Weeds from the Orobanchaceae family are serious parasitic pests in crop production, e.g., Striga asiatica (L.) Kuntze, Striga hermonthica (Del.) Benth and S. aspera (Wild) Benth ( Rodenburg and Johnson, 2009 ). There is another group of weeds that produce chemicals that are detrimental to crops such as P. hysterophorus with its allelopathic effect but Desmodium spp. has allelopathic effect on other weeds, e.g., S. asiatica and S. hermonthica. Allelopathic effect of Desmodium spp. to Striga spp. has been utilized to develop a push–pull technology, which is a climate smart weed management technology ( Khan et al., 2011; Pickett et al., 2014 ). Under the push and pull technologies the weeds are used to interfere with germination of parasitic weeds to enhance crop growth and they provide competition useful for increasing growth.
The accidental introduction of the economically destructive zebra mussel into US waters when a ship's ballast water was released led Congress to create the Nonindigenous Aquatic Nuisance Prevention and Control Act in 1990. This act covers any plant, animal, or other “viable biological material,” such as a virus, that disperses to an aquatic ecosystem in which it is not historically found. In contrast to the Lacey Act provisions, a nonindigenous species does not have to be from a foreign country. To be termed a nuisance, a nonindigenous species must threaten the abundance or diversity of native species or the ecological stability or commercial productivity of the infested waters. The act mandates creation of a task force to implement a program to prevent the introduction and dispersal of aquatic nuisance species, but it does not specify who determines which species are a nuisance ( Bean and Rowland, 1997 ).
Weed Dynamics and Management in Wheat
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Climate change will affect species dominance in different ecologies and this will determine which management practice to apply. Weeds are among the most significant biological yields reducing factors together with pests and disease and where infestations are severe yield losses as high as 90% have been recorded. Naturally weeds compete intensely with any plant and the competition is equally high among different weed species. In southern Africa there is a wide diversity of weed flora that colonizes agricultural land (both cropped land and livestock pastures). Under conditions where rainfall is limiting and temperature is unfavorable to crops. Some weed species dominate and utilize resources for vegetative and reproductive growth stages ahead of crops. Table 6.1 shows most common weed species found on arable land in southern Africa. Although absolute elimination of weeds is not necessary, the aim of the most effective management practice will be to reduce to bare minimum interference. There is a need for crop interference to be minimized, especially during the critical period of weed competition, a period where the effect of competition for resources should be least to avoid crop losses ( Akobundu, 1987 ). This period varies with crop variety, cropping system, weed species, and climatic condition of a particular area. Climatic conditions that favor dominant weed flora development will lead to increased interference with crop growth.
There are numerous reports in the veterinary medical literature of H. perforatum causing photosensitization in domestic animals and in some locations it is considered a noxious weed . Wet and/or desiccated plant tops can also cause photosensitization in humans, ruminants, horses, and other mammals. Onoue et al. (2011) , using in vitro methods, showed that hypericin, pseudohypericin, and hyperforin had photoreactivity when exposed to 250 W/m 2 of sunlight. In sunlight, quercetin attenuated the generation of singlet oxygen by hyperforin and quercetin had no effect on hypericin. The photosensitizing chemical is hypericin, a phenanthroperylenequinone that has complex physical chemical behavior ( Ernst, 2000; Theodossiou et al., 2009 ). In most bioassays hypericin is present as a monosodium salt. The maximum absorbance of hypericin salts is 548 and 591 nm in ethanol solution and it has red fluorescence at 594 and 642 nm. Hypericin associates with proteins (albumen, low-density lipoprotein, etc.) and has red fluorescence. In light, it has a high triplet quantum yield. It is an efficient singlet oxygen producer and superoxide anion generator, and these radicals can trigger apoptosis and cellular necrosis. Hypericin can also cause phototoxicity in the lens and retina, thereby damaging the eye ( Ehrenshaft et al., 2013 ). Damage to proteins in the lens of the eye is not repairable and temporal summation results in cataracts due to damage to cx-crystallin protein in the lens. Using self-reporting information, a study showed that there is an association between cataracts and the use of H. perforatum extract ( Booth and McGwin, 2009 ). Photosensitization is a dose-limiting side effect of H. perforatum extracts. There are reports of photosensitization occurring after oral use of phytopharmaceutics containing H. perforatum—both were uses of extract prepared for topical use ( Ulbricht et al., 2010 ).
