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Bend's culture is one of the things that makes Bend so great. As a whole we are fun seekers, outdoor lovers, beer fanatics, and friend makers. We love our dogs, our free time, our food trucks, our trails, and our powder days. There's a lot to get excited about here, and believe us, we get excited about all of it. We also want you to share that excitement!
The good people at Visit Bend have put together a campaign encouraging people to visit Bend like a local. We were inspired and wanted to share some central beliefs to the mission of Wanderlust Tours.
For over 23 years Wanderlust Tours has shared the beauty of central Oregon while striving to preserve the earth and care for natural habitats. We train our staff with this mentality in mind and teach our guests to do the same. Here are a few ways we do that.
- We carpool. Most of our trips meet at our office in Bend before we transport guests in one vehicle to our final destination. This keeps lake parking lots less crowded, cuts down on road wear and tear, and is better for our environment.
- We pick up trash. Wherever we go we try to practice LNT (leave no trace). This means that our trips will not leave an impact, but it also means that we pick up after others. Each of our guides brings a trash bag in case they see floating trash along the trail.
- We clean the caves. Each year Wanderlust Tours joins forces with other local companies to clean the caves and desert area east of town. Anyone is welcome to join in these efforts. This year's Cave Cleanup is scheduled for May 6, 2017.
- We don't use plastic bottles. In fact, we exclusively use recyclable cups, plates and utensils. We like to call this practice "pre-cycling." We sell bottles from Hydro Flask in our office and encourage our guests to fill up their bottle before leaving for the tour.
- We wash our boats after each water tour. Why? Aquatic invasive species attach to boats and travel from one body of water to another. They displace native species and harm the fish and wildlife habitat. Worst of all, they are extremely difficult to remove once they arrive. We don't want to disrupt the natural wildlife!
- We sell locally-made products. This supports local businesses and cuts down on the need for shipping (think extra packaging waste, fuel, etc.)
There are a ton of other great ways to learn how to "visit like a local." Visit Bend has worked hard to put together some awesome tips! Including how to navigate those round-a-bouts! Search the hashtag on Instagram or Facebook and find out other ways you can visit like a local!

domain: travel


Trade studies and close examination of direct detection laser crosslinks for a number of applications have shown that the development risk is comparable to or lower than that of RF systems. Since laser crosslinks offer significant advantages over RF crosslinks for the same applications, the specification of laser crosslinks is a good choice. The reason that the risk is low is examined in this paper which details the technologies and components which comprise current, second generation design laser crosslinks. The specifics which are examined include diode power summing, diode life, data rates of a Gbps and beyond, detector sensitivity/radiation effects, telescopes, gimbals and optics, alignment stability, acquisition, pointing and tracking, electronics and the space qualification of assemblies and systems. Differences between first and current (second generation) system designs and technologies are examined. An assessment of the maturity of the current direct detection technology is made and conclusions formulated.


A Presidency source told SaharaReporters that some of President Muhammadu Buhari’s aides are concerned about his health.
The aides believe that the president’s frequent travels might be taking a toll on his wellbeing. The source said that the president’s personal physician, Dr. Suhayb Sanusi Rafindadi, now stands very close to him during and after public events on foreign and sometimes domestic trips due to concerns over the President’s health.
Also, Buhari’s chief security officer, Abdulkarim Dauda, travels two days ahead of the president in order to spend two days in hotel rooms where Mr. Buhari is expected to sleep. “It is a precautionary measure,” said the source.


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Introducing our brand new packaging. Our treats now come in these stand up pouches with a resealable zipper top. They are a bit smaller in weight, but a lot smaller in price at a savings of almost $2 per bag. We’ve changed the name from I Smell Bacon to Mmm… Bacon, but don’t worry, we didn’t change the recipe, it’s the same tasty treat your dog’s loved all along.
Our dogs are just like us. They simply can’t resist the smell of sizzling, crackling bacon. Share one of your favorite breakfasts—bacon and eggs, of course—with your four-legged friend thanks to these delicious, crunchy cookies made with organic oat flour, cheese, and that classic breakfast combination. We value the health of our dogs, and know that your animal’s well being is vitally important to you, which is why we use only cage-free eggs and free-range meats. This is one treat that’s as humane and healthy as it is delicious!
Bag Size: 6.5 oz. (treat size 1.25″ – 1.75″)
Average of 45 treats per bag.
Ingredients: organic oat flour, organic brown rice flour, cheddar cheese, bacon and eggs.
Guaranteed Analysis: crude protein (min.) 19%, crude fat (min.) 18%, crude fiber (max.) 5%, moisture (max.) 6%
We only use cage-free eggs and free-range meats in our treats.

domain: food


text:
These adorable little pillows add a delightful dash of lavender scent to cupboards and drawers. Tuck them away and return to uplifting pockets of fragrance amidst your clothes, linens and anything else you wish to keep fresh.
- Presented as a tidy ribbon-wrapped trio
- Makes a splendid gift
- Filled with fragrant wooded beads that deliver long-lasting scent
The story of
Let the scent of England's favourite floral transport you to the purple fields and sun-dappled meadows of summer. Lavender, long renowned for its calming effects, is the perfect thing to lift your senses. Notes of sweet violet, sensual jasmine, tonka bean and musk delight and charm, whilst a whisper of lemon adds zest and energy. In short, the soothing days of summer, distilled.

domain: artistic


text:
Malayalam beauty Malavika Mohanan, who made heads turn with her fantastic performance in ‘Poongodi,’ turns up the heat with her photoshoots. Malavika made her debut in the Malayalam film industry with ‘Pattam Pole,’ released in 2013. She shot to fame with her performance in Oscar-nominated filmmaker Majid Majidi’s first India-centric project ‘Beyond the Clouds.’ So, let’s check out some of her glamorous pictures.
Malavika Mohanan is turning up the heat with her photoshoots.
She is a Malayalam beauty.
She amazes everyone with her performance in Poongodi.
Her fans love her in every way.
She is a complete stunner


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Foreign direct investment (“FDI”) within the European Community (“EU”) contributes to competitiveness, enhances employment and drives economic growth. It generates capital, encourages technological innovation and expertise and, significantly, also opens EU member states to the export of goods and services. The benefits of FDI can however, sometimes be neutralised by the risks which it could present to the security and public order of Members States and therefore, indirectly, to the EU as a whole.
EU Regulation 2019/452 (“the Regulation”) was introduced to establish a framework for the screening of foreign direct investment into the union. The main objective of the Regulation is to provide legal certainty amongst Member States which stand to benefit from FDI as to the risks which this may pose to security and public order, and to ensure that there is EU wide co-operation in tackling these risks.
The Regulation does not replace existing screening mechanisms within the EU but rather enhances their effectiveness. Whilst the Regulation is applicable to all Member States, Malta transposed its terms into Act LX of 2020, the ‘National Foreign Direct Investment Screening Office Act', Chapter 620 of the laws of Malta (“the Act”). The provisions of this Act extend to all foreign direct investments(“FDIs”) made or planned to be made within the jurisdiction of the Maltese islands and to all persons involved in foreign direct investment schemes, including those aiming to establish or maintain lasting and direct links for the pursuance of an economic activity in Malta. These investment schemes include investments which enable effective participation or control of a company carrying out an economic activity but exclude portfolio investments.
The Acts establishes the National Foreign Direct Investment Officer (“the Office”). Pursuant to the aims set forth under the Regulation, the Office is tasked with various duties and functions. These include, amongst other things, the setting up of mechanisms for the screening of FDIs in Malta which might affect the security or public order within the jurisdiction, as well as acting as a regulator and supervisory authority 1Article 9 (Act).
The Act imposes upon FDIs an obligation to notify the Office with information which is necessary for the proper execution of its functions under the Act, including but not limited to, whether factors mentioned under the schedule to the Act are carried out or sought to be carried out in the future, as well as information regarding the entity itself2. The Office is then given a five-day period to determine whether the investment is subject to screening or otherwise.
Should it transpire that the FDI is subject to screening, the cooperation mechanism is triggered. This mandatory mechanism ensures that security and public order is maintained, to the extent that Member States have a duty to notify the Commission and other Member States of any FDIs undergoing screening. Should the outcome of the cooperation mechanism conclude that the investment affects the security and public order of the EU, the Office may direct the investment to condition, prohibit or unwind such investment as the case may be 3Article 12 (7) Act. Whilst the final decision lies solely with the Member State where the investment is being sought, other Member States may raise their concerns on the matter.
It is worth noting that persons who fail to notify the Office, refuse to provide information in accordance to the notification procedure of this Act and/ or provide inaccurate, incorrect or incomplete information, may, depending on the nature of the breach, be subject to administrative penalties of up to €100,000. The hefty penalties that accompany these obligations should serve as a stern warning to investors and their advisors in Malta to familiarize themselves adequately with the provisions of this Act with a view to ensuring strict compliance therewith.
1 Article 9 (Act)
2 Article 12 (Act)
3 Article 12 (7) Act
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

