Method Metrics Supporting evidence Contradictory evidence Relevant spatial and temporal scales
Direct habitat measures
Food availability
Prey animal biomass (Atiénzar et al., 2012, Deboelpaep et al., 2020, Herring and Gawlik, 2013, Holopainen et al., 2014, Hunt et al., 2017, Parks et al., 2016, Schultz et al., 2020) Plant-derived food density or abundance (Arzel et al., 2015, Atiénzar et al., 2012, Dugger and Feddersen, 2009) Birds behaviourally track sites with highest prey biomass and density (Rose and Nol, 2010) Prey availability has a positive influence on reproductive performance (Herring et al., 2010) Chick condition is related to local prey abundance (Hunt et al., 2017) Predicts occupancy but not abundance (Gillespie and Fontaine, 2017) Sites with high food densities are not always the favoured foraging sites (Hagy and Kaminski, 2015) The seeds of different plant species consumed by waterfowl have different energy content (Dugger et al., 2007) Different food items can result in different mass gain even when fed ad libitum (Jorde et al., 1995) Waterbirds may forage selectively on larger size-class prey items meaning that overall prey density is not reduced through waterbird foraging even though waterbirds’ preferred prey size has been significantly depleted (Fonseca and Navedo, 2020)
Site/region – Instantaneous/within season/annual
Primary productivity
Normalised Difference Vegetation Index (NDVI) (Tang et al., 2016, Zhang et al., 2017) Enhanced Vegetation Index (EVI) (Guan et al., 2016)
The method provides an indirect indication of habitat quality with at least one further transitional state before primary productivity influences waterbird energy intake rate (Zhang et al., 2017)
Site/region/Flyway – Instantaneous/within season/annual
Predation pressure
Predator track density (Cohen et al., 2009) Index of predator reproduction (Trinder et al., 2009) Proportion of radio-tracked individuals predated (Kenow et al., 2009, Swift et al., 2020) Proportion of real or fake nests predated (Pehlak and Lõhmus, 2008, Swift et al., 2020) Alternate prey density (Holopainen et al., 2014) Predation can be the leading cause of waterbird nest failure (Riecke et al., 2019) Predation risk is evaluated by waterbirds and trade-offs made that may reduce other components of fitness (e.g., foraging rate) (Fernández and Lank, 2010) Nest predation rate was not a function of predator abundance or the availability of alternate prey species (Machín et al., 2019) The influence of predation can differ depending of the waterbird population density (Lebeuf and Giroux, 2014)
Site/region – Instantaneous/within season/annual
Vegetation structure
Vegetation height (Barati et al., 2011) Vegetation cover/abundance (Atiénzar et al., 2012, Hamza et al., 2015, Hierl et al., 2007, Nyman and Chabreck, 1996) Vegetation community composition (Benedict and Hepp, 2000, Dugger and Feddersen, 2009) Presence of invasive plants (Khan, 2010, Tavernia and Reed, 2012) Vegetation structure has implications for the suitability of a site for nest placement (Barati et al., 2011) Dense vegetation may increase prey abundance but reduce prey capture efficiency (Lantz et al., 2011)
Site/region – Instantaneous/within season/annual
Wetland spatial attributes
Connectivity to neighbouring wetlands (Sebastián-González et al., 2010b) Pond area (Atiénzar et al., 2012, He et al., 2009, Merendino and Ankney, 1994) Shoreline irregularity (Merendino and Ankney, 1994) Pond size and distance to the nearest neighbouring wetland are important determinants of waterbird habitat selection (Sebastián-González et al., 2010b) Cycles of hydrological stress (drought/non-drought) can influence waterfowl habitat preferences, with birds seeking relatively deeper water bodies during drought irrespective of other habitat variables that are influential in wet years (Atiénzar et al., 2012)
Site/region – Instantaneous/within season/annual
Water level
Drawdown (Herring and Gawlik, 2013, Townsend et al., 2006); Water level variability (Collazo et al., 2002) Availability of shallow water (Collazo et al., 2002, Gawlik and Crozier, 2007, Lantz et al., 2011) Landscape depth heterogeneity (Beerens et al., 2015) Wading birds preferentially selected ponds that had been experimentally manipulated to have shallow rather than deep water (Gawlik and Crozier, 2007) and waterbird species richness and density correlates with the availability of shallow water habitats (Wang and So, 2003) Water level recession rate was a key influence on physiological condition of two species of waterbirds (Herring and Gawlik, 2013) Water level variability did not influence habitat selection of wading birds (Gawlik and Crozier, 2007)
Site/region – Instantaneous/within season/annual
Disturbance
