In search of effective scales for stream management: does agroecoregion,watershed, or their intersection best explain the variance in stream macroinvertebrate communities?

Our lack of understanding of relationships between stream biotic communities and surrounding landscape conditions makes it difficult to determine the spatial scale at which management practices are best assessed. We investigated these relationships in the Minnesota River Basin, which is divided into major watersheds and agroecoregions which are based on soil type, geologic parent material, landscape slope steepness, and climatic factors affecting crop productivity. We collected macroinvertebrate and stream habitat data from 68 tributaries among three major watersheds and two agroecoregions. We tested the effectiveness of the two landscape classification systems (i.e., watershed, agroecoregion) in explaining variance in habitat and macroinvertebrate metrics, and analyzed the relative influence on macroinvertebrates of local habitat versus regional characteristics. Macroinvertebrate community composition was most strongly influenced by local habitat; the variance in habitat conditions was best explained at the scale of intersection of major watershed and agroecoregion (i.e., stream habitat conditions were most homogeneous within the physical regions of intersection of these two landscape classification systems). Our results are consistent with findings of other authors that most variation in macroinvertebrate community data from large agricultural catchments is attributable to local physical conditions. Our results are the first to test the hypothesis and demonstrate that the scale of intersection best explains these variances. The results suggest that management practices adjusted for both watershed and ecoregion characteristics, with the goal of improving physical habitat characteristics of local streams, may lead to better basin-wide water quality conditions and stream biological integrity.     

Monitoring the performance and decline of heritage trees in urban Hong Kong

Urban trees in Hong Kong exist in stressful and harsh habitat conditions due mainly to the exceptionally high-density development mode. This study focuses on the cream of the urban tree stock, the heritage trees, which were selected according to five sets of stringent criteria: species, dimension, structure, condition, location, and special considerations. The study area covers the main urban core of the city. The loss of trees in two periods, 1993-1998 and 1999-2003, was monitored, with the predisposing and direct causes of damages ascertained as far as possible. Of the 380 heritage specimens, 54 trees were lost in the survey period. The main predisposing causes were injuries sustained in roadwork and construction activities, both related to root damage and soil disturbance. The principal direct causes were recent gradual decline and abrupt demise due to typhoon breakage. Three pairs of contributing variables registered statistically significant associations (chi(2) test), namely predisposing cause versus direct cause, tree growth form versus direct cause, and survey period versus direct cause. Principal component analysis identified three factors that explained 70% of the variance, namely tree form, tree stature, and growth environment. The main reasons for the high mortality were explored. The possible applications of the findings to improve tree protection and management were discussed in relation to the overall planning for meritorious greenery and green space especially in compact cities.     

Planned versus actual outcomes as a result of animal feeding operation decisions for managing phosphorus

The paper explores how decisions made on animal feeding operations (AFOs) influence the management of manure and phosphorus. Variability among these decisions from operation to operation and from field to field can influence the validity of nutrient loss risk assessments. These assessments are based on assumptions that the decision outcomes regarding manure distribution will occur as they are planned. The discrepancy between planned versus actual outcomes in phosphorus management was explored on nine AFOs managing a contiguous set of 210 fields in south-central Wisconsin. A total of 2611 soil samples were collected and multiple interviews conducted to assign phosphorus index (PI) ratings to the fields. Spearman's rank correlation coefficients (r(S)) indicated that PI ratings were less sensitive to soil test phosphorus (STP) levels (r(S) = 0.378), universal soil loss equation (USLE) (r(S) = 0.261), ratings for chemical fertilizer application (r(S) = 0.185), and runoff class (r(S) = -0.089), and more sensitive to ratings for manure application (r(S) = 0.854). One-way ANOVA indicated that mean field STP levels were more homogenous than field PI ratings between AFOs. Kolmogorov-Smirnov (K-S) tests displayed several nonsignificant comparisons for cumulative distribution functions, S(x), of mean STP levels on AFO fields. On the other hand, the K-S tests of S(x) for PI ratings indicated that the majority of these S(x) functions were significantly different between AFOs at or greater than the 0.05 significance level. Interviews suggested multiple reasons for divergence between planned and actual outcomes in managing phosphorus, and that this divergence arises at the strategic, tactical, and operational levels of decision-making.     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

Improving lake riparian source area management using surface and subsurface runoff indices

Sensitivity indices, which rank factors pertinent to surface and subsurface runoff pathways, were used to identify phosphorus source areas in riparian zones of 15 northern Minnesota lakes. Watershed models were first developed using a geographic information system (GIS). Empirical models were then developed correlating water quality with land use, lake morphometry, and riparian sensitivity. Base models of forested, cultivated, pasture/open, wetland and residential land use within 100, 200, 400, and 2000 m of the study lakes were regressed on total phosphorus and chlorophyll-a. Area-weighted groundwater and surface runoff sensitivity indices were then incorporated into each model and tested for significance. Within the 200-m buffer, the total phosphorus base model was improved by including the groundwater index alone. The chlorophyll-a base model at 200 m was improved by including: (1) the groundwater index alone, and (2) both the groundwater and surface runoff sensitivity indices. Results suggest that surface and subsurface runoff analysis of potential source areas can improve decision making for lake riparian management.     

POTENTIAL EFFECTS OF CLIMATE CHANGE ON AGRICULTURAL WATER USE IN THE SOUTHEAST U.S.1

ABSTRACT: Climate change has the potential to have dramatic effects on the agricultural sector nationally and internationally as documented in many research papers. This paper reports on research that was focused on a specific crop growing area to demonstrate how farm managers might respond to climate-induced yield changes and the implications of these responses for agricultural water use. The Hadley model was used to generate climate scenarios for important agricultural areas of Georgia in 2030 and 2090. Linked crop response models indicated generally positive yield changes, as increased temperatures were associated with increased precipitation and CO2. Using a farm management model, differences in climate-induced yield impacts among crops led to changes in crop mix and associated water use; non-irrigated cropland received greater benefit since irrigated land was already receiving adequate moisture. Model results suggest that farm managers will increase cropping intensity by decreasing fallowing and increasing double cropping; corn acreage decreased dramatically, peanuts decreased moderately and cotton and winter wheat increased. Water use on currently irrigated cropland fell. The potential for increased water use through conversion of agriculturally important, but currently non-irrigated, growing areas is substantial.     

Establishing a Regional Monitoring Strategy: The Pacific Northwest Forest Plan

adaptive monitoring design. Adaptive monitoring design is an iterative process that refines the specifications for monitoring over time as a result of experience in implementing a monitoring program, assessing results, and interacting with users. An adaptive design therefore facilitates ecosystem management. We also discuss lessons of temporal and spatial scales raised by the consideration of a design for ecosystem management. Three additional issues—integration of information from different sources, institutional infrastructure, and the roles of individuals working in an interagency setting—are also identified, but not developed in detail.