domain: finance


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Adaptive multi-paddock grazing management’s influence on soil food web community structure for: increasing pasture forage production, soil organic carbon, and reducing soil respiration rates in southeastern USA ranches
- Academic Editor
- Alban Kuriqi
- Subject Areas
- Agricultural Science, Microbiology, Soil Science, Climate Change Biology, Environmental Impacts
- AMP grazing, Soil food web, Carbon sequestration, Soil fertility & health
- © 2022 Johnson et al.
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
- Cite this article
- 2022. Adaptive multi-paddock grazing management’s influence on soil food web community structure for: increasing pasture forage production, soil organic carbon, and reducing soil respiration rates in southeastern USA ranches. PeerJ 10:e13750 https://doi.org/10.7717/peerj.13750
Measurement of two grazing management’s influence on pasture productivity, soil food web structure, soil organic carbon and soil microbial respiration efficiency was conducted on five southeastern US, across-the-fence ranch pairs to compare adaptive multi-paddock grazing (AMP) management, using short grazing events with planned, adaptive recovery periods, to conventional grazing (CG) management, with continuous grazing at low stock density.
A point-in-time experimental field analysis was conducted to compare five AMP or CG ranch pairs to better understand the influence of grazing management on (a) standing crop biomass productivity; (b) soil food web community population, structure and functionality; (c) soil organic carbon accrual; and d) soil-C (CO2) respiration kinetics.
AMP grazing systems outperformed CG systems by generating: (a) 92.68 g m−2 more standing crop biomass (SCB), promoting 46% higher pasture photosynthetic capacity (Two sample Mann-Whitney; Z = 6.1836; no DF in MW; p = 6.26 × 10−10; Effect size = 0.35) (b) a strong positive linear relationship of SCB with fungal biomass (R = 0.9915; F(1,3) = 175.35; p = 0.015); fungal to bacterial (F:B) biomass ratio (R = 0.9616; F(1,3) = 36.75; p = 0.009) and a soil food web proxy (R = 0.9616; F(1,3) = 36.75; p = 0.009) and a concurrent very strong inverse relationship with bacteria biomass (R = −0.946; F(1,3) = 25.56; p = 0.015); (c) significant predator/prey interactions with an inverse relationship with bacterial population biomass (R = − 0.946; F(1,3) = 25.56; p = 0.015) and a positive relationship with total protozoa enumeration (R = 0.9826; F(1,3) = 83.68; p = 0.003) when compared to SCB; (d) a 19.52% reduction in soil C (CO2) respiration rates (Two sample t-test; T = −2.3581; DF = 52.3541; p = 0.0221; Effect size = 0.59); and (e) a 20.6% increase in soil organic carbon (SOC) in the top 10 cm of soil profile (Two sample Mann–Whitney; Z = 2.6507; no DF in MW; p = 0.008; Effect size = 0.24). Rancher conversion to AMP grazing strategies would appear to regenerate soil food web population, structure, diversity and biological functionality helping to improve: carbon flow into plant biomass, buildup of soil carbon, predator/prey nutrient cycling and soil microbial respiration efficiency while offering improved climate resilience and a strategy to increase the capture and storage of atmospheric CO2 in soils of the world’s rangeland.
This study reports on soil food web and vegetation interactions, under two grazing management strategies, an Adaptive Multipaddock (AMP) and a Continuous Grazing (CG) pasture management. It is part of a larger, multi-component southeastern USA study, focused on understanding the differences in the two management strategies. Research components and current published papers, and other components with publications pending, on this “systems” analysis are as follows: (1) soil carbon, nitrogen and water (Mosier et al., 2021), (2) greenhouse gas cycling (Gomez-Casanovas et al., 2021) (3) vegetation diversity and growth (Apfelbaum et al., 2022; Wang et al., 2021), (4) arthropod populations (Schmid, Welch & Lundgren, 2021), (5) grassland bird populations, (6) livestock well-being, (7) farmer well-being, (8) life-cycle cost assessment, (9) ecosystem modeling, and (10) production of documentary films https://www.carboncowboys.org/ (in progress) reporting on research results.
Grazing ecosystem soils and biotic communities coevolved with herbaceous vegetation, grazer insects and other herbivores over the last 40 million years, contributing to the expansion of carbon-rich soils in semiarid to semi-humid grassland regions that cover approximately 40% of the earth’s land area (Frank, McNaughton & Tracy, 1998; Retallack, 2013). The replacement of free-ranging wild herbivores, with fenced-in livestock, has contributed to degradation of vegetation and soils, declines in productivity and biodiversity, and a reduction in ecosystem resilience, resulting in an overall decline in historic ecosystem services generated through evolved grazer/grassland relationships (West, 1993; Milchunas & Lauenroth, 1993; Knopf, 1994; Frank, McNaughton & Tracy, 1998; Peterson, Allen & Holling, 1998).
To ensure sustainability and resilience, grazed ecosystems should be managed using grazing management that avoids overstocking and overgrazing (Teague, 2018). Conventional grazing management allows grazing animals unrestricted access in large fenced pastures, leading to degradation of soil and plant function due to patch-selective overgrazing and stocking with no planned recovery from grazing at stocking rates in excess of carrying capacity (Teague, 2018). Soil function is also diminished by the application of inorganic fertilizers, herbicides, pesticides, and parasiticides (Bardgett & McAlister, 1999; Leake et al., 2004; de Vries et al., 2006; Birkhofer et al., 2008; LaCanne & Lundgren, 2018). As an alternative, adaptive multi-paddock (AMP) grazing is a regenerative management option that has proven to be more productive, give greater economic returns and more abundant ecosystem services by improving biological function (Teague et al., 2013; Jakoby et al., 2014; Jakoby et al., 2015; Teague & Kreuter, 2020).
AMP emulates ecosystem processes that evolved in response to intense but periodic herbivory by large herds of ungulate grazers that included post grazing recovery (Frank, McNaughton & Tracy, 1998; Retallack, 2013) and has been documented to avoid and reverse the damage caused by continuous grazing in a timely and cost-effective manner (Gerrish, 2004; Teague et al., 2011; Teague et al., 2013; Wang, Teague & Park, 2016). AMP grazing uses a management decision process, responding to weather and forage variability, to avoid overstocking of, and overgrazing by livestock in an adaptive manner (Jakoby et al., 2014; Jakoby et al., 2015; Teague, Grant & Wang, 2015; Wang et al., 2018). The grazing benefits are achieved by adaptively adjusting grazing frequency and duration on available forage resources, using short, but intense grazing intervals, allowing livestock to graze ∼40% of available SCB. The remaining ∼60% of plant residue provides photosynthetic surface area to aid plant regrowth and/or be trampled onto the soil surface through short-term hoof-impact of the grazing herd. The trampled plant residue provides soil cover, reduces surface water runoff and erosion and provides above and below ground plant biomass to support microbial activity (Thurow, 1991; Dowhower et al., 2019; Teague & Kreuter, 2020). Appropriate length recovery periods promote more efficient recovery of plant communities, the soil food web and ecosystem restoration. Most AMP ranchers find this grazing strategy allows them to avoid application of inputs that may compromise soil biotic function, such as synthetic fertilizers, herbicides and pesticides. In combination, these actions result in light to moderate grazing impact on herbaceous plants, the soil food web, and the ecological functions they perform (Teague et al., 2013; Jakoby et al., 2014; Dowhower et al., 2019; Teague & Kreuter, 2020).
Mixed-study results from grazing researchers have concluded that no improvements in ecological and livestock indicators occurred under rotational grazing when compared to continuous grazing (e.g., Briske et al., 2008). However, these conclusions have been criticized for their relatively long periods of grazing and short recovery periods, as well as the short-term and small-scale and fixed rather than adaptively managed research frameworks (Teague et al., 2013; Gosnell, Grimm & Goldstein, 2019; Gosnell, Charnley & Stanley, 2020; Teague & Kreuter, 2020). Other studies provide evidence that rotational grazing, with fewer paddocks per herd, more extended grazing periods, and shorter recovery periods, can result in limited plant and animal production advantages compared to continuous set-stocking at low stocking rates (Briske et al., 2008; Teague et al., 2013; Wang et al., 2022). Low stocking rates and improperly applied rotational grazing strategies do not facilitate degraded resource recovery or provide adequate economic returns over time (Jakoby et al., 2014; Jakoby et al., 2015; Teague & Kreuter, 2020). CG set-stocked at low stocking levels implementing long periods of grazing, paired with inadequate recovery, set-stocking rates, and low levels of soil surface forage residue promote a compounding of negative effects on ecological function and economic returns as illustrated by Augustine et al. (2020).
Intensification of agricultural production has promoted management practices that have reduced soil carbon and the biomass and diversity of soil microbiota (Stoate et al., 2001; Postma-Blaauw et al., 2010) including shifts to more bacterial-dominated microbial communities with increased soil nitrogen use (de Vries et al., 2006), and reduced soil carbon stocks and accrual rates (Six et al., 2006). Soil microbes are instrumental in C and N cycling; however, microbial biomass and activity are strongly influenced by higher trophic-level organisms of the soil food web. The upper trophic-level organisms (protozoa and nematodes) consume soil microbiota and stimulate microbial turnover through “grazing” of lower trophic level organisms (Postma-Blaauw et al., 2005) providing nutrient mineralization processes that promote plant productivity (Setälä & Huhta, 1991).
Soil organic matter (SOM), and the carbon and nutrients it contains, are key components for supporting fundamental bio-geochemical processes for: plant carbon assimilation and growth; soil respiration; and carbon-climate feedbacks (Kallenbach, Frey & Grandy, 2016). Soil food web population, structure, diversity, and biological functionality facilitate these bio-geochemical processes and contribute substantially to: nutrient generation, nutrient cycling, nutrient capture, soil fertility development, and SOM formation and turnover (Schloter, Dilly & Munch, 2003; Van der Heijden, Bardgett & Van Straalen, 2008; Murray et al., 2009; García-Orenes et al., 2013). A shift towards fungal dominance in the soil food web has been observed to enhance C accumulation and reduce SOM turnover rates (Six et al., 2006). More efficient microbial biomass production and the accumulation of SOM are now considered to be driven by distinct soil food web structures, where microbial-derived SOM is greatest in soils that contain higher fungal abundances (Kallenbach, Frey & Grandy, 2016; Johnson, 2017).
