exchange for population persistence. We genotyped 5,950 individuals from 1,200 greater sage-grouse leks distributed across the entire species’ geographic range. We found a small-world network composed of 458 nodes connected by 14,481 edges. This network was composed of hubs—that is, nodes facilitating gene flow across the network—and spokes—that is, nodes where connectivity is served by hubs. It is within these hubs that the greatest genetic diversity was housed. Using indices of network centrality, we identified hub nodes of greatest conservation importance. We also identified keystone nodes with elevated centrality despite low local population size. Hub and keystone nodes were found across the entire species’ contiguous range, although nodes with elevated importance to network-wide connectivity were found more central: especially in northeastern, central, and southwestern Wyoming and eastern Idaho. Nodes among which genes are most readily exchanged were mostly located in Montana and northern Wyoming, as well as Utah and eastern Nevada. The loss of hub or keystone nodes could lead to the disintegration of the network into smaller, isolated subnetworks. Protecting both hub nodes and keystone nodes will conserve genetic diversity and should maintain network connections to ensure a resilient and viable population over time. Our analysis shows that network models can be used to model gene flow, offering insights into its pattern and process, with application to prioritizing landscapes for conservation.

Idaho, Wyoming, Montana, Utah, Nevada↗

Influence of fire refugia spatial pattern on post-fire forest recovery in Oregon’s Blue Mountains

Context Fire regimes in many dry forests of western North America are substantially different from historical conditions, and there is concern about the ability of these forests to recover following severe wildfire. Fire refugia, unburned or low-severity burned patches where trees survived fire, may serve as essential propagule sources that enable forest regeneration. Objectives To quantify the influence of fire refugia spatial pattern and other biophysical factors on the process of post-fire tree regeneration; in particular examining both the proximity and density of surrounding refugia to characterize the landscape of refugial seed sources. Methods We surveyed regeneration at 135 sites in stand-replacement patches across a gradient of fire refugia density in eastern Oregon, USA. We characterized the influence of refugial seed source pattern and other environmental factors on the abundance of regenerating seedlings, and examined the relationship between post-fire climate and the temporal pattern of ponderosa pine seedling establishment. Results Tree seedlings were present in 83% of plots 12–17 years post-fire, and densities varied substantially (0–67800 stems ha −1 , median = 1100). Variation in seedling abundance was driven by the spatial patterns of refugial seed sources. Despite widespread post-fire shrub cover, high-severity burned forests have not undergone a persistent type conversion to shrublands. Ponderosa pine seedling establishment peaked 5–11 years after fire and was not closely associated with post-fire climate. Conclusions Fire refugia and the seed sources they contain fostered tree regeneration in severely burned patches. Management practices that reduce refugia within post-fire landscapes may negatively influence essential forest recovery processes.

Oregon↗

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m −2 yr −1 and total NPP in the range of 318–490 Tg C yr −1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m −2 yr −1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m −2 yr −1 . MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

Illinois, Indiana, Iowa, Kansas, Michigan, Minneso↗

Rethinking foundation species in a changing world: The case for Rhododendron maximum as an emerging foundation species in shifting ecosystems of the southern Appalachians

“Foundation species” are widespread, abundant species that play critical roles in structuring ecosystem characteristics and processes. Ecosystem change in response to human activities, climate change, disease introduction, or other environmental conditions may promote the emergence of new foundation species or the decline of previously important foundation species. We present rhododendron ( Rhododendron maximum ) as an example of an emerging foundation species in riparian forest and headwater stream ecosystems of the southern Appalachian Mountains and use its example to propose a dynamic approach to recognizing foundation species. As other species have declined, rhododendron has increased in abundance, biomass, and ecosystem importance, and now dominates the riparian zones and mesic uplands of much of the region. Rhododendron structures, stabilizes, and modulates functions within both terrestrial and aquatic ecosystems. Studies of forest ecosystem response to environmental conditions indicate that rhododendron may increase the resistance and resilience of its associated ecosystems to predicted anthropogenic stress, including climate change, nitrogen enrichment, and invasive species. A more dynamic conception of foundation species as dependent on ecosystem states will help ecologists to focus on ecosystem processes and services, rather than on historically dominant species, for restoration strategies.

Alabama, Georgia, North Carolina, South Carolina, ↗

Bottlenecks and multiple introductions: Population genetics of the vector of avian malaria in Hawaii

Avian malaria has had a profound impact on the demographics and behaviour of Hawaiian forest birds since its vector, Culex quinquefasciatus the southern house mosquito, was first introduced to Hawaii around 1830. In order to understand the dynamics of the disease in Hawaii and gain insights into the evolution of vector-mediated parasite–host interactions in general we studied the population genetics of Cx. quinquefasciatus in the Hawaiian Islands. We used both microsatellite and mitochondrial loci. Not surprisingly we found that mosquitoes in Midway, a small island in the Western group, are quite distinct from the populations in the main Hawaiian Islands. However, we also found that in general mosquito populations are relatively isolated even among the main islands, in particular between Hawaii (the Big Island) and the remaining Hawaiian Islands. We found evidence of bottlenecks among populations within the Big Island and an excess of alleles in Maui, the site of the original introduction. The mitochondrial diversity was typically low but higher than expected. The current distribution of mitochondrial haplotypes combined with the microsatellite information lead us to conclude that there have been several introductions and to speculate on some processes that may be responsible for the current population genetics of vectors of avian malaria in Hawaii.

Hawai'i↗

Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl

Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.

