A Comparison of Five Statistical Methods for Predicting Stream Temperature Across Stream Networks

The health of freshwater aquatic systems, particularly stream networks, is mainly influenced by water temperature, which controls biological processes and influences species distributions and aquatic biodiversity. Thermal regimes of rivers are likely to change in the future, due to climate change and other anthropogenic impacts, and our ability to predict stream temperatures will be critical in understanding distribution shifts of aquatic biota. Spatial statistical network models take into account spatial relationships but have drawbacks, including high computation times and data pre-processing requirements. Machine learning techniques and generalized additive models (GAM) are promising alternatives to the SSN model. Two machine learning methods, gradient boosting machines (GBM) and Random Forests (RF), are computationally efficient and can automatically model complex data structures. However, a study comparing the predictive accuracy among a variety of widely-used statistical modeling techniques has not yet been conducted. My objectives for this study were to 1) compare the accuracy among linear models (LM), SSN, GAM, RF, and GBM in predicting stream temperature over two stream networks and 2) provide guidelines in choosing a prediction method for practitioners and ecologists. Stream temperature prediction accuracies were compared with the test-set root mean square error (RMSE) for all methods. For the actual data, SSN had the highest predictive accuracy overall, which was followed closely by GBM and GAM. LM had the poorest performance overall. This study shows that although SSN appears to be the most accurate method for stream temperature prediction, machine learning methods and GAM may be suitable alternatives

Grass-Shrub Associations over a Precipitation Gradient and Their Implications for Restoration in the Great Basin, USA

As environmental stress increases positive (facilitative) plant interactions often predominate. Plant-plant associations (or lack thereof) can indicate whether certain plant species favor particular types of microsites (e.g., shrub canopies or plant-free interspaces) and can provide valuable insights into whether “nurse plants” will contribute to seeding or planting success during ecological restoration. It can be difficult, however, to anticipate how relationships between nurse plants and plants used for restoration may change over large-ranging, regional stress gradients. We investigated associations between the shrub, Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis), and three common native grasses (Poa secunda, Elymus elymoides, and Pseudoroegneria spicata), representing short-, medium-, and deep-rooted growth forms, respectively, across an annual rainfall gradient (220–350 mm) in the Great Basin, USA. We hypothesized that positive shrub-grass relationships would become more frequent at lower rainfall levels, as indicated by greater cover of grasses in shrub canopies than vegetation-free interspaces. We sampled aerial cover, density, height, basal width, grazing status, and reproductive status of perennial grasses in canopies and interspaces of 25–33 sagebrush individuals at 32 sites along a rainfall gradient. We found that aerial cover of the shallow rooted grass, P. secunda, was higher in sagebrush canopy than interspace microsites at lower levels of rainfall. Cover and density of the medium-rooted grass, E. elymoides were higher in sagebrush canopies than interspaces at all but the highest rainfall levels. Neither annual rainfall nor sagebrush canopy microsite significantly affected P. spicata cover. E. elymoides and P. spicata plants were taller, narrower, and less likely to be grazed in shrub canopy microsites than interspaces. Our results suggest that exploring sagebrush canopy microsites for restoration of native perennial grasses might improve plant establishment, growth, or survival (or some combination thereof), particularly in drier areas. We suggest that land managers consider the nurse plant approach as a way to increase perennial grass abundance in the Great Basin. Controlled experimentation will provide further insights into the life stage-specific effectiveness and practicality of a nurse plant approach for ecological restoration in this region

Seed size influence on germination responses to light and temperature of seven pioneer tree species from the Central Amazon

In Amazon secondary forests are dominated by pioneer species that typically produce large amounts of small and dormant seeds that are able to form a persistent soil seed bank. Seed dormancy in this group of species is overcome by environmental conditions found in open areas, such as high irradiation or alternating temperatures. Nevertheless, a variety of germination responses to environmental factors is known among pioneers; some of them may germinate in diffuse light or in darkness condition at constant temperature. Seed mass can be considered as one of the factors that promotes this variety. Regarding species with very small seeds, it seems that the trigger for germination is light and for larger seeds temperature alternation may be a more important stimulus. In this study we established a relationship between seed mass and germination response to light and alternating temperature for a group of seven woody pioneer species from the Amazon forest. We found that an increase in seed mass was followed by a decrease in the need for light and an increase in the tolerance to alternating temperatures. Understanding germination strategies may contribute with the knowledge of species coexistence in high diverse environments and also may assist those involved in forest management and restoration.Na Amazônia as florestas secundárias são dominadas por espécies pioneiras que, normalmente, produzem grandes quantidades de sementes pequenas, dormentes e capazes de formar bancos de sementes no solo. A dormência neste grupo de espécies é superada pelas condições ambientais de áreas abertas, como alta irradiação ou alternância de temperaturas. No entanto, uma variedade de respostas de germinação aos fatores ambientais é conhecida entre as pioneiras; algumas germinam em luz difusa ou no escuro sob temperatura constante. Um dos fatores promotores desta variedade é a massa das sementes. Parece que para as espécies com sementes muito pequenas, o estímulo para que ocorra germinação é a luz e, para sementes maiores, a alternância de temperatura pode ser um estímulo mais importante. Neste estudo, estabeleceu-se uma relação entre a massa das sementes e a resposta de germinação à luz e temperatura para sete espécies pioneiras arbóreas da floresta amazônica. Descobrimos que o aumento na massa da semente foi acompanhado por diminuição da necessidade por luz e aumento da tolerância à alternância de temperatura. Compreender estratégias de germinação pode contribuir para os conhecimentos sobre a coexistência de espécies em ambientes altamente diversos e também pode ajudar aos pesquisadores envolvidos no manejo e restauração florestal