Predicting the effects of soil food web physiological regulation on soil C processes and their interaction with plants and livestock management, is critical if we are to improve the performance of our agroecosystems, project future global warming offset potentials, and enhance atmospheric CO2 reduction (Billings & Ballantyne, 2013). Despite this expectation, many studies have concluded there is no direct evidence that soil fungal-to-bacterial ratios (F:B) characterize the turnover of soil organic matter (Rousk & Frey, 2015), soil nutrient content or growth of vegetation (Wong et al., 2015), or that fungi are capable of enhancing soil carbon storage mechanisms (Thiet, Freya & Six, 2006; Johnson, 2017).
The influence of AMP grazing management on: in-situ field measurements for the soil food web population, structure, diversity and metabolic functionality, and the soil food web’s influence on standing crop biomass (SCB) production, soil organic carbon stocks (SOC) and soil microbial respiration efficiency is not well documented. The experimental hypothesis in this research is that AMP grazing methodologies will promote beneficial changes in soil food web population and structural composition (bacterial and fungal biomass, F:B ratio, and protozoa enumeration) and function, and that these shifts in the soil food web population structure will positively influence grazing system photosynthetic capacity, soil microbial respiration efficiency and the storage of carbon in AMP grazed rangeland soils when compared to CG systems. In this paper we evaluate the effects of two grazing management strategies on soil food web system functions and vegetation interactions measuring:
early season standing crop biomass production (g dry biomass m−2);
soil food web biomass (µg g−1 dry soil) for bacteria, actinobacteria, fungi; and population enumeration for total protozoa- (flagellates, ciliates, amoeba) (number g−1 dry soil);
a fungal-to-bacterial (F:B) structural biomass ratio;
a soil food web proxy (summation of all normalized soil food web constituents);
soil organic carbon (SOC%); and,
in-situ, diurnal soil CO2 respiration kinetics (g C m−2 day−1) of the soil food web,
in an effort to ascertain what can be learned about the soil food web’s contribution to the larger research team question: Can Adaptive Multi-Paddock (AMP) grazing contribute to sequestering carbon in soils and improve delivery of ecosystem services and socio-ecological resilience in grazing ecosystems?
Materials & Methods
Site screening, selection and soil type
A list of potential AMP and CG grazing partners was obtained from the Natural Resources Conservation Service (NRCS) technical staff, grazing consultants and organizers, in each of four states (Mississippi, Alabama, Tennessee and Kentucky) included in this study (Table 1). Potential candidates were invited to participate in an online survey to help in the selection of suitable paired ranches to conduct an across-the-fence comparison of adjacent AMP grazed and well-managed CG paired neighbors. Preliminary scouting was conducted on the prospective paired-ranches to confirm that each ranch pair had: (1) the same soil types, to reduce the potential that variable soil types may have on primary productivity, (2) similar topography, and (3) land use history with the primary deviation being the conversion of a former CG managed ranch to AMP grazing management that had been in AMP management for a minimum of one decade (Table 1, Table S1). Scouting included both soil typing using NRCS Soil Survey website (https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx) and pre-selection field soil core sampling and analysis to confirm accuracy.
|Farm pair||Grazing practice||Total 2018 annual net primary productivity (g m−2)||Average animal units carried (AU ha−1)||Livestock in study area||Average paddock size (ha)||Average # of paddocks per herd||Graze period goal (days)||Recovery goal (days)||Rest vs. graze period (ratio)||Years of current management||Land use history|
|Statistical significance pooled (AMP vs. CG)||p = 0.3981||p = 0.011||p = 0.00025||p = 0.036||p = 0.0106||p = 0.9161||p = 0.01193||p = 0.3308|
|Pair 1||AMP||1696||1.53||Beef, Sheep||1.2||45||2||45||22.5||13||Tobacco, grain, then grazing >30 years|
|CG||1108||0.79||Beef Cattle||14||1||365||0||0||6||Tobacco and grain crops|
|Pair 2||AMP||892||2.57||Beef Cattle||1||45||2||90||45||12||Row Crops, Hay and Grazing|
|CG||959||0.82||Beef Cattle||11||8||135||82.5||0.6||>25||Row Crops, Hay and Grazing|
|Pair 3||AMP||1119||1.55||Beef Cattle||1.2||60||1||50||50||29||Small Grains|
|CG||1017||0.82||Beef Cattle||16||50||15||82.5||5.5||17||Small Grains|
|Pair 4||AMP||733||2.75||Beef Cattle||0.4||135||1||80||80||24||Cotton|
|Pair 5||AMP||924||1.04||Beef Cattle||1.6||150||1||70||70||10||Tobacco, grain the grazing >50 years|
|CG||891||0.82||Beef Cattle||13||7||75||90||1.2||>40||Tobacco, cotton, market garden & grains|
Research area precipitation
Regional precipitation records, for the 6 months (January 2018–June 2018) prior to field sampling were obtained through NOAA’s Advanced Hydrological Prediction Service online data site (https://water.weather.gov/precip/). Heatmap images were obtained for the monthly percent-of-normal and April and May departure-from-normal precipitation maps for the Southeastern US corridor to confirm uniformity of precipitation events on research ranch pairs to verify similar growing conditions for assessing accurate SCB growth potential (Fig. S1).
Soil organic carbon analyses
Soil sample cores for SOC analyses were collected as described in USDA/NRCS Soil Survey Laboratory Methods Manual (Burt, 2004) specifically, harvested in a three-week sampling period, between the last two weeks of May 2018 to the first week of June 2018. Ten catenas were located on the five AMP/CG ranch pairs. Twelve soil core samples were taken, at evenly spaced locations, across each of three pre-determined linear transects within each catena (sloped or flat), having rectangular dimensions of ∼100 m by ∼50 m (120 total soil core samples). The soil cores for SOC analyses were comprised of a soil core four cm in diameter and 10 cm deep taken at each sample site (12 sites at each AMP and CG farm), placed in 1-quart plastic bags and shipped to Ward Laboratory Inc., (4007 Cherry Ave, Kearney, NE 68847) for SOC (%) carbon analysis (LECO, dry combustion). Laboratory testing included a preliminary acidification treatment to remove soil carbonate content and provide an accurate SOC (%) assessment. Each of the sample cores were sampled in triplicate to insure SOC (%) sampling accuracy.
Standing crop biomass (SCB)
Standing crop biomass was assessed (g dry biomass m−2) by clipping living/standing plant biomass 2.54 cm above ground height, assessing from 15–20 individual quadrats (quadrat = 1,000 cm2) taken inside multiple fenced livestock-exclusion areas, in each catena, on AMP and CG pastures. All plant materials were paper bagged, oven dried and weighed for dry biomass. The sample sites (sloped or flat) corresponded with the microbiological sampling sites for each ranch pair (Table S1) for the January to early June pasture forage growth period in each treatment plot. Each sample site was harvested, in a three-week sampling period, between the last two weeks of May 2018 to the first week of June 2018 corresponding with the sample timing for all microbiological and respiration metrics.
Soil food web analyses
Soil samples for soil food web analyses were collected as recommended by Earthfort (https://earthfort.com/wp-content/uploads/2021/08/Sample-Instructions-Combined_81221.pdf), specifically sampling at each location from a soil core four cm in diameter and 10 cm deep of the soil profile (n = 12 for each ranch). These samples were immediately placed on ice and mailed overnight to Environment Celebration Institute Inc., (Berry Creek, CA, USA) for soil food web analyses to quantify soil food web biomass (µg g−1 dry soil) for bacteria, actinobacteria, fungi; and in number of organisms gram−1 of dry soil for: total protozoa (flagellates, ciliates and amoeba) and nematodes. This data provided microbial biomass data to determine a structural fungal and bacterial biomass ratio (F:B) and a predator/prey assessment of the different trophic levels. Sample preparation and biomass quantification implemented direct observation microscopy (visible light, differential interference contrast) and other methodologies (Ingham, 1995; Ekelund, 1998; Stamatiadis, Doran & Ingham, 1990).
A soil-food web proxy, for each of the ranch pairs, was assessed as a composite summation of all normalized soil food web measurements for each sampled ranch catena, offering an internal, normalized full soil food web metric to compare aggregate soil food web population dynamics between ranches.
Soil CO2 respiration rates
Soil-respiration C (g C m−2 day−1) was measured with in-situ static alkali reactors (Gupta & Singh, 1981), using a 50 mL plastic centrifuge tube, containing 15 mL of standardized 1 M KOH, with a cross-sectional area of about 25% of soil surface sampled. Diurnal soil respiration measurements were conducted for the 24-hour period prior to, and at the identical location that soil samples were taken to assess SOC and the soil food web. Reactors were covered with a ∼1-liter glass cover (canning jar) screwed into the soil profile approximately two cm deep. Prior to placing the jar over the 50 ml centrifuge tube, all vegetation was removed from the surface for accurate evaluation of CO2 respired from the soil. Reactors measured soil CO2 emissions, over a diurnal time period, remaining in the field for 24 h (starting times and ending times were recorded to assess total time to 1-minute accuracy). After the 24-hour period, the 50 ml tubes were then removed from the reactors, capped, and taken to a laboratory for quantification of CO2 absorption by the 1 M KOH solution. A non-destructive analysis technique was implemented assessing reduction in reactor KOH solution conductivity as correlated to the quantity of CO2 absorbed, as described in Methodology S1. Respiration results were expressed in g C m−2 day−1. A small number of static-alkali reactors were disturbed by grazing livestock resulting in a different quantity of “n” comparisons.