Distance to footpaths, roads, or railways (Burton et al., 2002, Hu et al., 2016, Li et al., 2019) Human settlements (Li et al., 2019) The presence of people and vehicles nearby (≤50 m) reduces foraging rates (Maslo et al., 2012) Likewise, time spent foraging and flock density were reduced at a highly disturbed site (Swift et al., 2020) Human activities (e.g., clam harvesting) may have positive effects on waterbirds, especially shorebirds (Hamza et al., 2015)
Site/region – Instantaneous/within season/annual
Foraging substrate
Sediment grain size (Reurink et al., 2015, Rose and Nol, 2010) Organic carbon content (Hamza et al., 2015, Reurink et al., 2015) Mud content (Hamza et al., 2015) Prey biomass is strongly predicted by physical environment conditions including organic content and particle sizes of the sediments (Rose and Nol, 2010)
Site/region – Instantaneous/within season/annual
Land use
Proportion of agricultural land use (Austin et al., 2001, Duncan et al., 1999) Mariculture (Li et al., 2019) Mining (Li et al., 2019) Changing land use can cause ecological traps if agricultural landscapes appear similar to natural landscapes (e.g., grasslands) but offer lower habitat quality (Buderman et al., 2020) Factors such as traditional site use by waterbirds can confound the signal of change in response to changing land use (Tombre et al., 2005)
Site/region – Instantaneous/within season/annual
Water chemistry
Colour/turbidity (Atiénzar et al., 2012, Merendino and Ankney, 1994) pH (Merendino and Ankney, 1994, Walsh et al., 2006) Conductivity/salinity (Atiénzar et al., 2012, Merendino and Ankney, 1994) Dissolved nutrients (Merendino and Ankney, 1994, Pöysä et al., 2001, Walsh et al., 2006) Chlorophyll-α concentration (Atiénzar et al., 2012) Prey biomass is influenced by salinity (Rose and Nol, 2010) Water chemistry variables including pH, salinity, and nitrogen and potassium concentration can be a predictor of occurrence of breeding ducks (Walsh et al., 2006)
Site/region – Instantaneous/within season/annual
Bird-derived estimates
Demographic measures
Reproduction
Clutch size/volume (Hunt et al., 2017, Mallory et al., 1994, Powell and Powell, 1986) Number of fledglings (Powell and Powell, 1986) A direct contributor to the per capita rate of population increase, the most proximate indicator of habitat quality
Site/region – Instantaneous/within season/annual
Survival
Adult survival (Alves et al., 2013, Rice et al., 2007, Swift et al., 2020) Brood survival (Aubry et al., 2013, Cohen et al., 2009, Hunt et al., 2017, Owen and Pierce, 2014, Simpson et al., 2007, Swift et al., 2020) A direct contributor to the per capita rate of population increase, the most proximate indicator of habitat quality
Site/region – Instantaneous/within season/annual
Distributional measures
Density or abundance
Abundance (Castillo-Guerrero et al., 2009, Dugger and Feddersen, 2009, Ganzevles and Bredenbeek, 2005, Hickman, 1994, Liu et al., 2006) Species richness (Dugger and Feddersen, 2009, Hickman, 1994) Density (Loewenthal et al., 2015, Swift et al., 2020) Abundance of breeding pairs (Arzel et al., 2015, Austin et al., 2001, Sebastián-González et al., 2010a) The density of breeding pairs increased much faster than could be explained by population growth rates following habitat management that resulted in greater food availability (Loewenthal et al., 2015) This was attributed to previously subordinate adults taking up breeding territories as territory size of existing pairs contracted (Loewenthal et al., 2015) Can be confounded by site fidelity (O’Neil et al., 2014), lags in response to change in condition (Loewenthal et al., 2015, Meltofte, 2006), dispersal barriers or costs, and imperfect knowledge of habitat (Lewis et al., 2010) Local and regional weather influences habitat use (Kelly, 2001, Schummer et al., 2010) Reproductive output is not correlated with population density (Cohen et al., 2009) Reduction in food availability can increase shorebird density as they are concentrated into the remaining suitable patches (Kosztolányi et al., 2006) Disturbance by human activity and farming rather than habitat quality (availability of foraging areas) more strongly influences waterbird species richness and abundance (Quan et al., 2002) Requires birds to correctly perceive habitat cues, which may not always be the case (e.g., agricultural land uses may resemble native grasslands, but have much lower reproductive output) (Buderman et al., 2020)
Site/region – Instantaneous/within season/annual
Phenology
Length of breeding period (Raquel et al., 2016) Residence times on non-breeding or stopover sites (O’Neal et al., 2012, Rice et al., 2007, Williams et al., 2019)
Spring migration stopover duration can decrease as a function of Julian day of the year (Williams et al., 2019)
Site/region –Within season/annual
Age class distribution
