Physical and social access to land: Spatio-temporal patterns of agricultural expansion

Abstract The expansion of agriculture is posited as one of the main dynamics of land cover change globally, and the robust modeling of these processes is important for policy as well as academic concerns. Madagascar's farmers stand accused as the "proximate agents" of land conversion in one of the world's "hottest" biodiversity hotspots, and numerous studies have been conducted to describe and model the processes by which the country's forests are giving way to agriculture. This paper concerns a relatively small area on the island's eastern escarpment where considerable national and international attention has been paid to slow the expansion of agriculture into the remaining natural forests. The approach adopted here is to begin by examining the degree to which patterns of agricultural conversion can be attributed to a set of factors that have been identified as significant at broader scales in Madagascar and elsewhere, namely topography and prior human settlement and land use patterns. A regression model is constructed, and its predictions compared to the observed land conversion over a 43-year period. The study then examines in detail the spatial patterns highlighted by the failure of the model (the residuals of the regression), breaking the study area into smaller zones, or landscapes. The spatio-temporal trajectories of these zones are then contrasted, with particular attention to the institutional arrangements governing access to land resources. The study finds that while overall land change patterns in the region are largely explained by elevation and village proximity, more specific, sub-regional, trajectories reflect the signatures of institutions governing access to land

Changed Patterns of Genomic Variation Following Recent Domestication: Selection Sweeps in Farmed Atlantic Salmon

The introduction of wild Atlantic salmon into captivity, and their subsequent artificial selection for production traits, has caused phenotypic differences between domesticated fish and their wild counterparts. Identification of regions of the genome underling these changes offers the promise of characterizing the early biological consequences of domestication. In the current study, we sequenced a population of farmed European Atlantic salmon and compared the observed patterns of SNP variation to those found in conspecific wild populations. This identified 139 genomic regions that contained significantly elevated SNP homozygosity in farmed fish when compared to their wild counterparts. The most extreme was adjacent to versican, a gene involved in control of neural crest cell migration. To control for false positive signals, a second and independent dataset of farmed and wild European Atlantic salmon was assessed using the same methodology. A total of 81 outlier regions detected in the first dataset showed significantly reduced homozygosity within the second one, strongly suggesting the genomic regions identified are enriched for true selection sweeps. Examination of the associated genes identified a number previously characterized as targets of selection in other domestic species and that have roles in development, behavior and olfactory system. These include arcvf, sema6, errb4, id2-like, and 6n1-like genes. Finally, we searched for evidence of parallel sweeps using a farmed population of North American origin. This failed to detect a convincing overlap to the putative sweeps present in European populations, suggesting the factors that drive patterns of variation under domestication and early artificial selection were largely independent. This is the first analysis on domestication of aquaculture species exploiting whole-genome sequence data and resulted in the identification of sweeps common to multiple independent populations of farmed European Atlantic salmon

Structure and functional composition of macroinvertebrate communities in coastal plain streams across a precipitation gradient

Climate change is expected to alter rainfall and temperature regimes across the world. The hydrology and riparian zone vegetation of lotic ecosystems are tightly linked to rainfall and a mechanistic understanding of the effects of rainfall on lotic ecosystems is needed to forecast the ecological impacts of climate change. However, it is difficult to isolate rainfall effects from other environmental variables that covary across climates. To address this, we leveraged a unique steep rainfall gradient with few covarying changes in elevation, temperature, and geology to evaluate the effects of rainfall on stream invertebrate communities. We surveyed nine streams in the Texas Gulf Coast Prairie distributed along a 550–1,350 mm/year rainfall gradient. Four sites were classified as drier semi-arid streams (\u3c750 mm annual rainfall) and five sites were classified as wetter sub-humid streams (\u3e750 mm annual rainfall). A suite of characteristics including benthic invertebrate community metrics, flow conditions, and water quality variables were assessed monthly for 14 months at each site to relate precipitation regime to stream structure and function. Precipitation regime was observed to be a master explanatory variable. As annual rainfall increased, the flow environment became more stable within seasons and predictable across seasons, influencing spatial structure and temporal variability of invertebrate community composition. Wetter streams were dominated by slower growing taxa without adaptions for desiccation resistance and strong dispersal. Wetter sites displayed seasonal variation in community composition and species richness, whereas temporal variation in communities in drier streams was controlled by stochastic variation in flow conditions. These observations show that differences in local annual rainfall correlated with major changes to community structure and functional composition. We hypothesise that this association is related to the connection of rainfall to hydrological stability, particularly the frequency of low flow disturbances, and the subsequent effects on riparian vegetation and temporally available niches to stream invertebrates. Our work adds to evidence that alterations in precipitation patterns associated with climate change have sweeping impacts on lotic fauna