The static alkali reactor methodology was chosen to insure identical atmospheric conditions (temperature, solar insolation, etc.) and field moisture conditions for simultaneous side-by-side same-day comparison of all 12 sampling locations for each AMP and CG farm.
Univariate statistical analyses were used to test differences in means between paired and pooled measurements of AMP and CG treatments for: soil organic carbon percent (SOC%), standing crop biomass (SCB) (g dry biomass m−2), soil food web (µg g−1 dry soil and microorganism counts g−1 dry soil), and soil-respiration C (g C m−2 day−1), in the five ranch pairs. Statistical data analysis was conducted with Statistics Kingdom 2017 (https://www.statskingdom.com/). All data components were initially examined for normal distribution with Shapiro–Wilk (if n < 50) and/or Shapiro-Francia, and Anderson-Darling (if n > 50); F-tests were used to determine data variance. Means testing methodologies were selected based on the equality of variances and normality of data. Pairwise means comparisons were conducted with Two sample t-test (Welch’s T-test) if data had a normal distribution and equal variances and a Mann Whitney U test (Wilcoxon rank-sum) means tests was implemented if data was not distributed normally, had unequal variances or outliers. Simple linear regression analyses were conducted to test the fit of a linear model to the data. Means results are reported as mean values, ± standard error (mean ± SE), and a significance value α ≤ 0.05 threshold was used to determine statistical significance. Soil food web proxy measurements involved multiple data types (µg microbial biomass g−1 dry soil) and entity data counts (number of microbes g−1 dry soil) requiring normalization to permit data to be interrogated as a soil food web proxy, using a “universal data sub-language” (Codd, 1970).
Ranch pair selection and antecedent precipitation
The grazing-methodology adoption period in these ranch pairs ranged from 10 to 29 years in the AMP ranches (average 17.6 years) and from 6 years to 40 years in the CG ranches (average 25.6 years) providing no significant difference in years of management between AMP and CG ranches (Two sample t-test; T = −1.052996; DF = 6.3342; p = 0.3308; Effect size = 0.67) (Table 1). Total 2018 annual net primary productivity (g dry biomass m−2) and recovery goal (days) demonstrated no significant difference (Two sample t-test; T = 0.9018; DF = 6.7518; p = 0.3981; Effect size = 0.57) (Two sample Mann–Whitney; Z = −0.1054; no DF in MW; p = 0.9161; Effect size = 0.033) respectively (Table 1). A statistical analysis of the grazing management practices indicated significant differences between AMP vs. CG grazing management in: Average Animal Units (AU acre−1) (Two sample Mann–Whitney; Z = 2.5377; no DF in MW; p = 0.011; Effect size 0.8); Average Paddock Size (ha), (Two-sample t-test; T = −10.8336; DF = 4.3721; p = 0.00025; Effect size = 6.85); Average Number of Paddocks per Herd, (Two sample Mann–Whitney; Z = 2.0953; no DF in MW; p = 0.036; Effect size = 0.66); Graze Period Goal (days), (Two sample Mann–Whitney; Z = −2.5536; no DF in MW; p = 0.01066; Effect size = 0.81) and Rest vs. Graze Period (ratio), (Two sample Mann–Whitney; Z = 23.5143; no DF in MW; p = 0.01193; Effect size = 0.8) (Table 1), supporting the validity of the AMP vs. CG ranch-pair management selection criteria in this research project.
Precipitation maps, of the AMP/CG ranch locations (Fig. S1), available at https://water.weather.gov/precip/, indicated similar antecedent precipitation prior to the May-June sampling event, reducing the potential impact of differing rainfall amounts on ranching system SCB production. Monthly Percent-of-Normal rainfall, for January–June of 2018 and Departure-from-Normal rainfall, for April to May 2018 precipitation maps (Fig. S1) indicate that precipitation amounts supplied the historical monthly average rainfall or better at each sampling site, to ensure comparable precipitation quantities were available at each research site to support equivalent growth potential of SCB on ranch pairs.
Data from one-meter core samples, taken at the CG, and AMP area locations, on the same day by other researchers on this project, concurrent with the timing and location of microbiological sampling, supported sufficient soil water content for accurate soil carbon respiration and the soil bulk density assessment. The analysis of the core samples relayed the average soil moisture content on the AMP, and CG sites was ∼17.56% ± 1.1%. Soil bulk density averaged 1.21 g cm−3 ± 0.03 g cm−3 in the top ten centimeters of both AMP and CG soil profiles (Mosier et al., 2021).
Soil organic carbon
Soil organic carbon percentages, SOC (%), from AMP management strategies were significantly greater when compared to CG ranches in three of the five pairwise comparisons: AMP-3/CG-3, (Two sample t-test; T = 6.3614; DF = 20.99; p = 2.62 ×10−6; Effect size = 2.6); AMP-4/CG-4, (Two sample Mann–Whitney; Z = 2.3393; no DF in MW; p = 0.0193; Effect size= 0.48); and AMP-5/CG-5, (Two sample t-test; T = 6.1855; DF = 21.5438 ; p = 3.474 ×10−6; Effect size = 2.52) (Table 2). There was no significant difference of SOC (%) in AMP-1/CG-1 and AMP-2/CG-2.
|Pairwise comparison||Standing crop biomass (g dry biomass 0.1 m2)||Soil organic carbon (%)||Respiration (g C m−2 day−1)|
|AMP-1||241.7 ± 18.6||NS||2.59 ± 0.11||NS||2.477 ± 0.151||NS|
|CG-1||212.1 ± 15.1||2.97 ± 0.17||2.798 ± 0.302|
|AMP-2||216.9 ± 24.0||p = .0011||2.44 ± 0.12||NS||N/A|
|CG-2||362.3 ± 31.2||2.35 ± 0.10|
|AMP-3||380.6 ± 24.2||p = 0.0011||2.28 ± 0.10||p = 2.62×10−6||1.408 ± 0.210||p = 0.017|
|CG-3||95.5 ± 6.0||1.49 ± 0.08||2.135 ± 0.141|
|AMP-4||293.2 ± 29.0||p = 2.1× 10−6||2.39 ± 0.17||p = 0.0193||2.623 ± 0.223||NS|
|CG-4||122.0 ± 5.9||1.87 ± 0.08||1.855 ± 0.281|
|AMP-5||350.0 ± 20.8||p = 2.007 × 10−6||4.49 ± 0.17||p = 3.47 × 10−6||2.453 ± 0.197||p = 0.0023|
|CG-5||215.5 ± 14.1||3.08 ± 0.15||3.889 ± 0.323|
|Pooled comparison||Standing crop biomass (g dry biomass m2)||Soil organic carbon (%)||Respiration(g C m−2 day−1)|
|AMP||294.14 ± 11.4326||p = 6.26 × 10−10||2.83817 ± 0.12328||p = 0.008||2.2372 ± 0.1312||p = 0.0221|
|CG||201.45 ± 10.774||2.35418 ± 0.09524||2.7799 ± 0.1891|
No Statistical Significance
data not available
Pooled AMP soil organic carbon exhibited mean cumulative ranch SOC (%) of 2.83 ± 0.123%C, or 21% greater than mean cumulative CG SOC (%) of 2.354 ± 0.09%C (Two sample Mann–Whitney; Z = 2.6507; no DF in MW; p = 0.008; Effect size = 0.24) (Table 2).
Standing crop biomass (SCB)
Pairwise comparisons of standing crop biomass (SCB) were significantly greater in AMP systems in three of the five pairwise comparisons AMP-3/CG-3, (Two sample t-test Mann–Whitney; Z = −3.2627; no DF in MW; p = 0.0011; Effect size = 0.42); AMP-4/CG-4, (Two sample t-test; DF = 31.4136; T = −5.7858p = 2.1 ×10−6; Effect size = 1.49) and AMP-5/CG-5, (Two sample t-test; T = 5.31036; DF = 51.0642; p = 2.007 ×10−6; Effect size = 1.38) (Table 2); and reversed in the AMP-2/CG-2 comparison (Two sample Mann–Whitney; Z = −3.2627; no DF in MW; p = 0.0011; Effect size = 0.42) and not statistically significant in the AMP-1/CG-1 ranch pair.
AMP management strategies exhibited a pooled SCB mean of 294.1 ± 11.43 g dry biomass m−2, ∼92.7 g dry biomass or ∼46% more SCB than pooled CG systems SCB mean of 201.5 ± 10.74 g dry biomass m−2 (Two sample Mann–Whitney; Z = 6.1836; no DF in MW; p = 6.26 ×10−10; Effect size = 0.35) (Table 2).
Soil food web
Pairwise comparisons of AMP and CG soil food web analyses provided only one farm pair, AMP-3/CG-3, that demonstrated statistically significant differences in the means of soil food web- bacteria, (Two sample t-test; T = −2.8435; DF = 16.003; p = 0.0117; Effect size = 1.16); F:B ratio, (Two sample Mann–Whitney; Z = 2.1096; no DF in MW; p = 0.03489; Effect size = 0.43); soil food web proxy, (Two sample Mann–Whitney; Z = 2.5094; no DF in MW; p = 0.01209; Effect size = 0.5); and protozoa enumeration, (Two sample Mann–Whitney; Z = 2.4858; no DF in MW: p = 0.01292; Effect size = 0.51) (Table S2).
Pooled comparison of AMP and CG systems indicated a significant difference in the means of the bacterial population (Two sample Mann–Whitney; Z = −2.1766; no Df in MW; p = 0.02951; Effect size = 0.2) and protozoa enumeration (Two sample Mann–Whitney; Z = 2.3522; no DF in MW; p = 0.01866; Effect size = 0.21) (Table S2) but no statistically significant differences were observed in fungi, F:B ratio or soil foodweb proxy.
Simple linear regression analyses of mean AMP soil food web variables with SCB provided very strong direct relationships with fungal biomass, (R = 0.9915; F(1,3) = 175.35; p = 0.015); F:B ratio (R = 0.9371; F(1,3) = 21.56; p = 0.019); and soil food web proxy (R = 0.9616; F(1,3) = 36.75; p = 0.009) (Figs. 1B–1D), and a very strong inverse relationship with bacterial biomass (R = −0.946; F(1,3) = 25.56; p = 0.015) (Fig. 1A).
Simple linear regression analyses of CG soil food web variables with SCB for bacteria biomass, fungal biomass, F:B ratio and soil food web proxy were not statistically significant; (R = −0.3061, F(1,3) = 0.31, p = 0.6165); (R = −0.6605, F(1,3) = 2.32, p = 0.225); (R = −0. 2386; F(1,3) = 0.18, p = 0.6691); (R = 0.02491, F(1,3) = 0.00016, p = .991) respectively (Figs. 1B–1D) (trendlines not shown).
Predator/prey relationships, comparing protozoa populations (# g−1 dry soil) and bacteria biomass (µg g−1 dry soil) with standing crop biomass in AMP systems, provided a very strong positive relationship to total protozoa (R = 0.9826; F(1,3) = 83.68; p = 0.003), and a strong inverse relationship to bacterial biomass (R = −0.946; F(1,3) = 25.56; p = 0.015) (Fig. 2A); where CG systems provided no significant comparisons (Fig. 2B).
Pairwise comparisons of AMP and CG soil respiration provided two farm pairs, AMP-3/CG-3 (Two sample t-test; T = −2.8734; DF = 9.4854; p = 0.01744; Effect size = 1.54) and AMP-5, CG-5 (Two sample t-test; T = −3.797; DF = 12.7065; p = 0.0023; Effect size = 1.78) that demonstrated statistically significant differences in respiration (Table 2).
Pooled AMP management soil carbon respiration exhibited 19.52% less mean cumulative soil respiration (2.237 ± 0.131 g C m−2 day−1) when compared to CG soil respiration (2.779 ± 0.1890 g C m−2 day−1) (Two sample t-test; T = −2.3581; DF = 52.3541; p = 0.0221; Effect size = 0.59) (Table 2). Carbon dioxide flux towers have been installed by associated researchers on this project and are currently tracking soil respiration on two of the farm pairs AMP-4/CG-4 and AMP-5/CG-5. Data is still being collected but their initial data is also observing a commensurate ∼20% reduction in soil C (CO2) respiration comparing AMP to CG management (R. Clement, 2022, Pers. Comm.).