Age class distribution (Fernández and Lank, 2010) Adult shorebirds occupy sites with greater prey availability and lower predation risk than immature birds (Fernández and Lank, 2006)
Site/region – Instantaneous/within season
Hunting records
Harvest numbers as an indicator of present and past habitat quality (Merendino et al., 1992)
Region – Annual
Individual condition measures
Morphological variables
Abdominal profile index (Swift et al., 2020) Body mass (Herring and Gawlik, 2013, Hunt et al., 2017) Body condition index (Aubry et al., 2013, Parks et al., 2016) Chick growth rate (Hunt et al., 2017, Owen and Pierce, 2014) Abdominal profile index on the non-breeding grounds was correlated with breeding ground return rates, and subsequent nest survival and chick fate (Swift et al., 2020) Chick growth rates and adult body mass were positively correlated with invertebrate abundance in breeding Piping Plovers (Hunt et al., 2017)
Site/region –Within season/annual
Physiological variables
Stress markers (Aharon-Rotman et al., 2016b, Herring and Gawlik, 2013, Thomas and Swanson, 2013) Immune response markers (Buehler et al., 2009) Foraging metabolites (Lyons et al., 2008, Thomas and Swanson, 2013) Birds that occupy sites with higher fueling rates have lower concentration of physiological markers of stress in their blood (Aharon-Rotman et al., 2016b) Different species with different foraging strategies can have different blood physiology responses to changing availability of prey (Herring and Gawlik, 2013)
Site/region –Within season/annual
Parasite burden
Intestinal helminth load (Conner England et al., 2018) Haemosporidian parasite infection (Aharon-Rotman et al., 2016b)
Parasite burden negatively correlated with foraging habitat quality for some parasite taxa, but not significantly for all parasite taxa (Conner England et al., 2018)
Site/region –Within season/annual
Ptilochronology
Feather growth rate (Swift et al., 2020) Width of feather growth bands was positively correlated with an index of body condition (abdominal profile index) and feeding rates (Swift et al., 2020)
Site/region –Within season/annual
Behavioural measures
Foraging parameters
Peck/probe rate (Castillo-Guerrero et al., 2009, Mander et al., 2013) Success rate (Castillo-Guerrero et al., 2009, Swift et al., 2020) Step rate during foraging (Mander et al., 2013) Energy intake rate (Yu et al., 2020) Positively correlated with prey density and biomass and at productive sites may not be affected by interference competition (Rose and Nol, 2010) Peck rate is correlated with defecation rate indicating that peck rate is a meaningful proxy for intake rate (Rose and Nol, 2010) Capture success can be influenced by conspecifics, with increases in capture success occurring until conspecific density becomes high enough to induce interference competition (Stolen et al., 2012) Peck rate also reaches an upper asymptote, so may not be a true indication of habitat quality in very high productivity landscapes (Rose and Nol, 2010) Pecking rate can be significantly higher than probing rate for an equivalent energy return (Kuwae et al., 2010)
Site/region – Instantaneous/within season/annual
Time budgets
Proportion of time spent foraging (Castillo-Guerrero et al., 2009, Dugger and Feddersen, 2009, van der Kolk et al., 2019) Proportion of time in non-foraging behaviours (e.g., vigilance, disturbance) (Castillo-Guerrero et al., 2009, Maslo et al., 2012, Yu et al., 2020) Oystercatchers that spent longer foraging had lower inferred survival (van der Kolk et al., 2019) Time budgets may vary within an individual period of the annual cycle (e.g., between breeding stages, or within the non-breeding period) (Castillo-Guerrero et al., 2009, Mallory et al., 1999) or due to the presence of conspecifics (Kosztolányi et al., 2006, Mallory et al., 1999)
Site/region – Instantaneous/within season/annual
Anti-predator behaviours
Vigilance rates (Fernández and Lank, 2010) Flight initiation distance (Gunness et al., 2001) At sites where vigilance rates were higher, waterbirds maintained lower body mass (Fernández and Lank, 2010)
Site/region – Instantaneous/within season/annual
Individual movements
Home range size (Herring and Collazo, 2005) Commuting distance (Custer et al., 2004)
Site/region – Instantaneous/within season/annual
Flight speeds
Flight speeds between foraging patches (Reurink et al., 2015) Birds fly faster when heading to patches of high prey abundance because the greater expected returns are able to offset the greater flight costs of choosing to fly faster (Reurink et al., 2015) Requires the birds to have perfect knowledge of the resource distribution available (Reurink et al., 2015), which may not always be the case (Lewis et al., 2010)
Site/region – Instantaneous/within season/annual