Movement Ecology↗

Phytoplankton community structure response to groundwater-borne nutrients in the inland bays, Delaware

To determine the impacts of groundwater-borne nutrients on phytoplankton biomass and community structure, we conducted a series of mesocosm experiments in the Inland Bays of Delaware. Four treatments were tested, including mesocosms coupled directly to submarine groundwater seepage, mesocosms with the addition of pumped submarine groundwater, mesocosms with the addition of phosphate, and control mesocosms with no nutrient addition. We measured chlorophyll a concentrations as a proxy for overall biomass and used genetic sequencing techniques to characterize the phytoplankton community structure. Groundwater carried a high N load to the estuary with NO 3 - up to 295 µmol l -1 and NH 4 + up to 55 µmol l -1 . As a result, treatment mesocosms had elevated NO 3 - and NH 4 + , while control mesocosms were relatively low in nutrients. In June, the highest chlorophyll a concentrations occurred in mesocosms attached to seepage meters after 3.5 d, with significant differences across all treatments. In August, groundwater-amended mesocosms reached the highest biomass concentrations, which peaked after 3 d. There were significant differences across all treatments, except control and phosphate-amended mesocosms which remained unchanged. Community sequence data showed that species assemblage was also impacted by availability of nutrients, with significant differences in community structure for mesocosms receiving nutrients vs. control mesocosms in both June and August experiments. Harmful algal species proliferated in high nutrient treatments, including Cylindrotheca closterium , Karlodinium veneficum , Nitzschia spp., and Heterocapsa spp. While the general relationship between nutrient supply and biomass production is well known, we demonstrate the role groundwater-borne nutrients and sediment processes play in shaping community structure in estuarine primary producers and in promoting harmful algal blooms.

Delaware↗

Resilience is not enough: Toward a more meaningful rangeland adaptation science

Rangeland ecosystems, and their managers, face the growing urgency of climate change impacts. Researchers are therefore seeking integrative social-ecological frameworks that can enhance adaptation by managers to these climate change dynamics through tighter linkages among multiple scientific disciplines and manager contexts. Social-ecological framings, including resilience and vulnerability, are popular in such efforts, but their potential to inform meaningful rangeland adaptation science is limited by traditional disciplinary silos. Here, we provide reflective lessons learned from a multidisciplinary Rangelands, Ranching, and Resilience (R3) project on U.S. western rangelands that addressed 1) biophysical science projections of forage production under future climate scenarios, 2) ranchers’ views of resilience using social science methods, and 3) outreach efforts coordinated through extension professionals. Despite the project's initial intentions, human dimensions and ecological researchers largely worked in parallel sub-teams during the project, rather than weaving their expertise together with managers. The R3 project was multidisciplinary, but it provides a case study on lessons learned to suggest how social and ecological researchers can move towards approaches that transcend individual disciplines. Transdisciplinary science and management in rangelands requires more than just conceptual social-ecological frameworks. Additional methodological concepts need to include: 1) relationship building; 2) shared meaning making; and 3) a commitment to continual conversations and learning, or staying with the trouble, following Haraway (2016). If the goal is to address meaningful rangeland adaptation science rather than just produce academic products, researchers, outreach professionals, and rangeland-based communities should address a series of critical troubling questions. In the process of addressing these, deeper engagement among and beyond disciplines will occur as relationship building, shared meaning, and continual conversations and learning facilitate staying with the trouble.

Rangeland Ecology & Management↗

Visioning ecologically diverse and harmonious futures of Korea in Good Anthropocene

1.The Korean Demilitarized Zone (DMZ), a buffer between North and South Korea, holds profound historical, cultural and ecological significance, as well as exceptional potential for conservation and transformation. This study explores ecologically diverse and peaceful futures for the Korean Peninsula by envisioning the DMZ as a landscape for harmonious human–nature co-existence. 2.Using the Nature Futures Framework ( NFF ) and the Seeds of Good Anthropocenes ( SoGA ) approach, we co-developed four ‘Living in Harmony with Nature’ visions that reflect diverse values and meanings of nature for sustainable and well-being oriented futures in Korea. 3.These visions emphasize balancing human activities with ecological integrity, reimagining the DMZ as a space for peace, restoration and shared stewardship. They express citizens' perspectives on aspirational and inclusive futures, highlighting existing initiatives as levers for change and intersectoral and interdisciplinary collaboration as key enabling conditions. 4.This visioning process demonstrates the role of the science-policy-society interface, diverse stakeholder engagement and integration of history, culture and social cohesion. This paper reflects on the lessons from this process and discusses implications for future scenario development—particularly how a whole-of-society approach can help identify policy options and societal transformations that advance nature–people-positive futures in Korea and beyond.

Korean Peninsula↗

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

River Research and Applications↗

Evaluating abundance and trends in a Hawaiian avian community using state-space analysis

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

Hawai'i↗

Perspectives and insights gained from applying landscape ecological approaches to the Upper Mississippi riverscape

Advances in remote sensing, spatial data collection, hydraulic and geospatial models, and the maturation of landscape ecology during the early 2000s spurred the concept of rivers as landscapes or ‘riverscapes’. Since that time, the Upper Mississippi River Restoration (UMRR) Program - one of the world’s longest running large-river ecosystem restoration and monitoring programs - has applied landscape ecological principles to the Upper Mississippi River System (UMRS). I examine spatial patterns of aquatic nutrient concentrations, submersed aquatic vegetation, and fish and mussel communities, finding that within-river patterns are often patchy in nature, likely resulting from how nutrient processes and community traits interact with spatial variability in hydraulic exchange patterns. Local-scale patchy spatial patterns in the UMRS are embedded in system-scale longitudinal gradients and a hierarchical view of the river has provided a foundation for strategic river restoration planning. Key Words: Aquatic Habitat, hydraulic connectivity, patch, restoration, riverscape

BioScience↗