Documentation of the influence that AMP and CG management systems have on soil food web population and structure in grazing lands is scarce. This research focused on evaluating AMP and CG grazing management’s impact on soil food web population and structure and their effect on, (1) system standing crop biomass production or photosynthetic capacity, (2) SOC carbon accrual and (3) soil CO2 respiration on grazing lands.
Detailed understanding of the soil food web relationship to ecosystem function has often proven to be complicated, as have the development of methods to accurately assess soil food web structure. Much of this difficulty is due to our inability to make accurate direct observations, such as the technical challenges of measuring in situ activities, and the high diversity and/or spatial heterogeneity of the soil food web and soil environment (Barns, Takala & Kuske, 1999; Torsvik, Ovreas & Thingstad, 2002; Strickland & Rousk, 2010; Malik et al., 2016; Johnson, 2017).
This point-in-time research approach attempts to address the many challenges long-term research projects encounter i.e., multi-year, multiple sampling events, unpredictable weather conditions, participant buy-in, commitment and financial stability, adherence to prescribed practices, and duration of experiment. In addition to these challenges are the logistics of finding multiple adjacent ranches that have been practicing AMP and CG grazing for a minimum of one decade along with the significant financial investment and multi-year commitment by researchers, funders and land-owners. A point-in-time research approach can be a timely and cost-effective approach to garner the necessary data to determine the impact and/or efficacy of AMP and CG management practices on rangeland health and rancher productivity. Point-in-time research may also offer preliminary data or logistical design components that may benefit planning of long-term research opportunities. If ranchers and policymakers need critical data to influence their decisions towards adoption of AMP or CG management, then a point-in-time research project may be the best path forward to achieve those agendas in a timely manner.
Standing crop biomass is a keystone metric for determining soil fertility and productivity of AMP and CG management systems. Pairwise comparisons of AMP and CG farm pairs for the individual measurements of SCB, SOC (%), multiple soil food web components and soil respiration revealed very few clues for differentiating management practices, as results fluctuated and varied as related to the paired research farms (Table 2, Table S2). However; when the soil food web components were placed in the context of standing crop biomass productivity, simple linear regression analyses of the variables measured in pooled comparisons of AMP and CG management provided significant insight into the impact that soil food web structures have in AMP grazing for improving SCB, promoting SOC (%) increases and reducing soil C (CO2) respiration.
Extensive sampling (n = 12) of the soil food web components, at each participating AMP and CG farm, helped buffer the inherent heterogeneity of the soil food web matrix and provide valid comparisons with which to assess the influence of each soil food web component singularly and collectively. Direct pairwise comparisons of soil food web data between AMP and CG managed grazing offered little information for defining differences in grazing management systems, except in the AMP-3/CG-3 ranch pair. Soil food web components, bacteria, F:B ratio, soil food web proxy and total protozoa all demonstrated statistically significant differences between AMP and CG management in the AMP-3/CG-3 ranch pair. Of all the AMP/CG ranch pairs the AMP-3/CG-3 ranch comparison demonstrated the most dramatic contrast of management outcomes for pasture health and productivity when applying visual field observations, The AMP-3 ranch had the highest SCB and the lowest soil respiration of all ranches and it has the potential to provide a view to the future for the benefits that could be achieved as it had the longest period of the adoption of AMP practices when compared to all other AMP systems.
Comparisons of AMP and CG soil food web variables to standing crop biomass, were the most informative as they revealed very strong positive linear correlations of AMP systems increase in SCB to fungal biomass, F:B ratio, and a soil food web proxy while demonstrating very strong inverse relationships to bacterial biomass (Fig. 1). AMP-grazing measured variables correlated extremely well with SCB but CG systems demonstrated a complete lack of functional correlation (Fig. 1). The application of the soil food web analyses, as a potentially reliable metric of soil health in AMP farms, demonstrated good potential to resolve soil health and be predictive of SCB; however, no similar relationships were evident on CG farms. This may help explain the observations, by some researchers, relying on soil food web or soil fungal-to-bacterial ratios (F:B) to be predictive of: (a) the turnover of soil organic matter (Rousk & Frey, 2015), (b) growth of vegetation (Wong et al., 2015), or (c) enhancement of carbon storage in soils that have a more fungal dominant soil food web (Thiet, Freya & Six, 2006).
The question arises why do the soil microbiomes in AMP systems demonstrate strong correlations with SCB, and offer little statistically significant correlations in CG systems? There are likely several potential mechanisms, working singularly or collectively, that might help explain why the soil food web components in AMP systems correlated so well with SCB. Primary of these would be energy influx (de Vries et al., 2013), followed by nutrient availability, (Estrela et al., 2022), plant litter deposition (Heijboer et al., 2018), succession of microbial groups during the decomposition of litter (Keeley, 1987), nutrient deficiency-initiated dormancy (Cohen, 1966), the application of synthetic fertilizers, herbicides and pesticides (Birkhofer et al., 2008), and the development of predator/prey relationships in the soil food web (Brose et al., 2019).
Energy flow and directionality through a soil ecosystem is determined by the structure of the soil food web and its community of microorganisms (de Vries et al., 2013). The microbiome in soil systems represent multiple species of microorganisms operating as a complex self-organizing system demonstrating a certain level of species stability promoting processes involving conversion of energy substrates and conservation (Verstraete, 2015). Soil bacteria and fungi self-assemble into dynamic co-evolving communities, promoting complex interactions, ranging from antagonism to mutualisms, to compete or cooperate for the acquisition of nutrients driving ecosystem functions that are important for plant and animal health (Deveau et al., 2018).
Research indicates that nutrient availability governs microbial community level function and taxonomic structure (Estrela et al., 2022). Energy influx into a regime that has limited resources promotes a “unidirectional flow of energy” that is converted through the consumption and production of secondary-metabolites in an orderly succession promoting microbiome structures that utilize energy resources in a linear succession with each microorganism in that sequence having limited nutrient utilization capabilities (Marsland III et al., 2019). In contrast, a regime with a higher energy influx develops a qualitatively different structure providing simultaneous energy influxes into multiple entry points and feedback loops where community members utilize multiple energy resources with the incoming flux spread evenly over a community offering a more diverse and stable microbiome (Marsland III et al., 2019).
AMP systems demonstrated 46% more energy influx as an increase in forage productivity, when compared to CG systems, providing more total energy resource input for the grazing system. AMP systems also promoted the increase in available nutrients and energy by leaving 60% of standing crop biomass in the field as either trampled biomass (plant litter) or photosynthetically active plant material. CG systems management protocols offer limited and periodic access of standing crop biomass as a nutrient and energy substrate for the soil microbiome due to grazing protocols that remove grass down to the soil surface, requiring more time to rebuild plant structure and photosynthetic capacity while also negating the buildup of any significant soil-surface plant residue to supply energy and nutrients to support soil microbiome maintenance and function.
Research indicates that a succession of microbial groups occurs during the decomposition of litter. It was observed that 13C-labeled litter is first partitioned into fungal biomass with follow up partitioning into gram-negative bacteria, gram-positive bacteria, actinomycetes and micro-fauna (Heijboer et al., 2018). This successional partitioning of 13C into fungal biomass could help explain the differences observed between the soil microbial community structure and its correlation to SCB in AMP and not in CG grazing.
Another potential component that could affect AMP and CG soil foodweb structures is dormancy. Random or variable nutrient resource availability can determine when organisms enter or exit periods of reduced metabolic activity or dormancy (Keeley, 1987). AMP grazing protocols provide a more consistent nutrient resource by leaving ∼60% standing crop biomass in the field to feed the resident soil microbiomes where CG systems are more prone to a lack of nutrient resource availability, for the soil food web, due to removal of large percentages of plant biomass and little soil-surface residue buildup. Dormancy is only beneficial if the dormant organism does not deplete its energy reserves or avoids predation during the period that organism is dormant (Cohen, 1966). If there is a survival issue then dormancy could be another driver that promoted changes in soil food web structure and the lack of correlation of CG system’s soil food web structure with SCB.
Soil function has also been observed to diminish from the application of inorganic fertilizers, herbicides, pesticides, and parasiticides (Bardgett & McAlister, 1999; Leake et al., 2004; de Vries et al., 2006; Birkhofer et al., 2008; LaCanne & Lundgren, 2018) and application of these amendments is prominent in the CG managed ranches. Any or all of these interactions, listed above, acting singularly, collectively or interactively, could help explain the dysbiosis of the soil food web in CG managed systems but determination of which component(s) are responsible is beyond the scope of this research design.