A general pattern of trade-offs between ecosystem resistance and resilience to tropical cyclones

Tropical cyclones drive coastal ecosystem dynamics, and their frequency, intensity, and spatial distribution are pre-dicted to shift with climate change. Patterns of resistance and resilience were synthesized for 4138 ecosystem time series from n = 26 storms occurring between 1985 and 2018 in the Northern Hemisphere to predict how coastal ecosystems will respond to future disturbance regimes. Data were grouped by ecosystems (fresh water, salt water, terrestrial, and wetland) and response categories (biogeochemistry, hydrography, mobile biota, sedentary fauna, and vascular plants). We observed a repeated pattern of trade-offs between resistance and resilience across analyses. These patterns are likely the outcomes of evolutionary adaptation, they conform to disturbance theories, and they indicate that consistent rules may govern ecosystem susceptibility to tropical cyclones

Development of a non-cloggable subsea data logger for harsh turbidity current monitoring

Large submarine flows of sediment (sand and mud), known as turbidity currents, transfer and bury significant amounts of organic carbon and pollutants to the deep sea via submarine canyons. They are also significant geohazards, regularly breaking networks of seabed telecommunications cables that carry > 99% of global data that underpin the internet. Despite this, key parameters (notably their sediment concentration) in these flows are yet to be directly measured in real-time due to their inherently harsh environment that is unsuitable for commercial conductivity sensors. To address this issue, a subsea datalogger (SSDL) is developed with a planar conductivity sensor head that can measure the sediment concentration within dense turbidity currents. Unlike conventional sensors, the planar design of the SSDL’s sensor prevents clogging at high sediment concentrations, allowing for continuous measurements within turbidity currents. The conductivity sensor is developed with a temperature sensor which is measured using an external 16-Bit ADC which is controlled with a SAMD21 32-Bit ARM microcontroller. The SSDL measures the temperature and the conductivity of the seawater once every 4 seconds for over a year. In an initial device test, the SSDL can record a turbidity current within the Bute Inlet, Canada. It is found that the seawater’s conductivity increases with salinity concentration and decreases with sediment concentration. The SSDL developed here can thus be used for both conventional subsea datalogging applications and high turbidity current applications

Contemporary visions of progress in ecology and thoughts for the future

Although ecological research is progressing rapidly, the answers to certain key questions continue to elude us. This paper considers several of the contemporary challenges facing ecology. (1) Terminology is voluminous and often poorly defined, resulting in inefficient communication. (2) The concept of scale affects our inferences about system structure and function, requiring us to continue an almost heuristic investigation of breaks, domains, and integration. New tools that more explicitly incorporate scalar issues will need to be developed for progress to take place in the field of ecology. (3) Increasingly, it is expected that applied questions will be solved in less than a year. This demand for solutions from ecologists often produces short-term and inadequate responses. (4) How can ecologists improve communication between subdisciplines, with undergraduate students, and with the public? How will ecology be done in the future, and by whom? We provide some background to these observations and questions, and offer some potential solutions from the viewpoint of young practicing ecologists