We repeated all analyses with these variables and a summary scale reflecting the strength of controls on medical marijuana distribution, but these analyses failed to produce statistically significant results for any age group .Prior studies focusing on whether medical marijuana laws impact young people’s consumption of marijuana have produced mixed results. In the absence of robust evidence that medical marijuana laws are not adversely impacting young people, the number of states passing these laws has accelerated. The analyses presented here found that medical marijuana laws are not causally associated with recent marijuana consumption in young people. However, we did find that medical marijuana laws impact the initiation of marijuana use, but that this is confined to young adults and does not include the more vulnerable populations of early and late adolescents.Prior research has largely focused on how medical marijuana laws impact rates of marijuana consumption, placing less emphasis on the initiation of marijuana use. But the potential for these laws to impact the age-at-first use of marijuana has considerable public health significance. Initiating marijuana use in early adolescence is an important prognosticator for subsequent drug dependence . Younger age at initiation is one of the strongest predictors of drug dependence and related problems later in life .
Although we found a positive age gradient in the rates of consuming marijuana during the past month, horticulture solutions patterns were different for initiating marijuana use. Our analysis showed that the initiation of marijuana use most commonly occurs during late adolescence. This finding is consistent with developmental theories suggesting that high-school age youth are uniquely prone to act on social messages and to experimentation with drugs . Fully controlled regression analyses showed that medical marijuana laws significantly increase the likelihood oftrying marijuana for the first time among young adults, but not younger age groups. Young adults are in the peak years of engagement with illicit drugs during the life course . Compared to early and late adolescents, young adults have heightened availability and opportunities to use illicit drugs. This age group is past the peak age for initiating marijuana use and is therefore at a reduced risk for developing persistent marijuana-use disorders. However, our findings suggest that some of the young adults in this study might never have tried marijuana had they not been in a state that legalized medical marijuana. Future research should disentangle the mechanisms that account for why young adults in states with medical marijuana laws are more prone to initiating use. This finding is consistent with the notion that medical marijuana products may be diverted into illegal markets, thus increasing marijuana’s availability and driving down its price . Increased accessibility of illicit drugs is an important factor predicting the likelihood that individuals will initiate use .
Where larger numbers are using marijuana, whether for medical or non-medical reasons, individuals interested in trying the drug can more easily access information on how to obtain it . Another possibility is that, in states with relatively lax enforcement of existing medical marijuana regulations, young adults are more willing to try marijuana because they perceive that the risk of arrest is low or generally perceive the drug as less risky. Given the importance of this issue for drug policy, research on the mechanisms through which medical marijuana laws promote the initiation of marijuana use by young adults should be prioritized. This study was subject to several limitations. We were unable to rule out the possibility that, over longer windows of time, state medical marijuana laws will exert impacts on marijuana consumption and initiation by younger people dwelling in these states. We tested models using variables representing the length of time that each state’s medical marijuana law had been in place but found no statistically significant effects. We also could not examine whether legalization of marijuana for medical purposes has different effects as compared with recreational legalization; the NSDUH data did not extend into the years after recreational policies were established. The NSDUH data collection takes place at various points through the calendar year, and the date of any given participant interview may or may not have matched up with enactment of new medical marijuana legislation in their state; however local variation in availability of marijuana would make even a stricter date-based classification subject to the same potential mismatch on the individual level. Under reporting of drug consumption and initiation is also likely because of social acceptability concerns and survey respondents’ fears of disclosure .
The NSDUH used computer-assisted interviewing to increase the validity of self-reports consistently throughout the 10-year observation period. As young people’s views about marijuana grow more permissive over time , survey respondents could become more willing to report that they have tried marijuana thus introducing bias into this analysis. Our multivariate models controlled for time trends to address this problem. Finally, our analyses could not capture sub-state variation in the implementation of medical marijuana laws .Anticoagulant rodenticide exposure and poisoning has emerged as a conservation concern for non-target wildlife. These toxicants are used to eradicate or suppress rodent pest populations in agricultural or urban settings to minimize economic losses. Generally, the mechanism of AR function is to bind and inhibit enzyme complexes responsible for the recycling of vitamin K1, thus creating a series of deleterious clotting and coagulation impairments. The ARs are grouped into two classes: first-generation compounds, which require several doses to cause intoxication, and second-generation ARs, which are more acutely toxic often requiring only a single dose to cause intoxication and persist in tissues and in the environment. Rodents have started to develop resistance to both first-generation and second-generation ARs, prompting increasingly greater reliance on more acutely toxic compounds and increased distribution by AR users. Primary exposure by ingestion of bait or secondary exposure through consumption of exposed prey has been documented in numerous species of endangered and common non-target wildlife. Wildlife are thought to be at greatest risk of exposure to ARs in agricultural, urban or peri-urban settings, where large quantities of these compounds are often used. However, little is known about the risks to wildlife in settings with little or no anthropogenic influences. Fishers , a large mustelid and the largest member in the genus Martes, were once widely distributed throughout west coast of North America, but have experienced significant population declines, including extirpation from some regions and contractions of historic ranges. Populations of fishers inhabiting California, Oregon and Washington have been designated as a Distinct Population Segment and declared a candidate species for listing under the federal Endangered Species Act . The west coast DPS encompasses areas where fishers were extirpated from Washington and central and northern Oregon, a reintroduced population in the Cascade mountains of southern Oregon, and two extant and isolated populations, one spanning southern Oregon and northern California and another in the southern Sierra Nevada mountains of California. The population status of fishers in the southern Oregon/northern California is unknown; however population estimates for the isolated fisher population in the southern Sierra Nevada range from 150–300 fishers, grow benches with 120–250 in the adult age class. Because fishers in the DPS occur in and are dependent on mid to late-seral stage coniferous and hardwood forests and are not associated with agricultural or urban settings, toxicants have not been previously considered a likely threat to fisher populations. We assessed the magnitude of AR exposure and poisoning among fisher carcasses submitted for necropsy from 2006 to 2011 as part of a collaborative effort studying threats to population persistence of fishers in California. Additionally, spatial analysis of telemetry data from sampled fishers was conducted in an effort to identify potential sources of AR in the environment. We hypothesized that due to fishers being a forest-dependent carnivore, exposure to ARs will be rare.