It has been observed that high predator–prey (mass) may help stabilize communities and maintain ecosystem function (Brose, Archambault & Barnes, 2019). Pooled comparisons of bacterial biomass and protozoa enumeration with SCB revealed the importance of predator/prey interactions for their potential to liberate nutrients to facilitate plant growth (Fig. 2). The potential for improved nutrient cycling to increase SCB was very predictive in AMP systems when comparing bacterial biomass (µg gm−1 dry soil) and total protozoan counts (number gm−1 dry soil) with SCB productivity (Fig. 2A). There were very strong correlations of increases in SCB productivity as bacterial biomass decreased and total protozoan numbers increased, potentially indicating protozoa feeding on the bacterial community was promoting nutrient cycling. This predator/prey relationship was active in AMP management systems (Fig. 2A) but appeared disassociated when compared to CG management systems (Fig. 2B). Bacterial populations in AMP systems were less than 6,000 µg gm−1 dry soil where CG systems ranged as high as 10,000 µg gm−1 dry soil. Total protozoan counts exceeded 14,000 protozoa gm−1 dry soil in AMP systems and never exceeded 5,500 protozoa gm−1 dry soil in CG systems. CG systems demonstrated no significant predator/prey correlations when comparing bacteria biomass and total protozoan counts to SCB (Fig. 2B).
There is some indication that AMP systems continue to improve productivity the longer these practices are implemented. A comparison of the years of adoption with standing crop biomass for all five of the AMP grazers provides a moderate direct correlation (R = 0.5274; F(1,3) = 1.16; p = 0.361) (Fig. S2A), but when the AMP-5 farm is removed, a very strong direct relationship (R = 0.9589; F(1,2) = 22.83; p = 0.041) of years of adoption to standing crop biomass is observed (Fig. S2B). CG systems provided no similar observations as there is no diversion of plant biomass towards development of the soil food web population, structure, diversity and metabolic functionality. Leaving 60% of SCB in AMP managed systems promoted better conversion of incoming sunlight and water resources to enhance system photosynthetic capacity and resultant SCB, enough to provide sufficient forage biomass to support grazer stocking densities 2.38 times higher than CG systems (Table 1), while also promoting development of soil food web structure, diversity and functionality and collectively making AMP systems more ecologically resilient, sustainable and profitable.
Current rangeland research underestimates the potential for carbon capture on rangeland by presuming: (a) the “drivers of soil carbon fluxes on rangelands are dominated by climate rather than management” (Brown et al., 2010); (b) there is a general trending decrease in carbon sequestration potential associated with longevity of the grazing management practices (Derner & Schuman, 2007); and (c) estimates for soil carbon increases on rangeland of from 0.1 to 0.3 tonnes C ha−1 year−1 (Morgan et al., 2010). Comparison of AMP and CG management strategies challenges these observations by: (a) Brown et al., that climate instead of management is a key determiner of soil carbon flux on rangelands by demonstrating that grazing management is key to determining soil carbon flux as demonstrated by increased SCB, SOC% and reduced respiration across three climate zones (Zones 3,4 and 5); (b) Derner and Schuman’s research conclusions of a “trending decrease in carbon sequestration potential” associated with longevity of grazing management, where the number of years of adoption of AMP management increased carbon sequestration potential by demonstrating increasing SCB, SOC% and reduced soil respiration from increased longevity of AMP adoption, and (3) Morgan et al., of estimates of 0.1 to 0.3 tonnes C ha−1 yr−1 where AMP management demonstrated an extra 0.33 tonnes C ha−1 yr−1 (average SOC% increase of 0.48%, in the top 10 cm of the soil profile, with a soil with a bulk density of 1.21 g cm−3, over the average 17.6 years of adoption) when compared to CG systems. Sampling in the top ten centimeters does not allow a comprehensive assessment of soil carbon increase but an associated study, conducted in parallel and on the same calendar dates and identical sampling locations on these AMP and CG farms, concluded a total increase of 9 tonnes C ha−1 in soil organic C stocks, in the top meter of the soil, when comparing AMP to CG management (Mosier et al., 2021). This differential in soil carbon provides an average increase of 0.51 tonnes C ha−1 year−1 if calculated over the average 17.6 years of adoption of AMP practices.
Hypothetically, soil organic carbon increases of 0.51 tonnes C ha−1 yr−1 would provide an extra 1.86 tonnes CO2 ha−1 yr−1 removed from the atmosphere, or an extra 2.34 billion tonnes CO2 globally, if extrapolated to the adoption of AMP on the 1.25 billion hectares of rangeland. This mass is ∼6.39% of the total 36.6 tonnes anthropogenic CO2 emitted into the atmosphere.
Given photosynthetic capacity for savannahs average ∼900 g dry biomass m−2 yr−1 and temperate grasslands produce ∼700 g dry biomass m−2 yr−1 mean net primary productivity (Whittaker & Likens, 1975; Ruimy, Saugier & Dedieu, 1994), then AMP system’s 46.3% increase in SCB could hypothetically demonstrate from 323 g to 416 g SCB m−2 year−1 improvement in SCB. An average increase of 369.5 g dry biomass m−2 year−1of SCB in rangeland productivity would theoretically remove an extra 2.14 tonnes C ha−1 year−1 as a result of this increase in photosynthetic capacity. If AMP grazing methodologies were realized over the1.25 billion hectares of similar global grazing-land ecotypes, this increase in SCB would remove an extra 9.82 billion tonnes CO2 year −1 or ∼26.8% of the 36.6 tonnes of total anthropogenic CO2 emissions.
Respiration can be variable with climate, temperature, moisture and season; however, the observed 19.52% reduction of soil CO2 respiration rates in AMP managed ranches, offers significant potential annual soil CO2 respiration reduction. Using a conservative average of 745 ± 421 g C m−2 year−1 for the temperate grassland and savannah annual respiration rate (Bond-Lamberty & Thomson, 2010) the 19.52% decrease in soil CO2 respiration could reduce soil CO2 emissions by 145.42 g C m−2 yr−1 (533.22 g CO2 m−2 yr−1). This would give a hypothetical global CO2 reduction potential of ∼6.66 billion tonnes CO2 year−1 on the 1.25 billion hectares of savannahs and grasslands, or approximately 18.19% of global CO2 emissions.
AMP grazing management offers beneficial ecosystem services from related increases of carbon compartmentalization into SOC, SCB and observed reduction in soil carbon respiration. These increases/reductions are not cumulative, but they offer the potential impact for improving overall grazing land’s efficiency, in AMP managed systems, to assist in capturing or retaining carbon in soils of rangeland that in aggregate represent ∼51.38% of anthropogenic CO2 emissions. These potential “efficiency” increases, resulting from the adoption of AMP grazing systems practices, could provide a path towards a cost effective, logical and viable carbon sequestration vehicle.
The experimental hypothesis in this research was that AMP grazing methodologies promote beneficial changes in soil food web population and structural composition (bacterial and fungal biomass, F:B ratio, and protozoa enumeration) and function, and that these shifts in the soil food web population structure positively influence grazing system photosynthetic capacity, soil microbial respiration efficiency and the storage of carbon in AMP grazed rangeland soils when compared to CG systems. Funding for a multi-year “multi-systems” research project would have been prohibitively expensive. The observations and data garnered, in this point-in-time research analysis of soil food web population and structure in five ranch-pair comparisons of AMP and CG grazing strategies, offers preliminary data and experimental design components that provide an alternative perspective for viewing grazing management systems that could help in planning long-term research. Once CG ranchers are made aware of the benefits of AMP grazing management, it would be difficult for neighboring CG ranchers to commit to not altering their management practices for a long-term research project.
AMP management practices promoted: (a) increases in system photosynthetic capacity, as evidenced by higher SCB in AMP ranch systems, yielding a cumulative 92.68 g dry biomass m−2 increase for AMP over CG; (b) improved SOC accumulation in AMP systems, yielding an average 20.6% SOC (%) increase over CG systems; and (c) a 19.52% lower soil respiration rate in AMP ranches relative to CG ranches (Table 2) and (d) 2.36 times more animal units ha−1, without applying synthetic nutrient inputs.
Implementation of AMP grazing strategies, short grazing periods, leaving adequate forage residue for ground cover, providing longer rest periods for full forage recovery from grazing, and adjusting stocking levels to match available forage levels, helps to regenerate soil food web population, structure, diversity and biological functionality. AMP grazing systems provide a common-sense, economically viable mechanism to improve productivity and profitability of rangeland managers (Teague & Kreuter, 2020) while reducing green-house gasses and improving delivery of ecosystem services and socio-ecological resilience in grazing ecosystems.
Rainfall and percent of rainfall for AMP/CG ranch pairs
Monthly percent-of-normal rainfall maps for January-June of 2018, and departure-from-normal maps for April-May 2018. Black stars indicate AMP and CG farm locations.
Years of AMP and CG ranch grazing management
Years of Adoption of Adaptive Multi-Paddock (AMP) grazing management compared to standing crop biomass. Figure (A) depicts all five AMP farms number of years of adoption and their moderate direct correlation with standing crop biomass (R2 = 0.2782; p = 0.361). Figure (B) relays the linear regression analysis (R2 = 0.9194; p = 0.04) with the removal of AMP-5 to demonstrate a strong direct relationship indicting the longer AMP practices are employed, the greater the production of standing crop biomass.
Adaptive Multi-Paddock and Continuous Grazing Rainfall
Monthly percent-of-normal rainfall maps for January-June of 2018, and departure-from-normal maps for April–May 2018. Stars () indicate AMP and CG farm locations.
Adaptive Multi-Paddock and Continuous Grazing Soil Food Web
AMP and CG pairwise and pooled comparison of bacteria and fungi (ug gm −1 dry soil); fungal to bacterial ratio (F:B); soil food web proxy, a normalized summation of bacteria, fungi, and protozoa populations and protozoa (# g −1 dry soil). Statistically significant comparisons are highlighted in gray backgrounds and bold type. The abbreviation NS means No Statistical Significance.
Methodology for static alkali reactor assessment
Analysis methodology for assessing CO 2 absorption with Static Alkali Reactors.