Our model results suggest that, across our sampling region, an optimal maximum seed sourcing distance of 272 km, or approximately 170 miles, could reduce the risk of introducing a new exotic plant species as a contaminant of native species’ seed, while retaining as much seed availability as possible, measured as the number of acceptable production locations. That median value well represents most of the optimal maximum distance values calculated by our model, despite a long tail of higher values (Fig 4A). Those higher values were clustered spatially at the northern edge of our sampling region along the Canadian border (Fig 5A). While it is possible that there are fewer exotic species invading our sampling region from the north, this pattern is also likely in part due to occurrence data for exotic plant species being much less available from Canada (e.g., Rhaponticum repens in Appendix B). The lowest optimal maximum distance values are located in the southern half of our sampling region (Fig 5A). The randomization tests support that this area experiences both high pressure from nearby new exotic species, as can be seen when the spatial structure of the production locations is removed (Fig 5B), and high seed availability from nearby commercial production locations, as can be seen when the exotic species data are generated randomly (Fig 5C). Therefore, that is the region where it is most critical, but also most feasible, to source seed within our model’s suggested median optimal maximum distance.
Optimal maximum distances were calculated for each of the 483 restoration locations, mapped in ArcGIS, and solutions for all other possible locations were interpolated by using the IDW (inverse distance weighted) tool with default settings in ArcGIS.
Here we presented results from a decision framework in which we sought to quantitatively find the balance between two primary concerns of grassland restoration practitioners: 1. Availability of native prairie seed and 2. Risk of unintentional introduction of novel, invasive seed via contamination. Our analyses indicated that seed obtained from no more than 272 km from a prairie restoration site would balance these objectives. If a strategy of facilitated migration is pursued to adapt to anticipated future climate change, this distance would increase to 398 km to maintain current levels of seed availability. Our results are consistent with several current recommendations/requirements for maximum seed-sourcing distances in the sampling region but are more transparent in their derivation. We hope these results provide practical guidance to public entities that support prairie restorations and valuable insights to restoration practitioners about the potential hazards of importing seeds from long distances.
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Seed source recommendations among agencies can vary widely, from “local” recommendations of <42 km (25 miles) to historical recommendations of up to 482 km (300 miles) away . Most, however, do not give a definitive distance threshold to follow [but see 15, 30]. Instead, recommendations often include adherence to local ecotypes and avoidance of agronomic and horticultural cultivars [14, 33, 34], to preserve long-term fitness of extant populations that are (presumed to be) best adapted to the site . While use of locally sourced seed in close proximity to a restoration is seen as ideal, there are often limitations on species availability in quantities needed for large-scale restorations. Using cultivated seed, often sourced from greater distances, increases availability but comes with increased risk of introducing exotic, invasive species’ seed into grassland restorations. Results from our analyses offer guidance on minimizing risk of exotic species’ introduction, while maximizing native seed availability.
We searched ten sources (S1 Table) for native-seed production companies within our focal region. To be included in our model, a company had to grow or wild-harvest seed from native plant species that would be appropriate for a grassland-style planting (e.g., native roadside plantings, prairie restorations) in our model’s sampling area. Companies that did not produce seed or wild-harvest seed (i.e., they re-distribute seed purchased wholesale) were excluded because they did not have a production location that could be spatially referenced. We contacted each company to ensure they met the above criteria. We identified 46 production companies that operated 50 production locations (Fig 3). Some production locations did not have a physical address (e.g., when the location was an agricultural field with no associated structures). Those locations were recorded as the center of the nearest township. Addresses or townships were georeferenced using Google Earth Pro (7.3.2), then exported to ArcGIS (10.6, ESRI, Redlands, CA). Because location information could include proprietary information about a given producer, we could not publicly release this data. We acknowledge that some grassland species’ seed appropriate for native plantings in our area are produced outside our focal region . A nationwide assessment was beyond the scope of our study.
Numerous idiosyncratic factors affect the true probability that a weed contaminant will be present in a seed lot. Such factors include the abundance of different weed seeds at the time of harvest, the efficiency with which weeds are removed by various post-harvest cleaning techniques, and the potential for contaminated seed lots to be detected during seed testing and regulatory inspections. Each of these factors is influenced by numerous other variables that may change over time (e.g., weed densities and weather conditions in production areas, efficiency of weed management, timing of harvest, size and shape of weed seeds, etc.). We consider efforts to account for all of these variables to be untenable. Our abstraction of the problem assumes a constant, non-zero probability of introduction for each exotic weed species that could occur in a production area. Thus, as additional exotic weed species are encountered, the probability that at least one of these species is present in a shipment of seed increases. Our analysis provides an empirical estimate of the rate at which new weed species might be encountered as distance from a restoration site increases and a baseline against which future analyses might be compared.