Fishers were captured in box traps modified with a plywood cubby box , sampled, and fitted with a VHF radio-collar and monitored via telemetry. Fisher carcasses were submitted from the two isolated California populations by three fisher monitoring projects . Carcasses from the northern California population were submitted by the Hoopa Valley Reservation Fisher Project , conducted in northwestern California within tribal, private and public lands, and non-monitored fishers on public and private lands throughout the northern Sierra Nevada/southern Cascade Mountain borderlands of north central California . Carcasses from the southern Sierra Nevada California population were submitted by the Sierra Nevada Adaptive Management Project and the USDA Forest Service Kings River Fisher Project ; both projects were conducted on the Sierra National Forest in the northern and central portions of this population’s extent .Deceased fishers were collected by project personnel whenever a fisher was determined to be inactive for .24 hours, a mortality signal from the VHF collar was detected or when unmarked fisher carcasses were opportunistically observed at the project sites or adjacent areas. Fisher carcasses were stored in a 220 uC freezer until a complete necropsy to determine causes of mortality was performed by a board-certified pathologist specializing in wildlife at the California Animal Health and Food Safety Laboratory System or the University of California Davis Veterinary Medical Teaching Hospital in Davis, CA, USA. Liver samples were collected during necropsy and submitted for screening and quantification of seven ARs at CAHFS by liquid chromatographytandem mass spectrometry for screening presence of ARs and high-performance liquid chromatography to quantitate positive samples. The AR compounds tested for included first-generation ARs, warfarin , diphacinone , chlorophacinone , and coumachlor ; and second-generation ARs, brodifacoum , bromodiolone , and difethialone . The reporting limits were 0.01 ppm for BRD, 0.05 for WAF, BRM, and COM, and 0.25 ppm for DIP, CHL, and DIF. Detectable compound concentrations that were below quantitate limits were labeled as ‘‘trace’’ concentrations. Age classification was determined by tooth wear, sagittal crest or testicular/teat development, field and laboratory observation, and monitoring of individual animals. Fishers were classified as kits when fully or semi-altricial and dependent on milk for nourishment , juveniles if weaned and ,12 months of age, sub-adults when between 13–24 months of age, and adults $24 months of age.For monitored fishers, telemetry locations were used to generate 95% minimum convex polygon home-range centroids to represent a centralized point within the core area of movement within each individual fisher home-range within each project area. For each fisher, three centroids representing three sampling time frames were calculated using ArcView 9.1 home range extensions. The first centroid incorporated all fisher locations from initial capture until death, irrespective of the monitoring time; the second centroid incorporated fisher locations collected six months prior to death; and the third centroid incorporated only the fisher locations collected three months prior to death. These two latter centroids containing locations collected over a shorter time period prior to death were calculated because some ARs have relatively short half lives and any spatial clustering in these MCP centroids might suggest the locale of recent sources of AR exposure. Only fishers with $3 months of monitoring were used for spatial analysis, individuals that had less than or were opportunistically collected were excluded. Centroids were analyzed by spatial scan statistics to determine whether exposure to ARs, exposure to different generation classes of ARs, or exposure to individual compounds of ARs were distributed uniformly or spatially clustered in each of the two California populations. SaTScan version 9.1.1 was used to evaluate two separate models. First, a Bernoulli model utilizing count data was used to determine if spatial clustering occurred in exposed and non-exposed fishers, or in first or second-generation class ARexposure. The second model, a multinominal model using categorical data, was used to assign each fisher to a group based on the number of AR compounds detected and to examine possible clustering of individuals with high numbers of AR compounds. SatScan uses these models to scan the geographic area encompassing the MCP centroids to detect spatial clusters encompassing not more than 50% of the centroids. The elliptical scanning window option was chosen for both models because it utilizes both circular and elliptical shapes to allow for a better fit to linear geographic features that occur within the fisher’s habitat. All statistical values from the models were generated by Monte Carlo simulations of 999 iterations and clusters evaluated for significance with alpha = 0.05.