domain: agronomy


text:
An investigation for investors in DZS Inc. (NASDAQ:DZSI) shares over potential securities laws violations by DZS Inc. was announced.
San Diego, CA -- (SBWIRE) -- 06/14/2023 -- DZS Inc. is under investigation over potential securities laws violations in connection with certain financial statements.
Investors who purchased shares of DZS Inc. (NASDAQ: DZSI), have certain options and should contact the Shareholders Foundation at firstname.lastname@example.org or call +1(858) 779 - 1554.
The investigation by a law firm focuses on whether a series of statements by DZS Inc. regarding its business, its prospects and its operations were materially false and misleading at the time they were made.
Plano, TX based DZS Inc. provides access and optical networking infrastructure and cloud software solutions in the Americas, Europe, the Middle East, Africa, and Asia.
DZS Inc. reported that its annual Total Revenue rose from $350.2 million in 2021 to $375.69 million in 2022, and that its Net Loss increased from $34.68 million in 2021 to $37.43 million in 2022.
On June 1, 2023, before the market opened, DZS Inc. disclosed that it needs to restate its previously issued financial statements for the first quarter of 2023. DZS Inc. further disclosed that the restatement relates to approximately $15 million in revenue recognized in connection with two customer projects.
Shares of DZS Inc. (NASDAQ: DZSI) declined from $7.39 per share on May 19, 2023, to $.326 per share on June 06, 2023.
Those who purchased shares of DZS Inc. (NASDAQ: DZSI) have certain options and should contact the Shareholders Foundation.
Shareholders Foundation, Inc.
3111 Camino Del Rio North - Suite 423
92108 San Diego
About The Shareholders Foundation
The Shareholders Foundation, Inc. is a professional portfolio monitoring and settlement claim filing service, , which does research related to shareholder issues and informs investors of securities class actions, settlements, judgments, and other legal related news to the stock/financial market. Shareholders Foundation, Inc. is in contact with a large number of shareholders and offers help, support, and assistance for every shareholder. The Shareholders Foundation, Inc. is not a law firm. Referenced cases, investigation, and/or settlements are not filed/reached and/or related to Shareholders Foundation. The information is provided as a public service. It is not intended as legal advice and should not be relied upon.

domain: economics


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domain: entertainment


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The teaser scene was set on Haulover Beach in North Miami, which has a section for nude sun bathing. But we didn't film in that area; we're not that kind of show!
The mermaid tail worn by Cassandra Hudson was made by a specialty shop in Los Angeles and was constructed out of silicone. It weighs around 75 pounds and it took three costumers to get the stunt girl into it.
Question: What other TV show do guest star Amelia Blaire, who plays Brooke Hudson, and Michelle Hurd, who plays Colleen Manus, have recurring roles on? Answer: 90210.
The synchronized swimming group is played by a professional water show group called The Dolphinettes of Miami.
The scene where Callie and Jim slow dance was filmed at the Harbor Beach Marriott. Filming started around 11 p.m. and ended around 3 a.m. the next day. Interesting how a scene that only lasts two or three minutes can take four hours or longer to film, huh?
The hoop that Brooke comes down from the sky on during the big performance scene was originally going to be shaped like an anchor, but due to counter weight balance issues, the stunt coordinator had to come up something else. He had this new hoop developed and built by Cirque Du Soleil Orlando. The developers also came down to the set to rig and test it to make sure Amelia would be safe.
The octopus found in the victim's mermaid tail was real and had its own handler.
This episode was directed by Lee Rose. Last season, she directed the episode "Old Ghosts."
The "Drunk Tank" holding cell sounds like it has heavy duty steel doors, but the whole set is actually made of wood. We use sound effects to make you believe they are made of steel.
The Fire House bar scene was filmed up the road from the studio at a place called The Polo Club, which used to be famous restaurant called Casey's Nickelodeon.
The bathroom set is new to Jim's home on the Glades. It has real hot and cold running water and a drain system. The tub and shower area are built on a movable riser called a wild wall, which is used for wider views and angles.
Cassandra's apartment was actually a suite at the Hyatt Hotel in Fort Lauderdale, though you probably couldn't tell by the way it was dressed by our set decorating department. There was a 65-foot yacht in the backyard of the hotel, but by decorating and filming strategically, you couldn't tell.
Production notes courtesy of Marc Weinstein.


