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This data package contains nitrogen mineralization data from soils collected along the Jornada Basin LTER (LTER-I) transects in southern New Mexico, USA. These transects are located in a livestock exclosure established in 1982 in the Chihuahuan Desert Rangeland Research Center (CDRRC) and run from the middle of the College Playa up to the foot of Mt. Summerford (2.7 km in length). Prior to the exclosure, the study site was moderately to heavily grazed for the past 100 years. The Treatment transect was treated annually with ammonium nitrate fertilizer (NH4NO3 at 10g N/m2/yr) until 1987. Along each transect, 91 stations, each with a plant intercept line, are spaced at 30 meter intervals. For this dataset, 60 soil samples (total) were collected along the control and fertilized treatment transects and mixed with potassium chloride solution (KCl) on Nov 27, 1989, then filter extracted four days later to give a time = 0 incubation value. The dataset contains a soil moisture correction factor, sample weights, total inorganic nitrogen (NO3+NO2-N), and nitrogen in ammonium (NH4-N) for Week 0 of nitrogen mineralization potentials. The soil mineralization data complements the biomass harvest measurements that occurred in September 1989 (dataset knb-lter-jrn.210015001). This study is complete.
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Optimizing sampling across methods improves the power of ecological monitoring data
Transect-based monitoring has long been a valuable tool in ecosystem monitoring. These transects are often used to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of these core methods on a one-hectare plot to transect length, number, and sampling interval to determine: 1) minimum sampling required to describe ecosystem characteristics and detect change for each method and 2) optimal transect length and number for all three methods to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations spanning the western US, which included 151 measurements over time across five biomes. We found that longer and increased numbers of transects were more important for reducing sampling error than increased sample intensity along transects. For all methods and indicators across plots, three 100-m transects reduced sampling error so that indicator estimates fall within an 95% confidence interval of +/- 5% for canopy gap intercept and LPI-total foliar cover, +/- 5 cm for height and +/- two species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.
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- Award ID(s):
- 2025166
- PAR ID:
- 10557678
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This data package contains nitrogen mineralization data from soils collected along the Jornada Basin LTER (LTER-I) transects in southern New Mexico, USA. These transects are located in a livestock exclosure established in 1982 in the Chihuahuan Desert Rangeland Research Center (CDRRC) and run from the middle of the College Playa up to the foot of Mt. Summerford (2.7 km in length). Prior to the exclosure, the study site was moderately to heavily grazed for the past 100 years. The Treatment transect was treated annually with ammonium nitrate fertilizer (NH4NO3 at 10g N/m2/yr) until 1987. Along each transect, 91 stations, each with a plant intercept line, are spaced at 30 meter intervals. For this dataset, 60 soil samples (total) were collected along the control and fertilized treatment transects and mixed with potassium chloride solution (KCl) on Nov 27, 1989, then filter extracted the following day. The dataset contains a soil moisture correction factor, sample weights, total inorganic nitrogen (NO3+NO2-N), and nitrogen in ammonium (NH4-N) for Week F (field) of nitrogen mineralization potentials. The soil mineralization data complements the biomass harvest measurements that occurred in September 1989 (dataset knb-lter-jrn.210015001). This study is complete.more » « less
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Monitoring is a crucial tool for measuring the progress and success of environmental policies and management programs. While many studies have evaluated the effectiveness of biodiversity sampling methods, few have compared their efficiency, which is crucial given the funding constraints present in all conservation efforts. In this study we demonstrate how existing analytical tools can be applied to (i) assess the relationship between sampling effort and resulting confidence in biodiversity metrics, and (ii) compare the efficiency of different methods for monitoring biodiversity. We tested this methodology on data from marine fish surveys, including: roving surveys within permanent areas, randomly placed belt transects, and randomly placed transects conducted by citizen scientists using a reduced species list. We constructed efficiency curves describing how increasing effort spent on each method reduced uncertainty in biodiversity estimates and the associated ability to detect change in diversity. All programs produced comparable measurements of species diversity for all metrics despite substantial differences in the species being surveyed by each method. The uncertainty of diversity estimations fell faster and reached a lower level for the roving diver method. Strikingly, the transect method conducted by citizen scientists performed almost identically to the more taxonomically resolved transect method conducted by professional scientists, suggesting that sampling strategies that recorded only a subset of species could still be effective, as long as the excluded species were chosen strategically. The methodology described here can guide decisions about how to measure biodiversity and optimize the resources available for monitoring, ultimately improving management outcomes.more » « less
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