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STLCC Libraries provide electronic access to full-text articles, abstracts, and citations for journals in film to STLCC students, faculty and staff. You may also link to a list of art databases or a complete listing of the library databases.
St. Louis Community College Libraries
Florissant Valley Campus Library3400 Pershall Rd. Ferguson, MO 63135-1408Phone: 314-513-4514
Forest Park Campus Library 5600 Oakland St. Louis, MO 63110-1316Phone: 314-644-9210
Meramec Campus Library11333 Big Bend Road St. Louis, MO 63122-5720Phone: 314-984-7797
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domain: library


text:
Bain Capital is digging in on its $3-a-share bid for aged care operator Estia Health, Street Talk can reveal.
Sources said that the Boston-headquartered buyout fund, led locally by Mike Murphy, was reaching a critical point in the first round of due diligence and preparing to front its investment committee as early as this week for approval to proceed.
If all goes well, Bain and its advisers will dive into a second round of more extensive, confirmatory diligence with a view to putting a binding offer in front of the Estia board, led by veteran dealmaker Gary Weiss.
Of course, there’s plenty more to play out before we see a near $1 billion buyout but Murphy’s far from withdrawing from the fray, contrary to unsubstantiated reports published elsewhere.
When we last checked in on this saga, the Estia board was busy trying to reel in a bigger bid from Bain, describing its $3 a share bid as not compelling.
The board granted Bain access to non-public financial information to see whether there was something that could lead to a higher bid.
Bain would surely point out that only those on the register for five years or more have ever seen the share price at or above $3. Shares have been trading between $2.50 and $2.70 over the past month, revealing the market’s scepticism that a deal will get done.
The private equity shop first lobbed its bid for the aged care operator in late-March with Morgan Stanley in tow after Street Talk spotted movement on its register. The $3 a share represented a 28.2 per cent premium to Estia’s close on the day of the bid, but the stock ran up 9.3 per cent in the preceding days. It was 23.5 per cent higher than Estia shares’ 52-week high of $2.43.
Estia has called in UBS for defence.
The bid will play out against the fight for aged care pay in the Fair Work Commission, where the Australian Nursing and Midwifery Federation is pursuing major aged care providers and calling on the federal government to force them to pass on all funding as higher wages.
The M&A interest comes only two months after Estia’s long-time shareholder (and one-time mooted acquirer) Seven Group bailed on the company and blew open its share register. Seven sold its 10 per cent stake at $2 a share to institutional investors, via Macquarie’s desk.
Current substantial investors include Wilson Asset Management at 9.64 per cent, followed by Melbourne’s Copia Investors at 5.24 per cent and Argo Investments with about 5 per cent. WAM Capital has voiced opposition at the current bid price.


text:
Make a Cookbook
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Buffalo Shrimp Dip
Artichoke Crab Spread
*TIRAMISU [tih-ruh-mee-SOO, tih-ruh-MEE-soo] - the translation for tir..
Tortellini with Chicken, Basil & Tomato
Texas Style BBQ Brisket
Grilled Chicken Kabobs with Greek Style Barley Salad
*Note for the nutrition information, only ¼ of a cup of oil per servi..
Stuffed Flank Steak
German Beef Roulades over Spaetzle
Cajun Beef and Root Vegetable Stew
The ingredients for the original recipe are in "cooking for a crowd" a..
Broiled Flank Steak Chimichurri Sauce
The ingredient amounts here are for "cooking for a crowd" yield of 24 ..
Braised Short Ribs
Did you know that in some cases pepper has been used to stop bleeding?..
Stuffed vegetables and vine leaves
LOUIS HOTELS Celebrate! The 70 Years Young!! AND share with YOU 70 Mos..
Turkey Asiago Sliders
These sliders are the perfect way to get summer started.
Easy Chocolate Tart
Crunchy Gingerbread Men Cookies
Kellogg's Rice Krispies Cookies
Swedish Tea Cakes
Magic Cookie Bars
Tilapia Grilled With Coconut Curry Sauce (about $3 Per Serving)
Whole Wheat Caramel Lattes
I Want That Recipe Bars!
Lemon-poppyseed Bundt Cake
Coffee-Toffee Cake with Caramel Frosting
Spicy Strawberry Ice Cream
Cinnamon Cream Cheese Puffs


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Pick your preferred language. We speak English and 42 other languages.
Located in Wacken in the Schleswig Holstein region, Wacken Ferienhaus features a terrace. This self-catered vacation home has a garden.
Offering free WiFi and garden views, Bokelrehm is a property located in the apartment.
Offering free WiFi and garden views, Bahnhof Vaale • Fliegender Hamburger is a property located in Vaale. Guests staying at this apartment can use the fully equipped kitchenette and a terrace.
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Located in Neuendorf-Sachsenbande, Fewo Bendig offers self-catering accommodations with free WiFi. Guests benefit from terrace. Free private parking is available on site.


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domain: game


"Oh almost forgot, they said,
hear all the sounds and listen to them
and sleep in all the silences and get a good rest from them".
MyFace Bookperformance, p.118
In the series of “Letters & Notes & Rests: Bookperformance ”, Çiğdem expresses how a word is composed and transfer the “desired” meaning thanks to the letters, notes and rests.
It is a time and space for such an expression in company of especially sounds of jazz that are inspiring source for Çiğdem’s books and performances.
She employs any sound of any word in any language while composing pieces for such bookperformances that happen to be open to improvisation.
Differently from other venues that welcome bookperformance in letters, notes and rests, Blue Flamingo Jazz Festival, which Çiğdem has taken up presenting, is a time and space not only to do bookperformance but also conversations on sounds and silence with musicians and audience. Check out the dates of the editions and join the sounds!


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Softball - Minor Division Rules
UpdatedMonday May 2, 2016 byFranklin Little League.
Note that the Little League International rules apply, with the exception of the following. These rules will be in place for all regular-season games, either interleague or intraleague.
- All agreed-upon rules will be discussed with the umpire at the start of every game during the coaches meeting. Remember that each umpire will have a different interpretation of our agreement.
- Managers, remember this division is to develop players. Although competition will be natural, we ask that you focus on enhancing skills and abilities of each and every player. Save competition for the end of the season tournament.
- Nine (9) fielders will be used. You need a minimum of nine (9) to play. The three (3) outfielders need to start in the grass of the outfield.
- A continuous batting order will be used throughout the game. A player arriving late and is not entered in the lineup at the start, upon entering the game she will be inserted after the last batter listed on the lineup card.
- A five (5) run limit per inning will be imposed. The rule does not apply to the sixth (6th) inning. The home team will be the winner if they lead by ten (10) or more runs after three and a half (3 ½). The visitor will be the winner if they lead by ten (10) or more runs after the fourth (4th) or any full inning after that. Note that the 10-run rule may not be enforced in Franklin Little League intraleague play.
- Hard stop of play at 1:45 hours but batter may finish her at-bat. If last batter scores winning run or is the third out, the final score will be after that batter's at-bat. If the last batter does not score the winning run or is not the third out, the final score will revert to the last complete inning.
- Stealing is allowed, however the runner cannot leave the base until the ball crosses home plate.
- When the pitcher is in the pitcher's circle and in possession of the ball, the base runner(s) shall not leave their base(s) until the pitched ball has been batted or reaches the batter.
- Outfielders must play in or at the grass line not on the infield.
- A borrowed player will be the girl that last batted for the opposing team. A borrowed player(s) must play an outfielder position closest to the dugout they are in. A team may only borrow enough players to make nine (9).
- Coach Pitch: Coach Pitch will occur during regular season and tournament play. NO WALKS. When the pitcher has given the batter four (4) balls, the batter will receive up to three (3) coach pitches. The batters strike count will carry over to the coach pitch. The batter will get up to three (3) pitches or three (3) swinging strikes whatever comes first to put the ball in play. After three (3) pitches the batter will be out if the batter doesn’t put the ball in play. If the batter fouls the third (3rd) pitch, they will get another pitch or pitches until the ball is put into play or the batter swings and misses the ball. There is no limit on the number of pitches as long as the ball is fouled off. When the next batter is up the pitcher will continue. During coach pitch the pitcher and the coach must keep one foot inside the circle. If the ball is in play the mgr/coach must avoid getting in the way of the play. The batting team will be the coach who pitches for the batter. The ball needs to be delivered underhand.
- Batter Hit by a Pitch: Considering this is the first year that some players will be pitching, and batters will be facing live pitching, the rule concerning being hit by a pitched ball with regards to not making an attempt to move out of the way of the pitch will not apply at this level. Batters will be more likely to “freeze” rather than move. Therefore, if a pitched ball hits a batter, they will be awarded first base or given a choice for coach pitch, unless bases are loaded then only coach pitch.
- We will use a eleven inch (11”) softball and the pitching distance will be set at thirty-five feet (35’)

domain: sports